Miracle-dz/UniFAR-FTUs huggingface dataset:
EEG signal processing for eye tracking

Head-mounted Video-Oculography (VOG) eye tracking is visually intrusive due to a camera in the peripheral view. Electrooculography (EOG) eye tracking is socially intrusive because of face-mounted electrodes. In this work we explore Electroencephalography (EEG) eye tracking from less intrusive wireless cap scalp-based electrodes. Classification algorithms to detect eye movement and the focus of foveal attention are proposed and evaluated on data from a matched dataset of VOG and 16-channel EEG. The algorithms utilise EOG artefacts and the brain's steady state visually evoked potential (SSVEP) response while viewing flickering stimulus. We demonstrate improved performance by extracting features from source signals estimated by Independent Component Analysis (ICA) rather than the traditional band-pass preprocessed EEG channels. The work envisages eye tracking technologies that utilise non-facially intrusive EEG brain sensing via wireless dry contact scalp based electrodes.
Co-evolution of Morphology , Control and Behavior Master project

Currently, the maneuverability of robots is obtained by human design and is specific to each robot. There are no generic ways of designing robots with maneuverability skills. In this paper we investigate the use of co-evolution of body and mind in virtual robots to optimize maneuverability. Robots were successfully evolved to respond to steering commands and speed commands. It has been demonstrated that specific morphologies and controls are required to suite the maneuverability criteria. The robots developed for this project are designed to mimic animal morphologies and controls. Their body is constrained to produce only legged robots. The control is performed by a Central Pattern Generators network. The specific design of the robots constrains the search space and produce more easily realistic robots, especially robots using legged locomotion.
Mining search and browse logs for web search

Huge amounts of search log data have been accumulated at Web search engines. Currently, a popular Web search engine may receive billions of queries and collect terabytes of records about user search behavior daily. Beside search log data, huge amounts of browse log data have also been collected through client-side browser plugins. Such massive amounts of search and browse log data provide great opportunities for mining the wisdom of crowds and improving Web search. At the same time, designing effective and efficient methods to clean, process, and model log data also presents great challenges. In this survey, we focus on mining search and browse log data for Web search. We start with an introduction to search and browse log data and an overview of frequently-used data summarizations in log mining. We then elaborate how log mining applications enhance the five major components of a search engine, namely, query understanding, document understanding, document ranking, user understanding, and monitoring and feedback. For each aspect, we survey the major tasks, fundamental principles, and state-of-the-art methods.
The Thermal radiation of the isolated neutron star RX J1856.5-3754 observed with Chandra and XMM-Newton

We present results of the analysis of data collected in 57-ks XMM-Newton and 505-ks Chandra observations of the nearby ($\simeq $120 pc) isolated neutron star RX J1856.5–3754. We confirm most of the statements made by Burwitz et al. (2001) who discussed the original 55-ks Chandra data. Detailed spectral analysis of the combined X-ray and optical data rules out the currently available nonmagnetic light and heavy element neutron star atmosphere (LTE) models with hydrogen, helium, iron and solar compositions. We find that strongly magnetized atmosphere models also are unable to represent the data. The X-ray and optical data show no spectral features and are best fitted with a two-component blackbody model with $kT_{\rm bb,X}^\infty \simeq 63.5$ eV and $R_{\rm bb,X}^\infty\simeq\,4.4\,(d/120\,\rm pc)$ km for the hot X-ray emitting region, and $kT_{\rm bb,opt}^\infty $ 17 ( d /120 pc) km for the rest of the neutron star surface responsible for the optical flux. The large number of counts collected with XMM-Newton allows us to reduce the upper limit on periodic variation in the X-ray range down to 1.3% (at a 2 σ confidence level) in the $10^{-3}{-}50$ Hz frequency range. In an attempt to explain this small variability, we discuss an one-component model with $kT_{\rm bb}^{\infty}\simeq 63$ eV and $R_{\rm bb}^{\infty}\simeq 12.3\,(d/120\,{\rm pc})$ km. This model requires a low radiative efficiency in the X-ray domain, which may be expected if the neutron star has a condensed matter surface.
On ALADIN precipitation modeling and validation in an Alpine watershed

