nils-herrmann/clean_scirepeval huggingface dataset:
Improving lip-reading performance for robust audiovisual speech recognition using DNNs

This paper presents preliminary experiments using the Kaldi toolkit  to investigate audiovisual speech recognition (AVSR) in noisy environments using deep neural networks (DNNs). In particular we use a single-speaker large vocabulary, continuous audiovisual speech corpus to compare the performance of visual-only, audio-only and audiovisual speech recognition. The models trained using the Kaldi toolkit are compared with the performance of models trained using conventional hidden Markov models (HMMs). In addition, we compare the performance of a speech recognizer both with and without visual features over nine different SNR levels of babble noise ranging from 20dB down to -20dB. The results show that the DNN outperforms conventional HMMs in all experimental conditions, especially for the lip-reading only system, which achieves a gain of 37.19% accuracy (84.67% absolute word accuracy). Moreover, the DNN provides an effective improvement of 10 and 12dB SNR respectively for both the single modal and bimodal speech recognition systems. However, integrating the visual features using simple feature fusion is only effective in SNRs at 5dB and above. Below this the degradion in accuracy of an audiovisual system is similar to the audio only recognizer.
Serverless Data Analytics with Flint

Serverless architectures organized around loosely-coupled function invocations represent an emerging design for many applications. Recent work mostly focuses on user-facing products and event-driven processing pipelines. In this paper, we explore a completely different part of the application space and examine the feasibility of analytical processing on big data using a serverless architecture. We present Flint, a prototype Spark execution engine that takes advantage of AWS Lambda to provide a pure pay-as-you-go cost model. With Flint, a developer uses PySpark exactly as before, but without needing an actual Spark cluster. We describe the design, implementation, and performance of Flint, along with the challenges associated with serverless analytics.
Job Characteristics as Antecedents of Intention to Stay and Mediating Effects of Work Family Facilitation and Family Satisfaction among Single Mothers in Malaysia

Employee turnover is crucial to be investigated since it diminishes organization effectiveness and impedes the capacity to meet its goals. This study was conducted to test the mediating effects of work-family facilitation and family satisfaction on the relationship between job characteristics, and intention to stay among 240 single mother employees in Malaysia. Data was collected using self-administered research questionnaire on simple randomized respondents whereby six out of 24 single mother associations were selected to obtain research samples. Descriptive statistical analysis was conducted to describe the respondents and Pearson Product Moment Correlation to determine the relationships among variables. Structural Equation Modeling using AMOS version 16.0 was utilized for model testing and to check the presence of mediation effects in the relationships between independent and dependent variables. The Soble’s z-test was used to test whether the mediators carry the effect of the independent variables on the dependent variable. The findings indicated that single mothers have moderate levels of job characteristics in their lives, so as their levels of work-family facilitation, family satisfaction and intention to stay. There were positive and negative significant relationships among variables. The results also established the presence of mediation effects between the independent and dependent variables. Organizations may utilize work-family facilitation and family satisfaction as mechanisms to promote longer retention among employees.
Frontomaxillary facial angle in screening for trisomy 21 at 11 + 0 to 13 + 6 weeks.

Trisomy 21 is associated with a flat face, which can now be quantified by measurement of the frontomaxillary facial (FMF) angle. The aim of this study was to examine whether in trisomy 21 fetuses fetal nuchal translucency (NT) thickness and maternal serum free ss-human chorionic gonadotropin (ss-hCG) and pregnancy-associated plasma protein-A (PAPP-A) are independent of the FMF angle, and to estimate the performance of a first-trimester screening test for trisomy 21 that includes measurement of the FMF angle.



This was a prospective study in singleton pregnancies at 11 + 0 to 13 + 6 weeks of gestation in which three-dimensional volumes of the fetal head were obtained and measurement of the FMF angle performed immediately before fetal karyotyping by chorionic villus sampling (CVS). The women chose to have CVS after risk assessment by a combination of maternal age, fetal NT thickness and maternal serum free ss-hCG and PAPP-A. Regression analysis was used to examine the significance of the association within the euploid and within the trisomy 21 fetuses between the deviation from the normal median in FMF angle and the deviation in NT, free ss-hCG and PAPP-A. We estimated the detection rate (DR) and false positive rate (FPR) of first-trimester screening for trisomy 21 by measuring the FMF angle in all cases and of an alternative policy in which first-stage screening is by fetal NT and maternal serum biochemistry in all patients, followed by second-stage assessment of FMF angle only in those with an intermediate risk (1 in 51 to 1 in 1000) after the first stage.



