Miracle-dz/UniFAR-FTUs huggingface dataset:
Grammatical error prediction

In this thesis, we investigate methods for automatic detection, and to some extent correction , of grammatical errors. The evaluation is based on manual error annotation in the Cambridge Learner Corpus ((((), and automatic or semi-automatic annotation of error corpora is one possible application, but the methods are also applicable in other settings, for instance to give learners feedback on their writing or in a proofreading tool used to prepare texts for publication. Apart from the , we use the British National Corpus (((() to get a better model of correct usage, WordNet for semantic relations, other machine-readable dictionaries for or-thography/morphology, and the Robust Accurate Statistical Parsing ((((() system to parse both the and the and thereby identify syntactic relations within the sentence. An ancillary outcome of this is a syntactically annotated version of the , which we have made publicly available. We present a tool called GenERRate, which can be used to introduce errors into a corpus of correct text, and evaluate to what extent the resulting synthetic error corpus can complement or replace a real error corpus. Different methods for detection and correction are investigated, including: sentence-level binary classification based on machine learning over n-grams of words, n-grams of part-of-speech tags and grammatical relations; automatic identification of features which are highly indicative of individual errors; and development of classifiers aimed more specifically at given error types, for instance concord errors based on syntactic structure and collocation errors based on co-occurrence statistics from the , using clustering to deal with data sparseness. We show that such techniques can detect, and sometimes even correct, at least certain error types as well as or better than human annotators. We finally present an annotation experiment in which a human annotator corrects and supplements the automatic annotation, which confirms the high detection/correction accuracy of our system and furthermore shows that such a hybrid setup gives higher-quality annotation with considerably less time and effort expended compared to fully manual annotation. Preface First of all, there are many people who deserve to be mentioned on this page, but whose names do not appear — from my parents, who hardly ever lost their patience when I bombarded them with questions as a child, to the visiting friend who presented me with the idea of a doctorate over dinner at a time when further studies did not seem an obvious choice —, and I should like to …
Autonomous aerial rendezvous of small unmanned aircraft systems using a towed cable system

Many unmanned aircraft systems (UAS) have relatively short endurance and range which limits their usefulness in applications where their home station is a long distance from the area of interest. This paper lays out a method for placing a towed drogue system into an appropriate orbit used by a seeker UAS to track and rendezvous with it. The principle contributions of the work include a method for controlling the drogue path by manipulating the mothership orbit and airspeed. Another contribution is a vision-based nonlinear tracking method that provides pitch rate and roll commands to allow the seeker UAS to rendezvous with the drogue. Flight test results are presented to demonstrate the suitability of these methods.
Reproducible Tract Profiles (RTP): from diffusion MRI acquisition to publication

Reproducible Tract Profiles (RTP) comprises a set of methods to manage and analyze diffusion weighted imaging (DWI) data for reproducible tractography. The tools take MRI data from the scanner and process them through a series of analysis implemented as Docker containers that are integrated into a modern neuroinformatics platform (Flywheel). The platform guarantees that the entire pipeline can be re-executed, using the same data and computational parameters. In this paper, we describe (1) a cloud based neuroinformatics platform, (2) a tool to programmatically access and control the platform from a client, and (3) the DWI analysis tools that are used to identify the positions of 22 tracts and their diffusion profiles. The combination of these three components defines a system that transforms raw data into reproducible tract profiles for publication. Graphical abstract Reproducible Tract Profiles (RTP) comprises a set of methods to manage and analyze diffusion weighted imaging (DWI) data for reproducible tractography. The RTP methods comprise two main parts. Server side software tools for storing data and metadata and managing containerized computations. Client side software tools that enable the researcher to read data and metadata and manage server-side computations. The server-side computational tools are embedded in containers that are linked to a JSON file with a complete specification of the computational parameters. The data and computational infrastructure on the server is fully reproducible.
Dynamical properties of neuronal systems with complex network structure

