Miracle-dz/UniFAR-FTUs huggingface dataset:
INFLUÊNCIA DO NÚMERO E DISTRIBUIÇÃO DE PONTOS DE CONTROLE EM ORTOFOTOS GERADAS A PARTIR DE UM LEVANTAMENTO POR VANT

Os VANTs têm sido amplamente utilizados para vários domínios, que vão desde aplicações militares a civis. Para elaboração de Cartograï¬a e análise de fenômenos (como desastres ambientais, monitoramento ï¬‚orestal, monitoramento de áreas vulcânicas, monitoramento de obras, dentre outras aplicações), esta técnica apresenta-se como relevante dependendo da aplicação, pois os custos operacionais são baixos. Entretanto, devido estar em fase inicial, seu uso é realizado muitas vezes sem conhecimento sobre a qualidade posicional do mesmo. Para tanto, foi avaliada a acurácia posicional planimétrica de ortofotos geradas com diferentes quantidades e distribuição de pontos de controle para uma área da Universidade Federal de Viçosa, no município de Viçosa-MG. Utilizou-se como padrão de acurácia posicional deï¬nido pelo Decreto-lei nº 89.817, podendo ser complementado pela ET-CQDG (Especiï¬cação Técnica de Controle de Qualidade em Dados Geoespaciais), aplicando o método de feição linear do Buï¬€er Duplo. O resultado obtido para as ortofotos geradas a partir de 5, 10 e 15 pontos de controle distribuídos por toda a região, apresentaram classiï¬cação Classe B, Classe B e a Classe A na escala 1:1.000, respectivamente. Para ortofoto gerada com a utilização de 15 pontos de controle terrestre, com padrão de distribuição agrupado, obteve-se resultado Classe D na escala 1:1.000, apresentando tendência nas coordenadas.
An Electrically Steerable Parasitic Array Radiator in Package Based on Liquid Crystal

An electrically steerable parasitic array radiator in package based on liquid crystal (LC) is presented. It consists of one main and two parasitic inverted microstrip patch elements on an embedded LC layer with direct current bias. The antenna is designed to operate under the voltage mode at Ka-band. By varying the induced voltages on parasitic elements, the main beam can be steered to the desired direction. Measured results show that the pattern can be steered from –27° to +29° continuously in the H-plane at 28 GHz. The peak realized gain is 6.03 dBi with 1 dB variation within the steering range. The array achieves an 8.3% impedance bandwidth and avoids both large direct current power consumption and complicated bias scheme, making it a good antenna candidate for millimeter-wave 5G access point applications.
DDLA: dual deep learning architecture for classification of plant species

Plant species recognition is performed using a dual deep learning architecture (DDLA) approach. DDLA consists of MobileNet and DenseNet-121 architectures. The feature vectors obtained from individual architectures are concatenated to form a final feature vector. The extracted features are then classified using machine learning (ML) classifiers such as linear discriminant analysis, multinomial logistic regression (LR), Naive Bayes, classification and regression tree, k -nearest neighbour, random forest classifier, bagging classifier and multi-layer perceptron. The dataset considered in the studies is standard (Flavia, Folio, and Swedish Leaf) and custom collected (Leaf-12) dataset. The MobileNet and DenseNet-121 architectures are also used as a feature extractor and a classifier. It is observed that the DDLA architecture with LR classifier produced the highest accuracies of 98.71, 96.38, 99.41, and 99.39% for Flavia, Folio, Swedish leaf, and Leaf-12 datasets. The observed accuracy for DDLA + LR is higher compared with other approaches (DDLA + ML classifiers, MobileNet + ML classifiers, DenseNet-121 + ML classifiers, MobileNet + fully connected layer (FCL), DenseNet-121 + FCL). It is also observed that the DDLA architecture with LR classifier achieves higher accuracy in comparable computation time with other approaches.
Machine Learning-Based Handovers for Sub-6 GHz and mmWave Integrated Vehicular Networks

