Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameter identification of the fuzzy clusters membership grade functions

Takagi-Sugeno models are an important class of fuzzy rule base oriented models, generally used for prediction and control. Takagi-Sugeno models are data models based on their automatic identification. Fuzzy clustering is one of the effective methods for identification. This paper presents a new method for obtaining the fuzzy sets of input variables using results of fuzzy clustering procedure. The fuzzy set measure of fuzziness is used for determination of the fuzzy set approximation parameters. Results of numerical example are presented to demonstrate the effectiveness of the new proposed method.
Parallel adaptive radiations in arid and temperate Australia: molecular phylogeography and systematics of the Egernia whitii (Lacertilia: Scincidae) species group

It has been an enduring belief that increasing aridity combined with Pliocene-Pleistocene glacial cycles resulted in the formation of distinct arid zone and temperate zone faunas within Australia. We assembled a molecular phylogeny for the Egernia whitii species group, an endemic group of skinks that comprises representatives from arid and temperate Australia, in order to test several biogeographical hypotheses regarding the origin of the Australian arid zone fauna. Sequence data were obtained from ten of the 11 species within the species group, plus three other Egernia species and an outgroup (Eulamprus heatwolei). We targeted portions of the ND4 (696 base pairs) and 16S rRNA (500 bp) mitochondrial genes and the b-Fibrinogen 7th Intron nuclear gene (648 bp). The edited alignment comprised 1844 characters, of which 551 (30%) were variable and 382 (69%) were parsimony informative. We analysed the data using maximum likelihood and Bayesian techniques and produced a single optimal tree. Our phylogeny strongly supports two major clades within the species group, corresponding to temperate-adapted rock-dwelling species and arid-adapted obligate burrowing species. However, the phylogenetic affinities of E. pulchra were not resolved. Our topology indicates that the New South Wales population of E. margaretae is actually E. whitii and reveals that E. margaretae margaretae and E. m. personata are distinct species. There also appears to be a major phylogeographical break within E. whitii occurring in eastern Victoria. Although our data supported several previously proposed phylogenetic relationships, Shimodaira‐Hasegawa tests soundly rejected several suggested affinities between certain species. The arid zone members of the E. whitii species group had been suggested to have originated as a result of multiple periods of colonization during the Pleistocene glaciation cycles. However, our genetic data suggest a single origin (presumably from a semiarid E. multiscutata-like ancestor) for the arid zone members of the group prior to the Plio-Pleistocene, probably during the late Miocene to early Pliocene. Our topology displays substantial sequence divergence between species with short internodes and long terminal branches, indicating rapid adaptive radiations within the arid and temperate zones. The presence of temperate-adapted species within more mesic refugia of the arid zone suggests that the necessary adaptations to aridity for colonizing the dry interior of the continent have not evolved since the initial period of adaptive radiation, despite the long evolutionary history of the species group. © 2004 The Linnean Society of London, Biological Journal of the Linnean Society, 2004, 83, 157‐173. ADDITIONAL KEYWORDS: 16S rRNA ‐ b-fibrinogen ‐ biogeography ‐ mtDNA ‐ ND4 ‐ nuclear gene ‐ phylogeny ‐ skink ‐ taxonomy.
Completion of Collision Avoidance Control Algorithm for Multicopters Based on Geometrical Constraints

The collision avoidance problem for multicopters is solved based on the combination of geometrical constraints and kinematics equation through this paper. The method is proposed for solving the vehicle flight from the start position to a destination point with collision avoidance in both static and dynamic environment. First, a collision zone is determined by tangential lines from a current position of the multicopter to the boundary spheres of obstacles. A collision detection angle is computed based on geometrical constraints between the multicopter and the obstacles to determine the shortest avoidance path. Afterward, a guidance law is obtained from the Lyapunov stability to control the heading angle of the vehicle for collision avoidance. In addition, a method to approach a given position after the completion of collision avoidance is also presented in this paper. The proposed method is applied in the outer loop of position and heading control to generate the set point of velocity and heading angular rate. A numerical simulation in different scenarios was performed to prove the effectiveness of the proposed algorithm.
Block backtracking-based matching pursuit for arbitrary block sparse signal recovery

Compressed sensing can exactly reconstruct sparse or compressible signals. In practice, many sparse signals have block sparse structures. To recover block sparse signals, a block backtracking-based matching pursuit algorithm is proposed, which chooses possible correct atoms by using a block processing and deletes unreliable atoms by a backtracking mechanism. The proposed algorithm doesn't require the prior knowledge about the sparse structure of signal. Experiments demonstrate that the proposed algorithm outperforms some other greedy recovery methods.
Stability Analysis of Systems With Delay-Dependent Coefficients: An Overview