An important question in neuroscience is how the structure and dynamics of a neuronal network relate to each other. We approach this problem by modeling the spiking activity of large-scale neuronal networks that exhibit several complex network properties. Our main focus lies on the relevance of two particular attributes for the dynamics, namely structural heterogeneity and degree correlations. Although these are fundamental properties of many brain networks, their influence on the system’s activity is not yet well understood. As a central result, we introduce a novel mean-field method that makes it possible to calculate the average activity of heterogeneous, degree-correlated neuronal networks without having to simulate each neuron explicitly. The method is based on grouping neurons with equal number of inputs (their in-degree) into populations and describing the dynamics of these populations in terms of reduced firing rate equations. We find that the connectivity structure is sufficiently captured by a reduced matrix that contains only the coupling between the populations. This matrix can be calculated analytically for some generic random networks, which allows for an efficient analysis of the system’s dynamics. With the mean-field method and numerical simulations we demonstrate that assortative degree correlations enhance the network’s ability to sustain activity for low external excitation, thus making it more sensitive to small input signals. This effect is reminiscent of an increased structural robustness of assortative networks that is well-known in network sciences. Therefore, we additionally examine the structural robustness of correlated networks with a simplified percolation model, additionally taking into account the fact that neuronal networks among other real-world systems are subject to metric constraints: Spatially close neurons are usually more likely to connect to each other than distant neurons. The main result of this examination is that for weak metric constraints assortativity generally makes the network more robust, whereas for strong metric constraints assortativity can strengthen or weaken the network, depending on its local structure. Therefore, we conclude that degree correlations and metric constraints strongly interplay and that they should not be regarded as independent features of real-world networks.
Computational Analysis Of The Effect V241F KCNQ1 Mutation On Cardiac Ventricular Mechanical Responses: Simulation Method.

Abstract Several studies have found genetic mutations, which affect characteristics of specific ion channels and cause cardiac arrhythmia such as atrial and ventricular fibrillation [1]. Study about understanding the genetic predisposition, modeling cardiac tissue to apply on simulation study, and how genetic mutation influence the Atrial and Ventricular Fibrillation challenge the researcher to solve it. To construct a computational model of a cardiovascular system, we used 3D finite element model of a failing human ventricle, combined with a lumped model of the circulatory system [12]. In a 3D cardiac tissue CAD electromechanical model, we analyze the propagation wave in 2 conditions, normal sinus rhythm and reentry. During normal sinus pacing, the electrical stimulation applied from Purkinje fibers tissue. In our research, we investigate the effect of V241F mutation in canine ventricular in failure state using the computational method. This is the first study to implement a finite element of an image based on the electromechanical model for the heart, to investigate cardiac electrophysiology and mechanics for V241F mutation. The mutation V241F effected the mechanical behavior according to electrical as an input. In a single cell, V241F with pure mutation shortened the ventricular APD around 67% and 33% for intermediate variant mutation. Keywords: Finite Element Model (FEM), Mechanical simulation, Cardiovascular
AutoTeach: incremental hints for programming exercises

In recent years, e-learning platforms and MOOCs (Massive Open Online Courses) have gained great popularity, and the Computer Science area is not excluded from this trend. A challenge for MOOCs is providing effective exercises to the students, and this is even more important in applied disciplines such as programming. A major difficulty of this challenge is ensuring that students do not get stuck in solving the exercises, which eventually leads to giving up. This is one of the most significant drawbacks of MOOCs over more traditional forms of teaching, where teachers can provide direct guidance to students who lack the necessary idea for solving an exercise. We designed AutoTeach, an incremental hint system for programming exercises. Given a complete solution of a programming exercise, AutoTeach can generate several stripped out versions of it, numbered by hint level, which initially only contain the skeleton of the solution’s code, and then, for higher hint levels, gradually reveal more parts of the code and/or hints on how to write it. Students who get stuck on an exercise can ask for a hint (one or multiple times) and receive versions of the code where more and more parts of the solution are revealed, until they are able to proceed on their own. This way we ensure that students who happen to lack the necessary idea for solving an exercise can receive the help they need, instead of immediately giving up.
Trade off study on different envelope detectors for B-mode imaging

Generation of B-mode images involves envelope detection of the RF signals. Various detection algorithms are available. A trade of between performance, price, and complexity determines the choice of algorithm in an ultrasound system. A Hilbert transform (HT) and a subsequent computation of the magnitude give the ideal envelope, but the approach (IDE) is expensive and complex. A rectifier (REC) is a simple, low-cost solution, but the performance is severely degraded (especially in dynamic imaging). This study has investigated the possibility of providing a detector with a complexity and cost close to REC, while maintaining performance close to IDE. Two low-cost detectors have been implemented and evaluated on in-vivo data. The first approach is an expansion of the rectifier with a median filter (ERM). The second detector (TAS) approximates the HT by a time delay and the magnitude by a weighted sum of the real and imaginary signals. The four detectors were evaluated on in-vivo data acquired with a B-K Medical 2102 scanner interfaced to the sampling system RASMINE. Three data sets were acquired with three different center frequencies. Hundred images were acquired as the transducer was moved across the liver and the carotid artery of a 30 years old healthy male. The root-mean-square (RMS) error relative to the IDE, and a visual inspection determine the performance. For the 3.5 MHz data sets RMSE's of 15.7%, 1.6%, and 1.9% are obtained with REC, ERM, and TAS, respectively. The performance is similar to the two other data sets. Close to envelope detection is therefore obtainable with a simple detector (ERM or TAS), which is less complex and costly.
An application of online learning algorithm for Bayesian network parameter

