Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent controlled three-phase squirrel-cage induction generator system using wavelet fuzzy neural network for wind power

An intelligent controlled three-phase squirrel-cage induction generator (SCIG) system for grid-connected wind power application using wavelet fuzzy neural network (WFNN) is proposed in this study. First, the indirect field-oriented mechanism is implemented for the control of the SCIG system. Then, an AC/DC power converter and a DC/AC power inverter are developed to convert the electric power generated by a three-phase SCIG from variable-voltage and variable-frequency to constant-voltage and constant-frequency. Moreover, the intelligent WFNN controller is proposed for both the AC/DC power converter and DC/AC power inverter to improve the transient and steady-state responses of the SCIG system at different operating conditions. Three online trained WFNNs using backpropagation learning algorithm are implemented as the tracking controllers for the DC-link voltage of the AC/DC power converter and the active power and reactive power outputs of the DC/AC power inverter. Furthermore, the network structure and the online learning algorithm of the WFNN are introduced in detail. Finally, some experimental results are provided to demonstrate the effectiveness of the proposed SCIG system for wind power.
Design for Efficiency Improvement and Future prediction in Multi Chip Module for DC-DC Converter

We present the importance of all the parasitic inductance of the main current path. In order to reduce this parasitic inductance, we adopted new multi chip module (MCM). The MCM has successfully improved the conversion efficiency because of its minimum parasitic inductances. We also introduced new figure of merit (FOM), RonQstr, corresponding to reduction of parasitic LCR. The value of new FOM of conventional trench MOSFET is favorable and efficiency is expected to be reduced by parasitic LCR.
Noninvasive detection of spatiotemporal activation-repolarization interactions that prime idiopathic ventricular fibrillation

Description Premature beats originating in clinically concealed areas of local early repolarization promote ventricular arrhythmias and sudden cardiac arrest. Detecting arrhythmogenic electrical interactions The interactions between triggers for ventricular fibrillation (VF) and subtle repolarization abnormalities of the heart have been difficult to study because these changes are not typically detected on a standard electrocardiogram. Here, Cluitmans and colleagues combined perfused explanted human and pig heart studies with computational modeling and electrocardiographic imaging of survivors of idiopathic VF to better understand how the steepness of repolarization time (RT) gradients and the sizes of different repolarization regions contributed to idiopathic VF development. The authors found that the timing of a premature beat and its origination from an early RT region, as well as the presence of a steep RT gradient and the sizes of regions with early and late repolarization, led to the development of idiopathic ventricular fibrillation, suggesting that targeted interventions may be possible. A comprehensive understanding of the interaction between triggers and electrical substrates leading to ventricular fibrillation (VF) and sudden cardiac arrest is lacking, and electrical substrates are difficult to detect and localize with current clinical tools. Here, we created repolarization time (RT) dispersion by regional drug infusion in perfused explanted human (n = 1) and porcine (n = 6) hearts and in a computational model of the human ventricle. Arrhythmia induction was tested with a single ventricular extrastimulus applied at the early or late RT region. Arrhythmias could only be induced from early RT regions. Vulnerability to VF increased with RT gradient steepness and with larger areas of early RT, but not with markers on the body-surface electrocardiogram. Noninvasive electrocardiographic imaging was performed in survivors of idiopathic VF (n = 11), patients with frequent premature ventricular complexes (PVCs) but no history of sudden cardiac arrest (n = 7), and controls (n = 10). In survivors of idiopathic VF, RT gradients were steeper than in controls, without differences in the clinical electrocardiogram, consistent with the ex vivo results. Patients with idiopathic VF also showed local myocardial regions with distinctly early-versus-late RT that were more balanced in size than in controls. Premature beats originated more often from the early RT regions in idiopathic VF survivors than in patients with frequent PVCs only. Thus, idiopathic VF emerges from the spatiotemporal interaction of a premature beat from an early-repolarization region with critical repolarization dispersion in that region. Electrocardiographic imaging can uncover the co-occurrence of these abnormalities.
Face recognition system for uncontrolled environment

: Biometrics is a technique for identifying and authenticating a person based on a set of recognized and verifiable data that is unique and distinctive to that person. As a result, it recognizes the individual based on both global and local characteristics. Because many identity methods, such as password/PIN systems and token systems, have problems with counterfeiting, theft, and lapses in human memory, biometric identification systems have been developed as a response. The identifying mechanism in these biometric identification systems is based on physiological features. For recognition, the Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) algorithms use global features and Elastic Bunch Graph Matching (EBGM) recognizes images based on a similarity function between the given images and the graph that has been generated. In the Local Binary Pattern (LBP) approach, the image of the face is first split into smaller components, from which LBP retrieved features are fused into a feature space histogram that effectively describes the facial image. Face recognition will face issues such as facial variation, illumination from a range of light sources, image aging, occlusion, and so on. In order to solve most of the issues, a new method using the LBP Contrast Adjustment, Bilateral Filter, and Histogram Equalization were proposed as part of the algorithm. Experiments are carried out on both standard and real data sets to show that the suggested technique outperforms previously proposed algorithms.
The Design of the Bow 1