This paper gives an overview of the stability analysis of systems with delay-dependent coefficients. Such systems are frequently encountered in various scientific and engineering applications. Most such analyses are generalization of those on systems with delay-independent coefficients. Therefore an introduction on systems with delay-independent coefficients is also given, with an emphasis on the $\tau $ -decomposition approach. Methods for two key ingredients of this approach are discussed, namely the identification of imaginary characteristic roots with the corresponding delays, and local behavior analysis of these roots as the delay increases through these critical values. For systems with delay-dependent coefficients, we review the methods of analysis for systems with a single delay and commensurate delays, their application to output feedback control and a geometric perspective that establishes a link between systems with and without delay-dependent coefficients. We provide the main ideas of various stability analysis methods and their advantages and limitations. We also present our perspectives on future directions of research on this interesting topic.
An Examination of the Home-Intruder Sex Offender

One particular crime location in sexual assaults is the victim’s residence. Similar to sexual burglars, “home-intruder” sex offenders choose to assault the victim in her residence, most likely in their bedroom. The aim of the current study is to analyze modus operandi, temporal factors, and victim characteristics in a sample of 347 stranger sexual assaults committed by 69 serial sex offenders to determine which factors may be more relevant to sexual assaults committed in the victim’s residence compared with sexual assaults committed at another type of location. Our hypothesis is that offenders who choose to sexually assault victims in their home constitute a specific type of sex offender, one that resembles the sexual burglar. Results showed that modus operandi (e.g., burglary), temporal factors (e.g., time at crime scene with victim), and victim characteristics (e.g., age, victim-offender relationship) were significant in predicting whether the victim encounter, crime site, and victim release site were located at the victim’s residence or not. Moreover, these findings were generally significant across the three crime locations, which can be explained by the high consistency in location during home-intrusion sexual assaults. Situational crime prevention strategies aimed at making a residence less attractive for offenders should help reducing this particular type of sexual assault.
A reactive approach to classifier systems

The navigation problem involves how to reach a goal avoiding obstacles in dynamic environments. This problem can be faced considering reactions and/or sequences of actions. Classifier Systems (CS) have proven their ability of continuous learning, however they have some problems in reactive systems. A modified CS is proposed to overcome these problems. Two special mechanisms are included in the developed CS to allow the learning of both reactions and sequences of actions. This learning process involves two main tasks: first, discriminating between rules and second, the discovery of new rules to obtain a successful operation in dynamic environments. Different experiments have been carried out using a mini-robot Khepera to find a generalized solution. The results show the ability of the system for continuous learning and adaptation to new situations.
Distributed multi-arm systems for complex pushing tasks

Distributed robot systems using autonomous manipulators are widely employed in complex tasks such as object pushing, handling, tumbling, or combinations of them. In such cases, the problem of arm reconfiguration is encountered if the object has to be moved into another orientation. In the paper, we describe an object-pushing robot system in which emphasis is placed on efficient planning on the changing of pushing positions, which we call arm repositioning. A new algorithm is proposed for the repositioning mainly based on an evaluation of the object stability and load distribution. The applicability of the algorithm is illustrated by results of experiments using simulated or real arm systems.
Zero covariation returns

Asset returns are modeled by locally bilateral gamma processes with zero covariations. Covariances are then observed to be consequences of randomness in variations. Support vector machine regressions on prices are employed to model the implied randomness. The contributions of support vector machine regressions are evaluated using reductions in the economic cost of exposure to prediction residuals. Both local and global mean reversion and momentum are represented by drift dependence on price levels. Optimal portfolios maximize conservative portfolio values calculated as distorted expectations of portfolio returns observed on simulated path spaces. They are also shown to outperform classical alternatives.
3D Visualization of Sentiment Measures and Sentiment Classification using Combined Classifier for Customer Product Reviews

The Internet has wide reachability making many users to buy the products online using e-commerce websites. Usually, users provide their opinions, comments, and reviews about the products in social media, e-commerce websites, blogs, etc. The product review comments provided by the customers have rich information about the usage of the products they bought and their sentiments towards those products. In this research, we have collected reviews from Amazon.com and performed sentiment analysis to collect sentiment information. We have proposed 3D visualizations to represent sentiment information, such as sentiment scores and statistics about words used in the reviews. The 3D visualizations are useful to represent large sentiment related information and to have an in-depth understanding of sentiments of users. We have developed a combined classifier using Logistic Regression, Decision Tree and Support Vector Machine. From the reviews, we formed N-gram features using a bag of words and performed sentiment classification using combined classifier. On 10 fold cross-validation, a maximum classification rate for combined classifier of 90.22% is obtained for sentiment classification.
Metrics for quantifying antibiotic use in the hospital setting: results from a systematic review and international multidisciplinary consensus procedure