The integration of sub-6 GHz and millimeter wave (mmWave) bands has a great potential to enable both reliable coverage and high data rate in future vehicular networks. Nevertheless, during mmWave vehicle-to-infrastructure (V2I) handovers, the coverage blindness of directional beams makes it a significant challenge to discover target mmWave remote radio units (mmW-RRUs) whose active beams may radiate somewhere that the handover vehicles are not in. Besides, fast and soft handovers are also urgently needed in vehicular networks. Based on these observations, to solve the target discovery problem, we utilize channel state information (CSI) of sub-6 GHz bands and Kernel-based machine learning (ML) algorithms to predict vehicles’ positions and then use them to pre-activate target mmW-RRUs. Considering that the regular movement of vehicles on almost linearly paved roads with finite corner turns will generate some regularity in handovers, to accelerate handovers, we propose to use historical handover data and $K$ -nearest neighbor (KNN) ML algorithms to predict handover decisions without involving time-consuming target selection and beam training processes. To achieve soft handovers, we propose to employ vehicle-to-vehicle (V2V) connections to forward data for V2I links. The theoretical and simulation results are provided to validate the feasibility of the proposed schemes.
Prediction of Changes in the Potential Distribution of a Waterfront Alien Plant, Paspalum distichum var. indutum, under Climate Change in the Korean Peninsula

기후변화에 따른 침입외래식물의 잠재적 분포지를 예측하는 것은 하천과 저수지에서 생물다양성 보전과 생태적 관리를 위하여 중요하고 해결해야 할 과제이다. 본 연구에서는 한반도에서 털물참새피 (Paspalum distichum var. indutum)의 잠재적 미래 분포에 미치는 기후변화의 영향을 파악하였다. 털물참새피는 담수생태계.
Strangeness and hadronic resonance production in pp, p-Pb and Pb-Pb collisions measured by ALICE at the LHC

The measurement of strangeness production is one of the powerful tools to study the thermal properties of the QGP and while strangeness enhancement is a well established experimental observation in heavy ion collisions, its interpretation is still debated. In particular the study of (multi-)strangeness particle production as a function of the event multiplicity in different collision systems, reported by ALICE, has shown a smooth increase of strange particle yields with respect to yields of non-strange particles. In this proceedings, we present the latest results on multiplicity-dependent strangeness production in different colliding systems at LHC energies. Furthermore, recent measurements of mesonic and baryonic resonances will be presented to investigate how hadronic scattering processes affect measured resonance yields. The experimental results obtained in pp, p--Pb and Pb--Pb collisions will also be compared with the theoretical predictions.
lfda: Local Fisher Discriminant Analysis in R

Fisher discriminant analysis (Scholkopft & Mullert, 1999) is a popular choice to reduce the dimensionality of the original dataset. It maximizes between-class scatter and minimizes within-class scatter. It works really well in practice but lacks some considerations for multimodality. Multimodality exists within many applications, such as disease diagnosis, where there may be multiple causes for a particular disease. In this situation, Fisher discriminant analysis cannot capture the multimodal characteristics of the clusters. To deal with multimodality, local-preserving projection (Niyogi, 2004) preserves the local structure of the data in that it keeps nearby data pairs in the original data space close in the embedding space. As a result, multimodal data could be embedded and its local structure will not be lost.
Finite time synchronization of stochastic Markovian jumping genetic oscillator networks with time-varying delay and Lévy noise

*Correspondence: ymkang@xjtu.edu. cn 1School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, P.R. China Abstract This paper is to investigate the finite-time synchronization of stochastic Markovian jumping genetic oscillator networks with time-varying delay and Lévy noise. At first, we generalize the finite-time stability theorem from the systems driven by Brownian motion to the Markovian jumping systems with Lévy noise. And then, we utilize the stochastic Lyapunov functional method and appropriate control to obtain sufficient conditions for finite-time synchronization. Finally, two numerical examples are presented to verify the effectiveness of the proposed criteria.
Stable algorithms for generalized thermoelasticity based on operator-splitting and time-discontinuous Galerkin finite element methods