The FMF angle was measured in 782 euploid and 108 trisomy 21 fetuses. In the euploid fetuses the mean FMF angle decreased linearly with CRL from 83.5 degrees at a crown-rump length (CRL) of 45 mm to 76.4 degrees at a CRL of 84 mm. In the euploid fetuses the mean delta FMF angle was 0.0 (SD, 4.264) degrees and the respective values in the trisomy 21 fetuses were 7.172 (SD, 4.092) degrees . Incorporating the FMF angle in first-trimester combined screening increased the estimated DR from 90 to 94% at an FPR of 5% and from 85 to 92% at an FPR of 3%. In two-stage screening it would be necessary to measure the FMF angle in 12% of cases and the DRs would be 93 and 91% at FPRs of 5 and 3%, respectively.



Measurement of the FMF angle improves the performance of first-trimester screening for trisomy 21.
How to generate cryptographically strong sequences of pseudo random bits

Much effort has been devoted in the second half of this century to make precise the notion of Randomness. Let us informally recall one of these definitions due to Kolmogorov []. A sequence of bits A =all a2••.•• at is random if the length of the minimal program outputting A is at least k We remark that the above definition is highly non constructive and rules out the possibility of pseudo random number generators. Also. the length of a program, from a Complexity Theory point of view, is a rather unnatural measure. A more operative definition of Randomness should be pursued in the light of modern Complexity Theory.
Wireless Body Area Network (WBAN): A Survey on Reliability, Fault Tolerance, and Technologies Coexistence

Wireless Body Area Network (WBAN) has been a key element in e-health to monitor bodies. This technology enables new applications under the umbrella of different domains, including the medical field, the entertainment and ambient intelligence areas. This survey paper places substantial emphasis on the concept and key features of the WBAN technology. First, the WBAN concept is introduced and a review of key applications facilitated by this networking technology is provided. The study then explores a wide variety of communication standards and methods deployed in this technology. Due to the sensitivity and criticality of the data carried and handled by WBAN, fault tolerance is a critical issue and widely discussed in this paper. Hence, this survey investigates thoroughly the reliability and fault tolerance paradigms suggested for WBANs. Open research and challenging issues pertaining to fault tolerance, coexistence and interference management and power consumption are also discussed along with some suggested trends in these aspects.
Role of cortical cell type and morphology in subthreshold and suprathreshold uniform electric field stimulation <ce:italic>in vitro</ce:italic>

The neocortex is the most common target of subdural electrotherapy and noninvasive brain stimulation modalities, including transcranial magnetic stimulation (TMS) and transcranial current simulation (TCS). Specific neuronal elements targeted by cortical stimulation are considered to underlie therapeutic effects, but the exact cell type(s) affected by these methods remains poorly understood.



We determined whether neuronal morphology or cell type predicted responses to subthreshold and suprathreshold uniform electric fields.



We characterized the effects of subthreshold and suprathreshold electrical stimulation on identified cortical neurons in vitro. Uniform electric fields were applied to rat motor cortex brain slices, while recording from interneurons and pyramidal cells across cortical layers, using a whole-cell patch clamp. Neuron morphology was reconstructed after intracellular dialysis of biocytin. Based solely on volume-weighted morphology, we developed a parsimonious model of neuronal soma polarization by subthreshold electric fields.



We found that neuronal morphology correlated with somatic subthreshold polarization. Based on neuronal morphology, we predict layer V pyramidal neuronal soma to be individually the most sensitive to polarization by optimally oriented subthreshold fields. Suprathreshold electric field action potential threshold was shown to reflect both direct cell polarization and synaptic (network) activation. Layer V/VI neuron absolute electric field action potential thresholds were lower than layer II/III pyramidal neurons and interneurons. Compared with somatic current injection, electric fields promoted burst firing and modulated action potential firing times.



We present experimental data indicating that cortical neuron morphology relative to electric fields and cortical cell type are factors in determining sensitivity to sub- and supra-threshold brain stimulation.
A systematic review and comparative analysis of cross-document coreference resolution methods and tools

Information extraction (IE) is the task of automatically extracting structured information from unstructured/semi-structured machine-readable documents. Among various IE tasks, extracting actionable intelligence from an ever-increasing amount of data depends critically upon cross-document coreference resolution (CDCR) - the task of identifying entity mentions across information sources that refer to the same underlying entity. CDCR is the basis of knowledge acquisition and is at the heart of Web search, recommendations, and analytics. Real time processing of CDCR processes is very important and have various applications in discovering must-know information in real-time for clients in finance, public sector, news, and crisis management. Being an emerging area of research and practice, the reported literature on CDCR challenges and solutions is growing fast but is scattered due to the large space, various applications, and large datasets of the order of peta-/tera-bytes. In order to fill this gap, we provide a systematic review of the state of the art of challenges and solutions for a CDCR process. We identify a set of quality attributes, that have been frequently reported in the context of CDCR processes, to be used as a guide to identify important and outstanding issues for further investigations. Finally, we assess existing tools and techniques for CDCR subtasks and provide guidance on selection of tools and algorithms.
Code quality analysis in open source software development