Abstract Background Quantifying antibiotic use is an essential element of antibiotic stewardship since it allows comparison between different settings and time windows, and measurement of the impact of interventions. However, quantity metrics (QMs) and methods have not been standardized. Objectives To propose a set of QMs for antibiotic use in inpatients (IQMs) that are accepted globally by professionals in a range of disciplines. The study was conducted within the Driving Reinvestment in Research and Development and Responsible Antibiotic Use (DRIVE-AB) project. Methods A systematic literature review using MEDLINE identified articles on measuring inpatient antibiotic use, published up to 29 January 2015. A consensually selected list of national and international web sites was screened for additional IQMs. IQMs were classified according to the type of numerator used and presented to a multidisciplinary panel of stakeholders. A RAND-modified Delphi consensus procedure, which consisted of two online questionnaires and a face-to-face meeting, was performed. Results The systematic literature review and web site search identified 168 eligible articles from which an initial list of 20 IQMs, composed of 20 different numerators and associated denominators was developed. The consensus procedure resulted in a final set of 12 IQMs. Among this final set, DDDs per 100(0) patient-days and days of therapy per patient-days were most frequently found in the review. The panel recommended that antibiotic use should be expressed in at least two metrics simultaneously. Conclusions Our consensus procedure identified a set of IQMs that we propose as an evidence-based global standard.
Electrochemotherapy pre‐treatment in primary squamous vulvar cancer. Our preliminary experience

Previous studies showed a local tumor control of 80% in patients with relapsed squamous cell vulvar cancer (V‐SCC) treated with electrochemotherapy. These results encouraged electrochemotherapy use as neo‐adjuvant treatment in V‐SCC. The objective of this study was to evaluate the effectiveness of electrochemotherapy in reducing tumor burden in V‐SCC.
Coordination of back bending and leg movements for quadrupedal locomotion

—Many quadrupedal animals use lateral degrees of freedom in their backs to assist locomotion. This paper seeks to use a robotic model to demonstrate that back bending assists not only forward motion, but also lateral and turning motions. We present a simple planner that uses geometric mechanics to pre- scribe gaits that coordinate both leg movements and back bending motion. Using these geometric tools, we show that back-bending can improve stride displacement in the forward, rotational, and lateral directions. Interestingly, we observe that the animal’s (salamander, Salamandra salamandra ) back-bending is close to our calculated back-bending to improve forward displacement. In addition to locomotion performance improvement, back bending can also expand the target position space a robot can reach within one gait cycle. Our results are veriﬁed by conducting experiments with a robot moving on granular materials.
Real time video stabilization methods in IR domain for UAVs — A review

In applications that involve a camera attached to a moving platform, such as UAV, Car, Drones etc., mechanical vibrations of the moving platform cause undesired shaking motion in videos known as Video Jittering. This causes severe performance degradation in applications such as object detection and tracking for applications such as surveillance and remote sensing. Video stabilization is required as preprocessing step to remove undesired motion while preserving the desired ones. Video Stabilization is an active research area for past decade and most of work done is on offline methods for stabilizing video in visible range. However stabilizing Infrared videos and that too for real time applications is still an open research area. This is because of the difficulty in detecting and tracking good features in IR videos due to lower resolution/quality videos. In this paper various existing methods provided in literature are compared in detail to focus on method that is more feasible for real time IR stabilization implementation.
Generative Adversarial Networks for Realistic Synthesis of Hyperspectral Samples

This work addresses the scarcity of annotated hyperspectral data required to train deep neural networks. Especially, we investigate generative adversarial networks and their application to the synthesis of consistent labeled spectra. By training such networks on public datasets, we show that these models are not only able to capture the underlying distribution, but also to generate genuine-looking and physically plausible spectra. Moreover, we experimentally validate that the synthetic samples can be used as an effective data augmentation strategy. We validate our approach on several public hyperspectral datasets using a variety of deep classifiers.
Laser micro-machining of LPM compound material for panel and IC packaging

In this paper, the authors present a study of micromachining of LPM (low pressure mold) material by using ultrafast laser including cutting, drilling and trenching. LPM is a rubber like material and the processing speed is usually slow. We did some tuning of process parameters to improve the machining speed by the ultraviolet laser. The test results will be presented as the effective speed is improved from 0.8 mm/min to 2.99 mm/min; hole diameter: top 2.63 mm, bottom 2.57 mm; cutting wall side tilt ∼1 degree. A series of comprehensive parametric study has been conducted in this paper.
Development of head-attached interface device (HIDE) and its application experiments

Head-attached interface device (HIDE) has been developed as a new type of human interface device in an actual work environment. The HIDE has flexible integrated functions which consist of speech recognition and view direction detection as hand-free input channels, direct presentation of audio/visual information as output channels, and mobile system configuration. In this paper, the design concept of the HIDE was first introduced, and individual functions to configure the design concept were developed by their separate testing. An integrated prototype system HIDE was then produced, and its functional evaluation test was made to examine the individual functions. According to the evaluation result, we proposed a design guideline of application software, and developed an example software.
Crowdsourcing community heuristic evaluations