This thesis deals with the theoretical and numerical analysis of coupled problems in thermoelasticity. Of particular interest are models that support propagation of thermal energy as waves, rather than the usual mechanism by diffusion. The thesis consists of two parts. The first deals with the non-classical, linear thermoelastic model first proposed and developed by Green and Naghdi in the years between 1991 and 1995, as a possible alternative that potentially removes the shortcomings of the standard Fourier based model. The non-classical theory incorporates three models: the classical model based on Fourier’s law of heat conduction, resulting in a hyperbolic–parabolic coupled system; a non-classical theory of a fully-hyperbolic extension; and a combination of the two. An efficient staggered time-stepping algorithm is proposed based on operator-splitting and the time–discontinuous Galerkin finite element method for the non-classical, linear thermoelastic model. The coupled problem is split into two contractive sub-problems, namely, the mechanical phase and thermal phase, on the basis of an entropy controlling mechanism. In the mechanical phase temperature is allowed to vary so as to ensure the entropy remains constant, while the thermal phase is a purely non-classical heat conduction problem in a fixed configuration. Each sub-problem is discretized using the time–discontinuous Galerkin finite element method, resulting in stable time-stepping sub-algorithms. A global stable algorithm is obtained by combining the algorithms for the sub-problems by way of a product method. A number of numerical examples are presented to demonstrate the performance and capability of the method. The second part of this work concerns the formulation of a thermodynamically consistent generalized model of nonlinear thermoelasticity, whose linearization about a natural reference configuration includes the theory of Green and Naghdi. The generalized
Actuator Control based on Interconnected Heterogeneous Networks

Recently, the use of electronic control units in vehicle has increased. The ECUs are connected to in-vehicle networks to process a large amount of information. In this paper, for an actuator that is interconnected to CAN and FlexRay, a FlexRay-CAN gateway is presented and a data packing algorithm with a bisection method of a FlexRay slot is proposed. And, a network based actuator control system and packing map is implemented. With the proposed packing method, contact force sensor data are transferred within the maximum allowed delay to ensure the stability. The proposed method is useful for control of distributed system.
Using NLP and context for improved search result in specialized search engines

This thesis investigates the performance of a search engine that uses NLP methods in order to find out if the use of triplets could improve search results when compared to a traditional search engine. In order to evaluate the proposed method a simple search engine was implemented in PHP. The indexing process included parsing a collection of selected documents with the Stanford CoreNLP parser to be able to extract potential triplets that were stored in an inverted index. Searching and ranking was done by using tf-idf to get a list of documents relevant to a search query. The results of this thesis showed that integrating NLP in a search engine has the potential of increasing the focus of a search and to more accurately identify the context of documents. This conclusion is based on the search results that were generally more focused toward a specific context compared to the traditional method, which provided a mixed distribution of documents. Even if the engine performed well the NLP methods used in the indexing process decreased the size of the index, which also affected the search process. Search terms had to be very specific and short in order to yield any results, which made the performance inconsistent compared to the traditional engine. By analysing the implementation along with the results, a solution to the indexing problem would be to integrate the extracted triplets during the ranking process as an additional weighting method. This would result in a fully extensive index and the ability to weigh a document based on both term frequency and the semantical importance of a term.
Review based Feature Matrix for Predicting ratings in Recommender System

—Recommender systems are acquiring extensive popularity and have become essential component of on-line business handling tools because of their capability of providing personalized guidance in selecting products and services. Collaborative Filtering that brings in the popularity aspect of the item amongst the user base, heavily depends on the ratings provided by the users, while Content - based Filtering that brings out the item's features matching the user's taste, requires content information as also user’s preference information. Service providers usually invite users to share their experience about the use of service in the form of reviews and ratings. Reviews which are verbose contain a rich source of information about the service's features as also user's preferences while ratings are usually sparse due to user’s reluctance to quantify. A feature matrix generated by processing review information using semantic similarity based on synsets can be used along with sparse ratings to generate the complete predicted ratings matrix. The paper presents a modified matrix factorization approach for recommendations using the review based feature matrix
Finger Detection Algorithm For Computer Mouse Control

