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Author(s):  
Sujata Rani ◽  
Parteek Kumar

In this paper, an aspect-based Sentiment Analysis (SA) system for Hindi is presented. The proposed system assigns a separate sentiment towards the different aspects of a sentence as well as it evaluates the overall sentiment expressed in a sentence. In this work, Hindi Dependency Parser (HDP) is used to determine the association between an aspect word and a sentiment word (using Hindi SentiWordNet) and works on the idea that closely connected words come together to express a sentiment about a certain aspect. By generating a dependency graph, the system assigns the sentiment to an aspect having a minimum distance between them and computes the overall polarity of the sentence. The system achieves an accuracy of 83.2% on a corpus of movie reviews and its results are compared with baselines as well as existing works on SA. From the results, it has been observed that the proposed system has the potential to be used in emerging applications like SA of product reviews, social media analysis, etc.


Author(s):  
Clara Hernández Tienda ◽  
Bonaventura Majolo ◽  
Teresa Romero ◽  
Risma Illa Maulany ◽  
Putu Oka Ngakan ◽  
...  

AbstractWhen studying animal behavior in the wild, some behaviors may require observation from a relatively short distance. In these cases, habituation is commonly used to ensure that animals do not perceive researchers as a direct threat and do not alter their behavior in their presence. However, habituation can have significant effects on the welfare and conservation of the animals. Studying how nonhuman primates react to the process of habituation can help to identify the factors that affect habituation and implement habituation protocols that allow other researchers to speed up the process while maintaining high standards of health and safety for both animals and researchers. In this study, we systematically described the habituation of two groups of wild moor macaques (Macaca maura), an Endangered endemic species of Sulawesi Island (Indonesia), to assess the factors that facilitate habituation and reduce impact on animal behavior during this process. During 7 months, we conducted behavioral observations for more than 7,872 encounters and an average of 120 days to monitor how macaque behavior toward researchers changed through time in the two groups under different conditions. We found that both study groups (N = 56, N = 41) became more tolerant to the presence of researchers during the course of the habituation, with occurrence of neutral group responses increasing, and minimum distance to researchers and occurrence of fearful group responses decreasing through time. These changes in behavior were predominant when macaques were in trees, with better visibility conditions, when researchers maintained a longer minimum distance to macaques and, unexpectedly, by the presence of more than one researcher. By identifying these factors, we contribute to designing habituation protocols that decrease the likelihood of fearful responses and might reduce the stress experienced during this process.


2022 ◽  
Author(s):  
Miroslav Poláček ◽  
Alexis Arizpe ◽  
Patrick Hüther ◽  
Lisa Weidlich ◽  
Sonja Steindl ◽  
...  

We present an implementable neural network-based automated detection and measurement of tree-ring boundaries from coniferous species. We trained our Mask R-CNN extensively on over 8,000 manually annotated rings. We assessed the performance of the trained model from our core processing pipeline on real world data. The CNN performed well, recognizing over 99% of ring boundaries (precision) and a recall value of 95% when tested on real world data. Additionally, we have implemented automatic measurements based on minimum distance between rings. With minimal editing for missed ring detections, these measurements were a 99% match with human measurements of the same samples. Our CNN is readily deployable through a Docker container and requires only basic command line skills. Application outputs include editable annotations which facilitate the efficient generation of ring-width measurements from tree-ring samples, an important source of environmental data.


2022 ◽  
pp. 112972982110683
Author(s):  
Filiz Uzumcugil

Employing the in-plane technique in infants the footprint of the ultrasound probe should be considered along with the depth of the vein, and the angle between the needle and the face of the probe, which is crucial in optimization of the visibility of the needle in the beam. Three different ultrasound probes are evaluated for different depths of vein. The hockey-stick probe provided a shorter minimum distance while maintaining the angle between the needle and the face of the probe within an optimal range for visualization of the needle in the beam, supporting its recommendation for infants with regard to its frequency and physical size.


Author(s):  
Marcel Fernandez ◽  
Jorge J. Urroz

AbstractAccording to their strength, the tracing properties of a code can be categorized as frameproof, separating, IPP and TA. It is known that, if the minimum distance of the code is larger than a certain threshold then the TA property implies the rest. Silverberg et al. ask if there is some kind of tracing capability left when the minimum distance falls below the threshold. Under different assumptions, several papers have given a negative answer to the question. In this paper, further progress is made. We establish values of the minimum distance for which Reed-Solomon codes do not posses the separating property.