Abstract. Highly resolved precipitation forecasts are necessary in many applications, especially in mountain meteorology and flash flood forecasts for small- to medium-sized alpine watersheds. Here we present precipitation forecasts simulated by the limited area model ALADIN applying different grid resolutions ( D x = 10 km and 4 km). Target area of the investigations is the Alpine Ticino-Verzasca-Maggia watershed (total area: 2627 km 2 ). We discuss problems of validation of high-resolution precipitation forecasts by comparison with observed precipitation fields and apply an indirect validation approach by using ALADIN forecasts as input to hydrologic simulations. These simulations are carried out with the distributed hydrologic model WaSiM-ETH ( D x = 500 m, D t = 1 h). The time step of meteorological input to WaSiM-ETH is fixed at 1 h but spatial resolution varies. The main result of the validation experiments for three heavy precipitation events is, that coarser-scale ALADIN forecasts (in model version 11.2) provide better precipitation predictors for hydrologic modeling than higher-resolution forecasts. The experiments demonstrate that hydrologic modeling is a promising tool for the evaluation of high-resolution precipitation fields. Key words. Hydrology (floods) – Meteorology and atmospheric dynamics (mesoscale meteorology; precipitation)
Unsupervised adaptation of PLDA by using variational Bayes methods

State-of-the-art speaker recognition relays on models that need a large amount of training data. This models are successful in tasks like NIST SRE because there is sufficient data available. However, in real applications, we usually do not have so much data and, in many cases, the speaker labels are unknown. We present a method to adapt a PLDA model from a domain with a large amount of labeled data to another with unlabeled data. We describe a generative model that produces both sets of data where the unknown labels are modeled like latent variables. We used variational Bayes to estimate the hidden variables. We performed experiments adapting a model trained on Switchboard to NIST SRE without labels. The adapted model is evaluated on NIST SRE10. Compared to the non-adapted model, EER improved by 42% and 49% by adapting with 200 and with all the NIST speakers respectively.
A high performance DSP controller for three-phase PWM rectifiers with ultra low input current THD under unbalanced and distorted input voltage

Although in recent years three-phase PWM rectifiers have become increasingly popular, in most practical cases the line unbalance and/or the presence of distortion can seriously affect their performances. Line unbalance and distortion add unwanted low frequency harmonics to the input current, leading to an increase in the total harmonic distortion (THD). At high power level, the switching frequency is restricted to a few kilo hertz and therefore an LC filter is needed to eliminate the switching ripple of the current. The resulting structure is an LCL filter that causes instabilities and oscillations. This paper details how to implement a high performance multi-loop digital controller suitable for a boost type PWM rectifier, leading to an extremely low THD content even with non-ideal input voltage conditions. The multi-loop method uses only two capacitor filter voltages and inverter currents to estimate the line voltages and currents. Positive and negative sequence controllers are used to regulate the fundamental currents while resonant controllers tuned to each harmonic from third to thirteenth remove the low frequency components due to input voltage unbalance and/or distortion. The proposed approach is implemented on a 16-bit fixed point DSP (ADMC401) and tested on a three-phase 20 kW IGBT-based PWM rectifier.
Semantic Class Hierarchies by Abstract Interpretation

A generic semantic-based framework is presented for the definition and manipulation of class hierarchies for object-oriented languages. The framework is based on the notion of observable of a class, i.e. an abstraction of its semantics when focussing on a behavioral property of interest. By exploiting such a notion, we define the semantic subclass relation, capturing the fact that a subclass preserves the behavior of its superclass up to a given (tunable) observed property. We study the relation between syntactic subclass, as present in mainstream object-oriented languages, and the notion of semantic subclass. Such an approach is then extended to class hierarchies, leading to a semantic-based modular treatment of a suite of basic observable-preserving operators on hierarchies. We instantiate the framework by presenting effective algorithms that compute a semantic superclass for two given classes, that extend a hierarchy with a new class, and that merge two hierarchies by preserving semantic subclass relations.
Association of Plasma Natriuretic Peptide Levels With Metabolic Risk Factors in Ambulatory Individuals