We propose a finger detection algorithm for computer mouse control to control the most commonly actions of a computer mouse(left, right and double click, scroll up and down then we add open and close, minimize and maximize a window, control the mouse.) We use a built-in web camera to control the mouse tasks. We detected, segment, then recognize the hand in our previous papers [1, 2]. The user will be able to interact with the computer with the number of fingers detected.
Plasma Micro-Cavity of Terahertz Wave During Laser Filamentation

In this work, we focused on the resonant cavity effect of the air plasma, formed during femtosecond laser filamentation, on the near- and far-field profiles of the generated terahertz (THz) radiation. Via the method of ray tracing, it has been demonstrated that both on-axis propagation and conical forward emission of THz wave could be qualitatively interpreted in case of considering the filament as a Fabry-Perot-like micro-cavity with radial step refractive index distribution in THz domain. Our theory might potentially solve the contradictions of different experimental observations on THz spatial profiles reported in publications, and renew the understanding of THz wave propagation inside the filament plasma column.
Novel Adaptive Histogram Trend Similarity Approach for Land Cover Change Detection by Using Bitemporal Very-High-Resolution Remote Sensing Images

Detecting land cover change through very-high-resolution (VHR) remote sensing images is helpful in supporting urban sustainable development, natural disaster evaluation, and environmental assessment. However, the intraclass spectral variance in VHR remote sensing images is usually larger than that of median-low remote sensing images. Furthermore, the bitemporal images are usually acquired under different atmospheric conditions, sun height, soil moisture, and other factors. Consequently, in practical applications, many pseudo changes are presented in the detected map. In this paper, an adaptive histogram trend (AHT) similarity approach is promoted to quantitatively measure the magnitude between the corresponding pixels in bitemporal images in terms of change semantic. In the proposed approach, to reduce the phenological effect on the bitemporal images of land cover change detection (LCCD), we first define the quantitative description of AHT. Second, the change magnitudes between pairwise pixels are quantitatively measured by an improved bin-to-bin (B2B) distance between the corresponding AHTs. Then, the change magnitudes between two entire bitemporal images are measured AHT-by-AHT. Finally, binary threshold methods, such as the Otsu method or the double-window flexible pace search (DFPS) method, are used to divide the change magnitude image into binary change detection maps and obtain the final change detection map. The performance of the AHT-based LCCD approach is verified by four pairs of VHR remote-sensing images that correspond to two types of real land cover change cases. The detected results based on the four pairs of bitemporal VHR images outperformed the compared state-of-the-art LCCD methods.
Cuestionar y problematizar la propia práctica: Investigación Acción Transformadora en los procesos de desarrollo profesional docente

espanolEl profesorado juega un rol fundamental en la construccion de nuevas alternativas para entender y mejorar los procesos de ensenanza y aprendizaje. Las reflexiones que hagan al respecto se tornan fundamentales para afrontar cambios en un sistema educativo altamente segregado, homogeneizador y desigual. En este sentido, el desarrollo profesional docente se abre como una herramienta de cambio en la medida que dichos espacios propicien el analisis y mejora de la propia practica docente, fomentando en los y las docentes una mirada critica, reflexiva y transformadora. Este trabajo propone articular los aportes de la Investigacion-Accion Transformadora (IAT), entendiendo como base la creencia en el potencial del docente para fomentar procesos sociales de construccion de aprendizajes en un contexto de diversidad y heterogeneidad. EnglishTeachers have a key role in building new ways to understand and improve the processes of teaching and learning. Reflections about it become essential to address changes in a highly segregated, homogenizing and unequal education system. In this sense, teacher professional development becomes a tool for change, insofar as such programs would encourage the analysis and improvement of teaching practice from a critical, reflective and transformational view. This paper intends to articulate the contributions of the Transformative Action Research (TAR) grounded on teachers' potential to generate changes in the education system, even beyond its own barriers, to promote social processes within the construction of learnings in a context of diversity and heterogeneity.
The people behind the papers – Maurício Rocha-Martins and Mariana Silveira