Theinventionofthebowandarrowprobablyranksforsocialimpactwiththeinvention of the art of kindling a flre and the invention of the wheel. It must have been in prehistoric times that the flrst missile was launched with a bow, we do not know where and when. The event may well have occurred in difierent parts of the world at aboutthe sametime orat widelydifiering times. Numerous kinds of bows are known, they may have long limbs or short limbs, upperandlowerlimbsmaybeequalorunequalinlengthwhilstcross-sectionsofthe limbs may take various shapes. Wood or steel may be used,singly as in ‘self’ bows, or mixed when difierent layers are glued together. There are ‘composite’ bows with layers of several kinds of organic material, wood, sinew and horn, and, in modern forms,layersofwoodandsyntheticplasticsreinforcedwithglassflbreorcarbon. The shapeofthebowwhenrelaxed,maybestraight orrecurved,wherethecurvatureof the partsof the limbsof the unstrungbowis opposite to the way they are ∞exedto fltthe string. Inpreviouspaperswehave dealt withthemechanics ofthebowandarrow. The main subject of this paper is the design and construction of bows. Nondimensionalization of the problem leads to the introduction of the maximum elastic energy storage capacity per unit of mass as a material constant for strength. At the same timeacoe‐cientisderivedwhichmeasurestheefiectivenessoftheformofthecrosssection of a bendingbeam. The assumption that the limbs of a bow are fully loaded implies a relationship between a number of design parameters. It reduces the dimension of the design parameter space. When the strength of materials is taken into account constraints are imposedona numberof designparameters. Thisdeflnesfeasible regions. Sensitivity analysis gives the in∞uence of a number of important parameters on
The significance of zero space vector placement for carrier based PWM schemes

Pulse width modulation has been one of the most intensively investigated areas of power electronics for many years, and the number and combination of permutations seem to be endless. However, a general hierarchial consensus appears to have emerged from this work which ranks space vector modulation techniques, regular sampled modulation and sine-triangle modulation strategies in decreasing order of merit based on harmonic performance. However, what has not been clearly identified is why space vector modulation should lead to a reduced harmonic current ripple compared to regular sampled modulation, especially since it is straightforward to show that they produce identical low frequency fundamental components. This paper addresses this issue, by showing how it is the placement of the zero space vector component within the carrier interval that determines the harmonic performance of the modulation strategy, rather than any intrinsic differences between the various methods of calculating the switching instances.
Automatic Transformation of Clinical Narratives into Structured Format

Vast amounts of data in healthcare are available in unstructured text format, usually in the local language of the countries. These documents contain valuable information. Secondary use of clinical narratives and information extraction of key facts and relations from them about the patient disease history can foster preventive medicine and improve healthcare. In this paper, we propose a hybrid method for the automatic transformation of clinical text into a structured format. The documents are automatically sectioned into the following parts: diagnosis, patient history, patient status, lab results. For the “Diagnosis” section a deep learning text-based encoding into ICD-10 codes is applied using MBG-ClinicalBERT - a fine-tuned ClinicalBERT model for Bulgarian medical text. From the “Patient History” section, we identify patient symptoms using a rule-based approach enhanced with similarity search based on MBG-ClinicalBERT word embeddings. We also identify symptom relations like negation. For the “Patient Status” description, binary classification is used to determine the status of each anatomic organ. In this paper, we demonstrate different methods for adapting NLP tools for English and other languages to a low resource language like Bulgarian.
Low Resource Multimodal Neural Machine Translation of English-Hindi in News Domain

Incorporating multiple input modalities in a machine translation (MT) system is gaining popularity among MT researchers. Unlike the publicly available dataset for Multimodal Machine Translation (MMT) tasks, where the captions are short image descriptions, the news captions provide a more detailed description of the contents of the images. As a result, numerous named entities relating to specific persons, locations, etc., are found. In this paper, we acquire two monolingual news datasets reported in English and Hindi paired with the images to generate a synthetic English-Hindi parallel corpus. The parallel corpus is used to train the English-Hindi Neural Machine Translation (NMT) and an English-Hindi MMT system by incorporating the image feature paired with the corresponding parallel corpus. We also conduct a systematic analysis to evaluate the English-Hindi MT systems with 1) more synthetic data and 2) by adding back-translated data. Our finding shows improvement in terms of BLEU scores for both the NMT (+8.05) and MMT (+11.03) systems.
Mining Bilingual Word Pairs from Comparable Corpus using Apache Spark Framework