Background— Experimental studies suggest that the natriuretic peptides influence lipid and fatty acid metabolism. Although it has been shown that obese individuals have reduced natriuretic peptide levels, conflicting data exist on the relation of natriuretic peptide levels to other metabolic risk factors. Methods and Results— We examined the association of plasma levels of B-type natriuretic peptide and N-terminal pro-atrial natriuretic peptide with metabolic risk factors, the metabolic syndrome, and insulin resistance in 3333 Framingham study participants free of heart failure (mean age, 58 years; 54% women). Regression analyses were performed, with adjustment for clinical and echocardiographic variables. Plasma natriuretic peptide levels were inversely associated with all components of the metabolic syndrome except for elevated blood pressure. Adjusted natriuretic peptide levels were lower in persons with the metabolic syndrome compared with those without the metabolic syndrome: In men, B-type natriuretic peptide was 24% lower (P<0.001) and N-terminal pro-atrial natriuretic peptide was 16% lower (P<0.001); in women, B-type natriuretic peptide was 29% lower (P<0.001) and N-terminal pro-atrial natriuretic peptide was 18% lower (P<0.001). Individuals with insulin resistance, as indicated by an elevated homeostasis model assessment (HOMA-IR) index, had lower levels of B-type natriuretic peptide (P=0.009 in men, P<0.001 in women) and N-terminal pro-atrial natriuretic peptide (P<0.001 in men, P=0.001 in women). Conclusions— Having several metabolic risk factors is associated with low circulating natriuretic peptide levels, even after adjustment for body mass index. These findings raise the possibility that reduced natriuretic peptide activity is a manifestation of the metabolic syndrome, which may have important clinical and pathophysiological implications.
The Path of Presupposition Projection in Processing - The case of Conditionals

While presupposition projection has been explored in depth in theoretical terms, not much is known about possible cognitive processes related to it. We investigate the question of whether projection, which can be seen as a mismatch between the location of where material is introduced syntactically and the level at which it is interpreted, comes with a processing cost that requires additional processing time. In an eye tracking reading study using conditional sentences with German wieder (‘again’) in the consequent and a preceding context sentence, we varied the relative location in which the presupposition of wieder was supported. We argue that the pattern of results we get reflects a processing cost for projection that directly correlates with the length of the projection path as it would be measured in Discourse Representation Theory (DRT). This perspective on the data crucially relies on the representational mechanisms involved in projection, which implies that a non-representational theory such as dynamic semantics cannot offer the same account. A simple processing hypothesis based on distance from presuppositional support measured in clauses also does not suffice to explain the data. The paper thus offers experimental evidence bearing on fine-grained theoretical choices in presupposition theory. It closes by relating our results to some other recent experimental work on presupposition interpretation.
"It’s an app. It’s a hypervisor. It’s a hypapp.": Design and Implementation of an eXtensible and Modular Hypervisor Framework (CMU-CyLab-12-014)

Abstract : This paper presents our efforts in developing XMHF, an eXtensible and Modular Hypervisor Framework. XMHF takes a developer-centric approach to hypervisor design and implementation, and strives to be a comprehensible and flexible platform for performing hypervisor research and development. XMHF encapsulates common hypervisor core functionality in a framework that allows others to build custom hypervisor-based solutions (called hypapps) while freeing them from a considerable amount of wheel-reinventing that is often associated with such efforts. We are encouraged by the end result - a clean, barebones hypervisor framework with desirable performance characteristics and an architecture amenable to formal analysis.
Hybrid Named Entity Recognition - Application to Arabic Language

Most Named Entity Recognition (NER) systems follow either a rule-based approach or machine learning approach. In this paper, we introduce out attempt at developing a hybrid NER system, which combines the rule-based approach with a machine learning approach in order to obtain the advantages of both approaches and overcomes their problems [1]. The system is able to recognize eight types of named entities including Location, Person, Organization, Date, Time, Price, Measurement and Percent. Experimental results on ANERcorp dataset indicated that our hybrid approach outperforms the rule-based approach and the machine learning approach when they are processed separately. Moreover, our hybrid approach outperforms the state-of-the-art of Arabic NER.
Impact of patients' choice for single embryo transfer of a top quality embryo versus double embryo transfer in the first IVF/ICSI cycle.