Bayesian network is a graphical model that encodes probabilistic relationships among nodes of interest. The automated creation of Bayesian networks can be separated into two tasks. Structure learning, which consists of creating the structure of the Bayesian networks from the collected data and parameter learning, which consists of calculating the numerical parameters for a given structure. A Voting EM algorithm which is based EM be discussed and applied in the online parameter learning in flood decision Bayesian networks in this paper. Both EM and Voting EM algorithm are applied in flood decision Bayesian networks to compared their performance. The result indicates that the Voting EM can be used in the online learning for Bayesian network parameter and it also has more precisely that general EM algorithm.
Antiviral Effect of Phyllanthus amarus Leaf Extract against Newcastle Disease Virus in Broilers

Background and Objective: Newcastle disease (ND) is a viral disease of economic importance in poultry industry worldwide. This study was conducted to investigate the antiviral potential of n-hexane leaf extract from Phyllanthus amarus (P. amarus). Methodology: A hundred and twenty day old broiler chickens were purchased and raised for the experiment. At four weeks, the birds were randomly assigned into 12 groups of 10 birds each. Chickens in groups 1, 2, 3, and 4 were vaccinated while those in 5, 6, 7, and 8 were left unvaccinated. Groups 9 and 10 served as the positive controls while 11 and 12 as the negative controls. All groups except the negative control were infected. To study the prophylactic effect of the extract, chickens in groups 1 and 5 received 250 mg/l while those in groups 2 and 6 received 500 mg/l of leaf extract for fourteen days before experimental infection. The chickens in groups 3 and 7 received 250 mg/l while those in groups 4 and 8 received 500 mg/l of leaf extract for fourteen days after infection with ND virus to assess the therapeutic effect of the extract. Clinical signs, bodyweight changes and mortality rates were documented. Antibody titers against the virus were determined and postmortem examination was conducted. Results: Results revealed reduction in mortality rates following administration of the n-hexane extract after the challenge. Prophylactic administration of the extract was more effective in reducing the mortality rates of birds due to the virus infection compared to the therapeutic administration. Similarly, antibody titers decreased in a dosage dependent pattern in the prophylactic group. Conclusion: These findings indicate that the n-hexane leaf extract from P. amarus has significant antiviral potentials against ND virus in broiler chickens and that prophylactic administration at 500 mg/l might be a safer approach in utilization of the leaf extract against Newcastle disease.
Discourse binding: DP and pronouns in German, Dutch, and English

Grammatical determiners of various sorts are differently distributed in individual languages. We will list and investigate briefl y a few related and non-related languages to survey the lexical lexemes relating to Determiner (DemPro) status vs. Article status and pronominal anaphor (PersPro). A synchronic line of discussion will be pursued. It will be crucial to see synchronically, fi rst, to which extent such determiners co-defi ne anaphors in contexts reaching beyond the single clause. Second, it will be investigated typologically what the determiner-determined features are where they are in interaction with aspect and morphological case. Third, and interlinking the synchronic and the diachronic chapters, since spoken-only codes use anaphoric determiners in ways strikingly different from their written(-only) standard varieties, processing differences will be made responsible for such a variation.
The anger in municipal bus drivers and its relationship with sociodemographic characteristics