Retinal ganglion cells connect the retina to the brain, and their degeneration underlies glaucoma, which is the leading cause of irreversible blindness in humans and currently untreatable. Replacement of lost cells could be achieved by in vivo reprogramming of endogenous cells in the retina, a strategy explored by authors of a new paper in Development who focus on a transcription factor renowned for its reprogramming ability in other contexts. We caught up with first author Maurício Rocha-Martins and his former supervisor Mariana Silveira, Professor at the Federal University of Rio de Janeiro in Brazil, to find out more about the story.
Simplified updates on the pathophysiology and recent developments in the treatment of amblyopia: A review

Amblyopia is the most common cause of monocular visual impairment affecting 2-5% of the general population. Amblyopia is a developmental cortical disorder of the visual pathway essentially due to abnormal visual stimulus, reaching the binocular cortical cells, which may be multivariate. Ganglion cells are of two types: parvocellular (P cells) and magnocellular (M cells); they are the first step where the light energy is converted in to neural impulse. P cells are involved in fine visual acuity, fine stereopsis, and color vision and M cells are involved in gross stereopsis and movement recognition. Strabismus, refractive error, cataract, and ptosis, occurring during critical period are highly amblyogenic. The critical period extends from birth to 7--8 years. The earlier the clinically significant refractive error and strabismus are detected and treated, the greater the likelihood of preventing amblyopia. Treatment for amblyopia in children includes: optical correction of significant refractive errors, patching, pharmacological treatment, and alternative therapies which include: vision therapy, binocular therapy, and liquid crystal display eyeglasses are newer treatment modalities for amblyopia. Age of starting the treatment is not predictive of outcome, instituting treatment on detection and early detection plays a role in achieving better outcomes. This review aims to give a simplified update on amblyopia, which will be of use to a clinician, in understanding the pathophysiology of the complex condition. We also share the cortical aspects of amblyopia and give recent developments in the treatment of amblyopia.
Comparative Analysis of miRNA Abundance Revealed the Function of Vvi-miR828 in Fruit Coloring in Root Restriction Cultivation Grapevine (Vitis vinifera L.)

Root restriction cultivation leads to early maturation and quality improvement, especially in the anthocyanin content in grapevine. However, the molecular mechanisms that underlie these changes have not been thoroughly elucidated. In this study, four small RNA libraries were constructed, which included the green soft stage (GS) and ripe stage (RS) of ‘Muscat’ (Vitis vinifera L.) grape berries that were grown under root restriction (RR) and in traditional cultivation (no root restriction, CK). A total of 162 known miRNAs and 14 putative novel miRNAs were detected from the four small RNA libraries by high-throughput sequencing. An analysis of differentially expressed miRNAs (DEMs) revealed that 13 miRNAs exhibited significant differences in expression between RR and CK at the GS and RS stages, respectively. For different developmental stages of fruit, 23 and 34 miRNAs showed expression differences between the GS and RS stages in RR and CK, respectively. The expression patterns of the eight DEMs and their targets were verified by qRT-PCR, and the expression profiles of target genes were confirmed to be complementary to the corresponding miRNAs in RR and CK. The function of Vvi-miR828, which showed the down regulated expression in the RS stage under root restriction, was identified by gene transformation in Arabidopsis. The anthocyanin content significantly decreased in transgenic lines, which indicates the regulatory capacity of Vvi-miR828 in fruit coloration. The miRNA expression pattern comparison between RR and CK might provide a means of unraveling the miRNA-mediated molecular process regulating grape berry development under root restricted cultivation.