BACKGROUND The aim of this study was to evaluate the impact of transferring a single top quality embryo in the first IVF/ICSI cycle of patients <38 years old who chose to have one or two embryos transferred. METHODS A total of 262 patients participated in the study, and 243 transfers were performed: 156 (64%) patients chose the transfer of a single top quality embryo, if available, and two non-top quality embryos if not available; 87 (36%) patients chose to have a double embryo transfer regardless of embryo quality. RESULTS In the first group an ongoing pregnancy rate of 40% (63/156) with a twin pregnancy rate of 2% (1/63) was achieved. In the second group the ongoing pregnancy rate was 44% (38/87) with 26% (10/38) twin pregnancies. In the patient group with only one embryo transferred, irrespective of the patient's choice, the ongoing pregnancy rate was 43% (54/127) with no twin pregnancies. For the study population as a whole, the ongoing pregnancy rate was 42% (101/243) with 11% (11/101) twins. CONCLUSION We conclude that the introduction of single embryo transfer in the first IVF/ICSI cycle is highly acceptable in women <38 years old.
A generic Reverse Conducting IGBT structure for monolithic switching cells integration

A generic structure of a Reverse Conducting IGBT (RC-IGBT) that integrates monolithically an IGBT for the forward conduction and a self-firing thyristor for the reverse conduction is proposed. As compared to the conventional RC-IGBT, the structure that we propose doesn't exhibit snap-back in the forward conducting mode [1], [2]. The static and dynamic performances of the structure are investigated in this paper by 2D Sentaurus™ numerical simulations. The proposed structure is then used to design two complementary monolithic power chips, named “Common Anode three-pole” and “Common Cathode three-pole”, within the context of “two-chip” integration of static power converter [4]. These two chips are then associated to form a complete inverter. The proposed three-pole common cathode chip uses a P+ wall for insulation between the two adjacent RC-IGBT sections. The proposed elementary RC-IGBT uses also the P+ wall in order to ensure the thyristor triggering in the reverse conducting mode.
An Evaluation of Component Adaptation Techniques

Adapting existing code to include additional functionality or behavior is a common theme in software engineering. These e(cid:11)orts are complicated because the developer adapting the code will rarely be the designer of the code. As object-oriented and component-based software development achieve greater widespread use, there will be a distinct need to support such third-party adaptation. This paper describes the issues and challenges surrounding component adaptation and surveys various approaches in the literature. We evaluate these adaptation techniques by comparing their use in adapting an existing component in a sample application. Our experience leads us to a better understanding of the similarities and di(cid:11)erences between existing adaptation techniques.
An Examination of Variability in Identification of Learning Disabled Students according to Selected Discrepancy Formulas over a Three Year Period.

ABSTRACT Cumulative files on 276 students (grades 2-12) identified as learning disabled (LD) were analyzed in the project designed to investigate effects of LD selection formulas and the influence of various LD services. Analyses revealed that few (3-5%) of the students were identified as LD by formulas demanding a substantial IQ achievement discrepancy; a significant decline in achievement from time of placement to time of reevaluation while mean IQ remained constant; and a paucity of significant results linking such characteristics as birth order and parental occupational status with learning disabilities. Students in self-contained classes tended to be more discrepant over time, particularly in the area of written expression. White Ss tended to be more discrepant in reading and math than black Ss. Evaluation instruments and data tables are appended. (CL)
The Starting School Study: Mothers' Perspectives of Transition to School