Bilingual dictionaries are essential resources in many areas of natural language processing tasks, but resource-scarce and less popular language pairs rarely have such. Efficient automatic methods for inducting bilingual dictionaries are needed as manual resources and efforts are scarce for low-resourced languages. In this paper, we induce word translations using bilingual embedding. We use the Apache Spark framework for parallel computation. Further, to validate the quality of the generated bilingual dictionary, we use it in a phrase-table aided Neural Machine Translation (NMT) system. The system can perform moderately well with a manual bilingual dictionary; we change this into our inducted dictionary. The corresponding translated outputs are compared using the Bilingual Evaluation Understudy (BLEU) and Rank-based Intuitive Bilingual Evaluation Score (RIBES) metrics.
Building A Corporate Corpus For Threads Constitution

In this paper we describe the process of build-ing a corporate corpus that will be used as a ref-erence for modelling and computing threadsfrom conversations generated using commu-nication and collaboration tools. The overallgoal of the reconstruction of threads is to beable to provide value to the collorator in var-ious use cases, such as higlighting the impor-tant parts of a running discussion, reviewingthe upcoming commitments or deadlines, etc. Since, to our knowledge, there is no avail-able corporate corpus for the French languagewhich could allow us to address this prob-lem of thread constitution, we present here amethod for building such corpora includingdifferent aspects and steps which allowed thecreation of a pipeline to pseudo-anonymisedata. Such a pipeline is a response to theconstraints induced by the General Data Pro-tection Regulation GDPR in Europe and thecompliance to the secrecy of correspondence.
Paragraph Similarity Matches for Generating Multiple-choice Test Items

Multiple-choice questions (MCQs) are widely used in knowledge assessment in educational institutions, during work interviews, in entertainment quizzes and games. Although the research on the automatic or semi-automatic generation of multiple-choice test items has been conducted since the beginning of this millennium, most approaches focus on generating questions from a single sentence. In this research, a state-of-the-art method of creating questions based on multiple sentences is introduced. It was inspired by semantic similarity matches used in the translation memory component of translation management systems. The performance of two deep learning algorithms, doc2vec and SBERT, is compared for the paragraph similarity task. The experiments are performed on the ad-hoc corpus within the EU domain. For the automatic evaluation, a smaller corpus of manually selected matching paragraphs has been compiled. The results prove the good performance of Sentence Embeddings for the given task.
Web-sentiment analysis of public comments (public reviews) for languages with limited resources such as the Kazakh language

In the pandemic period, the stay-at-home trend forced businesses to switch their activities to digital mode, for example, app-based payment methods, social distancing via social media platforms, and other digital means have become an integral part of our lives. Sentiment analysis of textual information in user comments is a topical task in emotion AI because user comments or reviews are not homogeneous, they contain sparse context behind, and are misleading both for human and computer. Barriers arise from the emotional language enriched with slang, peculiar spelling, transliteration, use of emoji and their symbolic counterparts, and code-switching. For low resource languages sentiment analysis has not been worked upon extensively, because of an absence of ready-made tools and linguistic resources for sentiment analysis. This research focuses on developing a method for aspect-based sentiment analysis for Kazakh-language reviews in Android Google Play Market.
Approximate analytical model for fluid film force of finite length plain journal bearing

Non-linear dynamic performance of rotor–bearing systems supported by plain journal bearings strongly depends on the mathematical oil film force model. In this article, the analytical solution of oil film pressure for finite length plain journal bearing is obtained by employing the separation of variables method to analytically solve the Reynolds equation based on dynamic Gümbel boundary conditions. The analytical expression of oil film force is then derived by applying the integral method. The expression of the pressure is analysed to investigate the pressure distribution. The oil film force of the analytical model is compared with the results from other methods, namely, long bearing approximation, short bearing approximation, as well as the finite difference method. The results clearly validate the current model. The proposed model also proved to be efficient for analysing the dynamic characteristics of a rigid rotor supported by plain journal bearings.
Extension of a finite version of the sampling theorem

The present paper approaches a multichannel sampling scheme, and provides a generalized sampling expansion for two-dimensional, bandlimited, not necessarily orthogonally periodic signals. It is shown that the signal can be reconstructed from a number of sampling points equal to the number of its harmonic components. The sampling density can be decreased in the multichannel approach with respect to the one-channel approach. One- and two-dimensional special cases are considered. >
Thermohaline staircase formation in the diffusive convection regime: a theory based upon stratified turbulence asymptotics