Proponents of open source style software development claim that better software is produced using this model compared with the traditional closed model. However, there is little empirical evidence in support of these claims. In this paper, we present the results of a pilot case study aiming: (a) to understand the implications of structural quality; and (b) to figure out the benefits of structural quality analysis of the code delivered by open source style development. To this end, we have measured quality characteristics of 100 applications written for Linux, using a software measurement tool, and compared the results with the industrial standard that is proposed by the tool. Another target of this case study was to investigate the issue of modularity in open source as this characteristic is being considered crucial by the proponents of open source for this type of software development. We have empirically assessed the relationship between the size of the application components and the delivered quality measured through user satisfaction. We have determined that, up to a certain extent, the average component size of an application is negatively related to the user satisfaction for this application.
What's up with whatsapp?: comparing mobile instant messaging behaviors with traditional SMS

With the advent of instant mobile messaging applications, traditional SMS is in danger of loosing it's reign as the king of mobile messaging. Applications like WhatsApp allow mobile users to send real-time text messages to individuals or groups of friends at no cost. While there is a vast body of research on traditional text messaging practices, little is understood about how and why people have adopted and appropriated instant mobile messaging applications. The goal of this work is to provide a deeper understanding of the motives and perceptions of a popular mobile messaging application called WhatsApp and to learn more about what this service offers above and beyond traditional SMS. To this end, we present insights from two studies an interview study and a large-scale survey highlighting that while WhatsApp offers benefits such as cost, sense of community and immediacy, SMS is still considered a more reliable, privacy preserving technology for mobile communication.
Multi-encoder Transformer Network for Automatic Post-Editing

This paper describes the POSTECH’s submission to the WMT 2018 shared task on Automatic Post-Editing (APE). We propose a new neural end-to-end post-editing model based on the transformer network. We modified the encoder-decoder attention to reflect the relation between the machine translation output, the source and the postedited translation in APE problem. Experiments on WMT17 English-German APE data set show an improvement in both TER and BLEU score over the best result of WMT17 APE shared task. Our primary submission achieves -4.52 TER and +6.81 BLEU score on PBSMT task and -0.13 TER and +0.40 BLEU score for NMT task compare to the baseline.
Structure tensor-based WLS filter for adaptive smoothing

The weighted least squares (WLS) filter is a well-known edge preserving smoothing technique, but its weights highly depend on the image gradients. Thus, it is hard to smooth local textures with large gradients by WLS filter. In this paper, we propose a structure tensor-based WLS (ST-WLS) filter to enhance the smoothing ability of WLS filter while successfully keeping object boundaries. We introduce structure tensor into WLS filter to extract local structures in an image and use them to guide the smoothing process. Specifically, we use structure tensor to measure isotropy of pixels. Then, we calculate the smoothing weights for pixels based on both their isotropy and gradients. Experimental results demonstrate that ST-WLS filter has strong ability of smoothing textures, especially for isotropic textures, while preserving boundaries and structures of objects.
Recommending resolutions of ITIL services tickets using Deep Neural Network

Application development and maintenance is a good example of Information Technology Infrastructure Library (ITIL) services in which a sizable volume of tickets are raised everyday for different issues to be resolved in order to deliver uninterrupted service. An issue is captured as summary on the ticket and once a ticket is resolved, the solution is also noted down on the ticket as resolution. It will be beneficial to automatically extract information from the description of tickets to improve operations like identifying critical and frequent issues, grouping of tickets based on textual content, suggesting remedial measures for them etc. In particular, the maintenance people can save a lot of effort and time if they have access to past remedial actions for similar kind of tickets raised earlier based on history data. In this work we propose an automated method based on deep neural networks for recommending resolutions for incoming tickets. We use ideas from deep structured semantic models (DSSM) for web search for such resolution recovery. We project a small subset of existing tickets in pairs and an incoming ticket to a low dimensional feature space, following which we compute the similarity of an existing ticket with the new ticket. We select the pair of tickets which has the maximum similarity with the incoming ticket and publish both of its resolutions as the suggested resolutions for the latter ticket. The experiment of our data sets shows that we are able to achieve a promising similarity match of about 70% - 90% between the suggestions and the actual resolution.
Enhance emotional and social adaptation skills for children with autism spectrum disorder: A virtual reality enabled approach