2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Naveen Prakash Noronha ◽  
Krishna Munishamaih

Abstract An aerodynamic analysis is presented in the current work, which estimates the separation distance between the balloon and the turbine in an airborne wind energy system (AWES). The stability of the structure of AWES depends on the aerodynamic interaction between the turbine and the balloon. A minimum gap must be maintained between the balloon and the wind turbine to reduce the interaction between the balloon and the turbine assembly. Three cases of AWES have been studied with a separation gap of 5 m, 10 m, and 16 m to estimate the minimum distance of separation between the balloon and the turbine. The aerodynamic interaction details suggest that a minimum distance of 13 m needs to be maintained between the turbine and the balloon to avoid the interaction between the balloon and turbine. Steady-state simulations of the rotor are run for various wind conditions to evaluate the efficiency of the duct-mounted configuration. The ducted turbine configuration saw a 7.4% increase in torque than the inducted turbine for a wind speed of 5 m s−1. A torque increase of 17.85% was observed when the separation distance was increased to 16 m from earlier 10 m.


2022 ◽  
Vol 14 (1) ◽  
pp. 0-0

A deterministic decision support system is developed for the assessment of various Indian cities based on the air quality parameters in this research. The present study shapes the assessment of cities as a multi-criteria decision making (MCDM) problem due to the involvement of many indicators. To solve the present assessment problem, an MCDM method, namely, Distance based approach (DBA) that mainly works on the Euclidean distance calculation for each city from the optimal point and ranks the cities on the basis of their calculated distances. The city scoring minimum distance value is ranked at top position and the city with the maximum distance value on the last position.


2021 ◽  
Vol 14 (6) ◽  
pp. 3577
Author(s):  
Celso Voos Vieira ◽  
Pedro Apolonid Viana

O objetivo deste trabalho foi a avaliação da acurácia de algoritmos de classificação do uso e cobertura do solo, quando aplicados a uma imagem orbital de média resolução espacial. Para esse estudo foram utilizadas as bandas espectrais da faixa do visível e infravermelho próximo, do sensor Operational Land Imager – OLI na Baía da Babitonga/SC. Foram propostas nove classes de cobertura do solo, que serviram como controle para testar 11 algoritmos classificadores: Binary Encoding, Example Based Feature Extraction, IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Neural Net, Parallelepiped, Spectral Angle Mapper e Spectral Information Divergence. O classificador Maximum Likelihood foi o que apresentou o melhor desempenho, obtendo um índice Kappa de 0,89 e acurácia global de 95,5%, sendo capaz de distinguir as nove classes de cobertura do solo propostas. Evaluation of the Accuracy of Orbital Image Classification Algorithms in Babitonga Bay, northeast of Santa Catarina A B S T R A C TThe objective of this work was to evaluate the classification algorithms accuracy of the soil use and cover when applied to a spatial mean orbital image. For this study we used the visible and near infrared spectral bands of the Operational Land Imager - OLI sensor in Babitonga Bay / SC. Nine classes of soil cover were proposed, which served as control to test 11 classifier algorithms: Binary Encoding, Example Based Feature Extraction, IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Neural Net, Parallelepiped, Spectral Angle Mapper and Spectral Information Divergence. The Maximum Likelihood classifier presented the best performance, obtaining a Kappa index of 0.89 and a global accuracy of 95.5%, being able to distinguish the nine proposed classes of soil cover.Keywords: Algorithms Accuracy, Babitonga Bay, Orbital image, Remote sensing, Soil Use and Cover. 


Webology ◽  
2021 ◽  
Vol 18 (2) ◽  
pp. 693-708
Author(s):  
A. Pushpa Athisaya Sakila Rani ◽  
N. Suresh Singh

One of the most important food crops in the world is rice, which is highly affected by various plant diseases and pests. Even though there are so many methods to address the concern, detection accuracy is a hectic challenge, which needs to be boosted for an enjoyable farming environment. In the present study a rice disease detection technique was implemented by the fusion of Sailfish optimization – K-means (SCM-KM) and the Faster Region Based Convolutional Neural Network (Faster R-CNN) method. For the optimization of the KM clustering method, Sailfish Optimizer was coupled with the Maximum and Minimum distance algorithm, as well as Chaos theory. The 2D Filtering Mask and Weighted Multilevel Median Filter(2DFM-AMMF) were used to eliminate the sounds. With the aid of the Faster 2D-Otsu technique, the target leaf lesion was segmented from the image. The SCM-KM method is used for detection of rice disease. The Rice diseases were characterized and classified by Region Proposal Networks (RPN) and Faster R-CNN method. Comparative analysis of the SCM-KM+ Faster R-CNN method was performed using the metrics sensitivity, accuracy, and specificity. The proposed detection method produced elevated performance over similar bench marking frameworks.


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