THE STARTING SCHOOL STUDY explored the transition to school from the perspectives of parents living in a disadvantaged area of Sydney, Australia. Fifty-seven parents participated in semi-structured interviews about their child's transition to school between 2009 and 2011. Topics discussed included: preparation for school, the first day, school relationships, supports and barriers to involvement and aspirations. A team of researchers working collaboratively in 2011 consolidated national and international research and theory of transition to school, to develop and publish an aspirational document entitled Transition to school: Position statement. The statement recognised and promoted the importance of transition to school using four constructs: opportunities, expectations, entitlements and aspirations. The results of the Starting School Study are discussed using these constructs. Overall, mothers in the study valued education, wanted their children to achieve and be successful, and hoped their children would have positive experiences of school; better than their own. The pivotal role of the teacher is discussed.
Towards the Formal Modeling of a Secure Operating System

To construct a secure operating system with high assurance, it is essential that the security architecture of the operating system can be analyzed vigorously and that the architecture can be easily understood by engineers who translate the design into code. In this paper we describe a partial model of the security policies of an operating system which implements a variant of the Bell-LaPadula model. In particular, we describe the privileges of trusted subjects and how they are used in granting accesses. We use a combination of an object-oriented modeling technique, the Unified Modeling Language (UML), and a mathematically-based formal method called Higher-Order Logic (HOL). UML provides a visual, intuitive model that is easy to write and easily understood by engineers. HOL provides a rigorous model whose properties can be mechanically proved, thus allowing the correctness of the model to be established. UML models provide the structure for natural language descriptions and HOL models. HOL models add precise semantics to both text descriptions and UML models.
Dynamic changes of the respiratory microbiota and its relationship to fecal and blood microbiota in healthy young cats

Advances in the field of metagenomics using culture-independent methods of microbial identification have allowed characterization of rich and diverse communities of bacteria in the lungs of healthy humans, mice, dogs, sheep and pigs. These data challenge the long held belief that the lungs are sterile and microbial colonization is synonymous with pathology. Studies in humans and animals demonstrate differences in the composition of airway microbiota in health versus disease suggesting respiratory dysbiosis occurs. Using 16S rRNA amplicon sequencing of DNA extracted from rectal and oropharyngeal (OP) swabs, bronchoalveolar lavage fluid (BALF), and blood, our objective was to characterize the fecal, OP, blood, and lower airway microbiota over time in healthy cats. This work in healthy cats, a species in which a respiratory microbiota has not yet been characterized, sets the stage for future studies in feline asthma in which cats serve as a comparative and translational model for humans. Fecal, OP and BALF samples were collected from six healthy research cats at day 0, week 2, and week 10; blood was collected at week 10. DNA was extracted, amplified via PCR, and sequenced using the Illumina MiSeq platform. Representative operational taxonomic units (OTUs) were identified and microbial richness and diversity were assessed. Principal component analysis (PCA) was used to visualize relatedness of samples and PERMANOVA was used to test for significant differences in microbial community composition. Fecal and OP swabs provided abundant DNA yielding a mean±SEM of 65,653±6,145 and 20,6323±4,360 sequences per sample, respectively while BALF and blood samples had lower coverage (1,489±430 and 269±18 sequences per sample, respectively). Oropharyngeal and fecal swabs were significantly richer than BALF (mean number OTUs 93, 88 and 36, respectively; p < 0.001) with no significant difference (p = 0.180) in richness between time points. PCA revealed site-specific microbial communities in the feces, and upper and lower airways. In comparison, blood had an apparent compositional similarity with BALF with regard to a few dominant taxa, but shared more OTUs with feces. Samples clustered more by time than by individual, with OP swabs having subjectively greater variation than other samples. In summary, healthy cats have a rich and distinct lower airway microbiome with dynamic bacterial populations. The microbiome is likely to be altered by factors such as age, environmental influences, and disease states. Further data are necessary to determine how the distinct feline microbiomes from the upper and lower airways, feces and blood are established and evolve. These data are relevant for comparisons between healthy cats and cats with respiratory disease.