Deficits in social-emotional reciprocity, one of the diagnostic criteria of Autism Spectrum Disorder (ASD), greatly hinders children with ASD from responding appropriately and adapting themselves in various social situations. Although evidences have shown that virtual reality environment is a promising tool for emotional and social adaptation skills training on ASD population, there is a lack of large-scale trials with intensive evaluations to support such findings. This paper presents a virtual reality enabled program for enhancing emotional and social adaptation skills for children with ASD. Six unique learning scenarios, of which one focuses on emotion control and relaxation strategies, four that simulate various social situations, and one that facilitates consolidation and generalization, are designed and developed with corresponding psychoeducation procedures and protocols. The learning scenarios are presented to the children via a 4-side immersive virtual reality environment (a.k.a., half-CAVE) with non-intrusive motion tracking. A total number of 94 children between the ages of 6 to 12 with clinical diagnosis of ASD participated in the 28-session program that lasted for 14 weeks. By comparing preand post-assessments, results reported in this paper show significant improvements in the project’s primary measures on children’s emotion expression and regulation and social-emotional reciprocity but not on other secondary measures.
A 240 × 180 130 dB 3 µs Latency Global Shutter Spatiotemporal Vision Sensor

Event-based dynamic vision sensors (DVSs) asynchronously report log intensity changes. Their high dynamic range, sub-ms latency and sparse output make them useful in applications such as robotics and real-time tracking. However they discard absolute intensity information which is useful for object recognition and classification. This paper presents a dynamic and active pixel vision sensor (DAVIS) which addresses this deficiency by outputting asynchronous DVS events and synchronous global shutter frames concurrently. The active pixel sensor (APS) circuits and the DVS circuits within a pixel share a single photodiode. Measurements from a 240×180 sensor array of 18.5 μm 2 pixels fabricated in a 0.18 μm 6M1P CMOS image sensor (CIS) technology show a dynamic range of 130 dB with 11% contrast detection threshold, minimum 3 μs latency, and 3.5% contrast matching for the DVS pathway; and a 51 dB dynamic range with 0.5% FPN for the APS readout.
A File Comparison Program

A file comparison program produces a list of differences between two files. These differences can be couched in terms of lines, e.g. by telling which lines must be inserted, deleted or moved to convert the first file to the second. Alternatively, the list of differences can identify individual bytes. Byte-oriented comparisons are useful with non-text files, such as compiled programs, that are not divided into lines. The approach adopted here is to generate only instructions to insert or delete entire lines. Since lines are treated as indivisible objects, files can be treated as containing lines consisting of a single symbol. In other words, an n-line file is modelled by a string of n symbols. In more formal terms, the file comparison problem can be rephrased as follows. The edit distance between two strings of symbols is the length of a shortest sequence of insertions and deletions that will convert the first string to the second. T h e goal, then, is to write a program that computes the edit distance between two arbitrary strings of symbols. In addition, the program must explicitly produce a shortest possible edit script (i.e. sequence of edit commands) for the given strings. Other approaches have been tried. For example, Tichy ' discusses a file-comparison tool that determines how one file can be constructed from another by copying blocks of lines and appending lines. However, the ability to economically generate shortestpossible edit scripts depends critically on the repertoire of instructions that are allowed in the scripts.2 File comparison algorithms have a number of potential uses beside merely producing a set of edit commands to be read by someone trying to understand the evolution of a program or document. For example, the edit scripts might be text editor instructions that are saved to avoid the expense of storing nearly identical files. Rather than storing
FRIP: a region-based image retrieval tool using automatic image segmentation and stepwise Boolean AND matching

We present our region-based image retrieval tool, finding region in the picture (FRIP), that is able to accommodate, to the extent possible, region scaling, rotation, and translation. Our goal is to develop an effective retrieval system to overcome a few limitations associated with existing systems. To do this, we propose adaptive circular filters used for semantic image segmentation, which are based on both Bayes' theorem and texture distribution of image. In addition, to decrease the computational complexity without losing the accuracy of the search results, we extract optimal feature vectors from segmented regions and apply them to our stepwise Boolean AND matching scheme. The experimental results using real world images show that our system can indeed improve retrieval performance compared to other global property-based or region-of-interest-based image retrieval methods.
A reconfigurable low-noise dynamic comparator with offset calibration in 90nm CMOS

This paper presents a reconfigurable, low offset, low noise and high speed dynamic clocked-comparator for medium to high resolution Analog to Digital Converters (ADCs). The proposed comparator reduces the input referred noise by half and shows a better output driving capability when compared with the previous work. The offset, noise and power consumption can be controlled by a clock delay which allows simple reconfiguration. Moreover, the proposed offset calibration technique improves the offset voltage from 11.6mV to 533μV at 1 sigma. A prototype of the comparator is implemented in 90nm 1P8M CMOS with experimental results showing 320μV input referred noise at 1.5GHz with 1.2V supply.