Crowdsourcing is growing in both industry and academia, providing new ways to conduct work. However, these online working environments show similarities with the industrial revolution, were workers have few to no rights. Although crowdsourcing is a new phenomenon, online communities have quite some history. We find a resource in the literature on how to build online communities and applied them to crowdsourcing platforms. We have gathered and adjusted community heuristics to evaluate crowdsourcing platforms. To support the evaluation task, we have developed a system which we present as a demo: http://tinyurl.com/ecscwdemo
Synthesis and antifungal activity of carvacrol and thymol esters with heteroaromatic carboxylic acids

Abstract Aiming to obtain the more effective pathogen inhibitive ingredients and explore the influence of introducing different heterocyclic units to carvacrol and thymol esters, twenty ester derivatives with different heterocyclic units were synthesized. And the in vitro antifungal activity of title compounds against five plant pathogenic fungi was evaluated by mycelium growth rate method. The results showed that some carvacrol and thymol esters showed good to excellent antifungal activity, and compound 9d (4-bromo-5-isopropyl-2-methylphenyl picolinate) exhibited a broad antifungal spectrum. Preliminary study indicated that the introduction of furan, thiophene and pyridine unit could enhance the antifungal activity of carvacrol and thymol esters against Botrytis cinerea and a bromine atom on the para position of benzene moiety could enhance their antifungal activity.
Diversity and interactions of begomoviruses and their associated DNA-satellites

To study the diversity of begomovirus/DNA-satellite complexes, plants of one crop species (okra; Abelmoschus esculentus) and one weed species (Ageratum conyzoides), both with leaf curling symptoms, were analyzed. Sequence analyses of complete genome components revealed a unique begomovirus/DNA-satellite complex in both plants. Okra was found to harbor infection with viruses of three begomovirus species, including the new recombinant species Okra leaf curl Cameroon virus, as well as one betasatellite and two divergent alphasatellites. The analysis of A. conyzoides revealed infection with a previously un-described complex of a begomovirus, betasatellite and alphasatellite. The results suggest that the diversity of begomoviruses and their associated DNA-satellites in Africa is much higher than previously thought, and that it may be similar to the diversity in Asia. Begomoviruses and satellites from different geographic regions, such as Africa and Asia, are genetically different. To test the compatibility of begomoviruses and satellites from Asia, Africa and the Mediterranean Region, inoculation experiments were carried out in the model host Nicotiana benthamiana using agroinfectious constructs for different begomoviruses and satellites. It was found that the tested begomoviruses and satellites could functionally interact with non-cognate betasatellites and alphasatellites with varying efficiencies. The results showed that the functional requirements for interaction between begomovirus and satellite can be quite relaxed. Thus, it is quite possible that new begomovirus-satellite combinations with components from different geographic regions will be formed, which may overcome plant resistance and increase the host range of begomoviruses. Functional studies were carried out on the betasatellite-associated monopartite begomovirus Cotton leaf curl Kokhran virus. Mutation analyses of the coat protein (CP), V2, C2 and C4 genes showed that CP, V2 and C2 are pathogenicity determinants and that they are involved in facilitating virus movement and maintenance of betasatellites. C4 is responsible for symptom induction, but it was not specifically required to maintain betasatellites.
High-Pass ΣΔ Converter Design Using a State-Space Approach and Its Application to Cardiac Signal Acquisition

Cardiac signal acquisition with high linearity and accuracy of the high-pass cut-off frequency imposes a challenge on the implementation of the analog preprocessing and the analog-todigital converter. This paper describes a state-space-based methodology for designing high-pass sigma-delta (HPΣΔ) topologies with high linearity, targeting high accuracy of the high-pass cut-off frequency. Intermediate functions are evaluated mathematically to compare the proposed HPΣΔ topologies with respect to dynamic range. A sensitivity performance analysis of the noise transfer function with respect to integrator nonidealities and coefficient variations is also described. Finally, to illustrate the design approach, an orthonormal HPΣΔ modulator is designed to be implemented in 0.18 μm CMOS technology, is tested with real prerecorded ECG signals.
Predicting Psychological Health from Childhood Essays. The UGent-IDLab CLPsych 2018 Shared Task System.

This paper describes the IDLab system submitted to Task A of the CLPsych 2018 shared task. The goal of this task is predicting psychological health of children based on language used in hand-written essays and socio-demographic control variables. Our entry uses word- and character-based features as well as lexicon-based features and features derived from the essays such as the quality of the language. We apply linear models, gradient boosting as well as neural-network based regressors (feed-forward, CNNs and RNNs) to predict scores. We then make ensembles of our best performing models using a weighted average.