Abstract We describe a mechanism that leads to the spontaneous formation of a thermohaline staircase in the high-latitude oceans. Our analysis of this mechanism is based upon a model in which uniform gradients of temperature and salinity are assumed and is applied to a simplified mean-field model of stratified turbulence. Detailed analysis employs a parametrization of turbulent diapycnal diffusivities (Bouffard & Boegman, Dyn. Atmos. Oceans, vol. 61, 2013, pp. 14–34). This parametrization is apparently unique in that it distinguishes between the diapycnal diffusivities for heat and salt on the basis of their Prandtl (Schmidt) numbers. Our model predicts that the temperature and salinity profiles will be susceptible to linear instability if the buoyancy Reynolds number lies in the range 0.18–91, and a nonlinear mean-field model simulation demonstrates that it evolves into a well-defined thermohaline staircase that matches the characteristics of those found in the high-latitude oceans. The criterion for initial instability is furthermore shown to be consistent with the observed regional variability of staircase occurrence in the Arctic Ocean as determined by the most recent observational datasets.
Invited: Advances in Active and Adaptive Chemical Sensing

In this presentation, we will review advances at the chemical sensor and data processing levels that may enable the development of adaptive sensors. We will briefly discuss techniques at the sensor and system levels, including modulation of internal parameters (e.g., operating temperatures and absorption wavelengths) and external parameters (e.g., exposure times, preconcentration temperatures). At the signal processing level, we will overview adaptive filtering strategies that may be used to cancel interferences (e.g., environmental variables, drift), adaptive classification techniques for incremental learning in dynamic environments, and active sensing methods for on-line optimization of sensor arrays and individual tunable sensors. We will also present a methodology based on probabilistic graphical models that may be used to model the dynamic response of metal-oxide sensors under temperature modulation and select suitable temperature sequences on-the-fly, as the sensor interacts with its environment.
Apathy in Parkinson’s Disease: A Retrospective Study of Its Prevalence and Relationship With Mood, Anxiety, and Cognitive Function

Apathy is thought to be an important clinical feature of Parkinson’s disease (PD). However, its prevalence ranges greatly across studies because of differing definitions, assessment tools, and patient inclusion criteria. Furthermore, it remains unclear how the presentation of apathy in PD is related to mood disorder and/or cognitive impairment. This study sought to examine the prevalence of a pure apathy syndrome in PD, distinct from both depression and anxiety, and reveal its associated cognitive profile. A retrospective study was performed on 177 PD patients who had completed measures of apathy [Apathy Evaluation Scale (AES)] and mood functioning [Hospital Anxiety and Depression Scale (HADS)] and had undergone extensive neuropsychological assessment, using measures of intellectual functioning, memory, executive function, attention, language, visual processing, and cognitive speed; 14.7% of the sample indicated clinically significant levels of apathy, but this nearly always co-presented with depression and/or anxiety, with cases of “pure” apathy very rare (2.8%). On extensive cognitive assessment, patients with mood disorder performed worse on a measure of non-verbal intellectual functioning, but patients with additional apathy or apathy only demonstrated no further losses. The syndrome of apathy in PD greatly overlaps with that of depression and anxiety, suggesting that apathy in PD may be in large an epiphenomenon of mood disorder, with no specific neuropsychological features.
The Saliency of Snake Scales and Leopard Rosettes to Infants: Its Relevance to Graphical Patterns Portrayed in Prehistoric Art

Geometrically arranged spots and crosshatched incised lines are frequently portrayed in prehistoric cave and mobiliary art. Two experiments examined the saliency of snake scales and leopard rosettes to infants that are perceptually analogous to these patterns. Experiment 1 examined the investigative behavior of 23 infants at three daycare facilities. Four plastic jars (15×14.5cm) with snake scales, leopard rosettes, geometric plaid, and plain patterns printed on yellowish-orange paper inside were placed individually on the floor on separate days during playtime. Fourteen 7–15-month-old infants approached each jar hesitantly and poked it before handling it for five times, the criterion selected for statistical analyses of poking frequency. The jars with snake scales and leopard rosettes yielded reliably higher poking frequencies than the geometric plaid and plain jars. The second experiment examined the gaze and grasping behavior of 15 infants (spanning 5months of age) seated on the laps of their mothers in front of a table. For paired comparisons, the experimenter pushed two of four upright plastic cylinders (13.5×5.5cm) with virtually the same colored patterns simultaneously toward each infant for 6s. Video recordings indicated that infants gazed significantly longer at the cylinders with snake scales and leopard rosettes than the geometric plaid and plain cylinders prior to grasping them. Logistic regression of gaze duration predicting cylinder choice for grasping indicated that seven of 24 paired comparisons were not significant, all of which involved choices of cylinders with snake scales and leopard rosettes that diverted attention before reaching. Evidence that these biological patterns are salient to infants during an early period of brain development might characterize the integration of subcortical and neocortical visual processes known to be involved in snake recognition. In older individuals, memorable encounters with snakes and leopards coupled with the saliency of snake scales and leopard rosettes possibly biased artistic renditions of similar patterns during prehistoric times.