Amac: Bu calisma belediye otobus soforlerinin sosyo demografik ozellikleriyle ofke duzeyi ile ofke ifade tarzlari arasindaki iliskinin incelenmesi amaciyla yapilmistir. Gerec ve Yontem: Calisma 95 otobus soforu ile yurutulmustur. Veriler anket formu ve Surekli ofke- ofke ifade tarzi olcegi ile toplanmistir. Bulgular: Puan ortalamalari; surekli ofke 16,67±4,29, ofke ice 15,05±3,31, ofke kontrol 25,12±4,97, ofke disa 12,48±2,94 olarak bulunmustur. Meslekte calisma yili ile surekli ofke, ofkeyi ifade etmekte zorlanma ile ofke kontrol ve ofke disa arasinda istatistiksel olarak anlamli bir iliski vardir. Bir diger iliski isteki sorunlar nedeniyle aile yasaminda ofkeli olma ile surekli ofke, ofke kontrol, ofke disa arasindadir. Ofke kontrolu egitimi alma ile ofke disa arasinda da anlamli bir iliski vardir. Sigara icme suresi (yil) ile ofke kontrol, kurumda calisma yili ile ofke disa arasinda pozitif anlamli bir iliski vardir. Diger calismalarla tutarli olarak bu calisma da mesleki deneyimin artmasinin ofke duzeyini azalttigini, kurumda calisma yili arttikca ofkenin daha kolay ifade edilebildigini gostermistir. Bu calismada isteki sorunlarin aile yasamina ofke olarak yansimasi incelenen farkli bir konudur. Sonuc: Calismanin bulgulari soforlerin ofke duzeyini ve ofke ifadesini etkileyen sosyodemografik ozelliklere dair kanitlar sunmaktadir. Arastirma sonuclari ofkeyi dogru ifade edebilme ve ofke kontrolu konusunda otobus soforlerine yonelik mudahaleler planlarken dikkate alinabilir.
Software Defined Networking (SDN) Network Virtualization for the IS Curriculum

Network technologies, enterprise architectures, and cloud architectures are recommended topics in the IS curriculum. Over 70% of today's servers are virtual machines. Cloud computing is the ultimate "system" to teach in an information system curriculum. The TCP/IP and OSI network models were adequate to serve industry and the IS curriculum in an age when static, client-server architectures were dominant. Current network models and technologies used to manage large-scale, complex networks, integrate cloud architecture resources and multi-tenant applications (Open Networking Foundation, 2014a), provide no user program control or customized automation services, are vendorspecific, and fail to address the complexity of different traffic classes mix, mobile devices, BYOD, individual users or applications. This paper provides a) an overview of limitations of current network models and technologies b) an overview of new enterprise network and cloud network standards introduced in 2012, such as, Software-Defined Networking (SDN), and OpenFlow, and OpenStack, and c) considers the inclusion of these new open standards in the IS network curriculum.
The role of platelet microparticles in the production of antibodies from B lymphocytes against HLA-DR antigen in vitro

Background: Platelets can activate B cells and stimulate them for the production of antibodies. Since platelet microparticles (PMPs) originate from platelets, they may have the same virtue. In the present study, the effect of PMPs was investigated on the production of human leukocyte antigen (HLA)-specific antibody from B cells in vitro. Materials and Methods: In this experimental study, HLA-DR antigen was solubilized from the immortalized B lymphocytes (Daudi cell line) and purified using the affinity chromatography. Antigen properties were determined by the ELISA technique. PMPs were isolated from platelet concentrate bags by centrifugation. Fresh blood products were prepared from the Innovation Center of Iranian Blood Transfusion Organization (IBTO) and B lymphocytes were purified by the MACS method. B cells were exposed with PMPs and HLA-DR antigens in the culture medium. On the third day of culture, the culture supernatant was examined in terms of antibody production using the ELISA test. The results were analyzed using paired sample T-test and P-value <0.05 was considered statistically significant. Results: The specificity of the purified HLA-DR antigen was confirmed using the anti-HLA-DR antibody and ELISA technique in the presence of appropriate controls. The results showed that PMPs could stimulate the production of antibodies from B cells. The difference between the case and control was significant (P-value=0.001). Although total immunoglobulin (IgG) was higher in HLA-DR-treated wells, HLA-DR-specific antibodies were not identified by ELISA technique. Conclusion: PMPs have the capability to induce IgG antibodies from B cells. In order to ensure the production of specific antibodies, further testing is required with high sensitivity.
Robust scheduling in MIMO-OFDM multi-user systems based on convex optimization

This paper proposes a new technique in the context of multi-user scheduling in orthogonal frequency division multiplexing (OFDM) and multi-input-multi-output (MIMO) systems by considering a design that is also robust to channel uncertainties. The whole technique is divided into two parts: i) a robust design for each particular MIMO link exploiting an imperfect channel state information (CSI) and ii) a multi-user design for the scheduling policy. The link between both stages is practical, intuitive, and simple. The robust MIMO design is based on a worst-case approach that maximizes via convex optimization procedures the worst possible signal to noise ratio (SNR) given a specified channel uncertainty region. The scheduling policy, also calculated with convex optimization techniques, minimizes the total number of utilized subcarriers. Therefore, the design is scalable in the sense of having the capability to incorporate new future potential users.