scholarly journals New Synonyms Extraction Model Based on a Novel Terms Weighting Scheme

2021 ◽  
Vol 45 (1) ◽  
pp. 171-221
Author(s):  
Ahmed Ababneh ◽  
Joan Lu ◽  
Qiang Xu
Keyword(s):  
Statistical Approach ◽  
Linear Time ◽  
Semantic Space ◽  
Weighting Scheme ◽  
New Method ◽  
Bag Of Words ◽  
Model Based ◽  
New Synonyms ◽  
Arabic And English ◽  
Extraction Model

The traditional statistical approach in synonyms extraction is time-consuming. It is necessary to develop a new method to improve the efficiency and accuracy. This research presents a new method in synonyms extraction called Noun Based Distinctive Verbs (NBDV) that replaces the traditional tf-idf weighting scheme with a new weighting scheme called the Orbit Weighing Scheme (OWS). The OWS links the nouns to their semantic space by examining the singular verbs in each context. The new method was compared with important models in the field such as the Skip-Gram, the Continuous Bag of Words, and the GloVe model. The NBDV model was manipulated over the Arabic and English languages and the results showed 47% Recall and 51% Precision in the dictionary-based evaluation and 57.5% Precision in the human experts’ evaluation. Comparing with the synonyms extraction based on tf.idf, the NBDV obtained 11% higher recall and 10% higher precision. Regarding the efficiency, we found that on average, the synonyms extraction of a single noun requires the process of 186 verbs and in 63% of the runs; the number of singular verbs was less than 200. It is concluded that the developed method is efficient and processes the single run in linear time.

scholarly journals A Research on Landslides Automatic Extraction Model Based on the Improved Mask R-CNN

2021 ◽  
Vol 10 (3) ◽  
pp. 168
Author(s):  
Peng Liu ◽  
Yongming Wei ◽  
Qinjun Wang ◽  
Jingjing Xie ◽  
Yu Chen ◽  
...  
Keyword(s):  
Remote Sensing Data ◽  
Extraction Methods ◽  
New Method ◽  
Detection Accuracy ◽  
Sufficient Information ◽  
Automatic Extraction ◽  
Emergency Rescue ◽  
Feature Pyramid ◽  
High Level ◽  
Extraction Model

Landslides are the most common and destructive secondary geological hazards caused by earthquakes. It is difficult to extract landslides automatically based on remote sensing data, which is import for the scenario of disaster emergency rescue. The literature review showed that the current landslides extraction methods mostly depend on expert interpretation which was low automation and thus was unable to provide sufficient information for earthquake rescue in time. To solve the above problem, an end-to-end improved Mask R-CNN model was proposed. The main innovations of this paper were (1) replacing the feature extraction layer with an effective ResNeXt module to extract the landslides. (2) Increasing the bottom-up channel in the feature pyramid network to make full use of low-level positioning and high-level semantic information. (3) Adding edge losses to the loss function to improve the accuracy of the landslide boundary detection accuracy. At the end of this paper, Jiuzhaigou County, Sichuan Province, was used as the study area to evaluate the new model. Results showed that the new method had a precision of 95.8%, a recall of 93.1%, and an overall accuracy (OA) of 94.7%. Compared with the traditional Mask R-CNN model, they have been significantly improved by 13.9%, 13.4%, and 9.9%, respectively. It was proved that the new method was effective in the landslides automatic extraction.

scholarly journals A Statistical Approach to Model the H-Index Based on the Total Number of Citations and the Duration from the Publishing of the First Article

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Mohammad Reza Mahmoudi ◽  
Marzieh Rahmati ◽  
Zulkefli Mansor ◽  
Amirhosein Mosavi ◽  
Shahab S. Band
Keyword(s):  
Nonlinear Regression ◽  
Research Funding ◽  
Statistical Approach ◽  
Practical Approach ◽  
H Index ◽  
Model Based ◽  
Funding Agencies ◽  
Number Of Citations ◽  
The Impact

The productivity of researchers and the impact of the work they do are a preoccupation of universities, research funding agencies, and sometimes even researchers themselves. The h-index (h) is the most popular of different metrics to measure these activities. This research deals with presenting a practical approach to model the h-index based on the total number of citations (NC) and the duration from the publishing of the first article (D1). To determine the effect of every factor (NC and D1) on h, we applied a set of simple nonlinear regression. The results indicated that both NC and D1 had a significant effect on h ( p  < 0.001). The determination of coefficient for these equations to estimate the h-index was 93.4% and 39.8%, respectively, which verified that the model based on NC had a better fit. Then, to record the simultaneous effects of NC and D1 on h, multiple nonlinear regression was applied. The results indicated that NC and D1 had a significant effect on h ( p  < 0.001). Also, the determination of coefficient for this equation to estimate h was 93.6%. Finally, to model and estimate the h-index, as a function of NC and D1, multiple nonlinear quartile regression was used. The goodness of the fitted model was also assessed.

Time Delay-Free Nonlinear Bilateral Teleoperation With Model-Based Predictive Display

2001 ◽  
Author(s):  
Vicente Parra-Vega
Keyword(s):  
Nonlinear Dynamics ◽  
Time Delay ◽  
Finite Time ◽  
Linear Models ◽  
Sliding Mode ◽  
Linear Time ◽  
Contact Forces ◽  
Rigorous Result ◽  
Model Based ◽  
Predictive Display

Abstract Robotic teleoperation is a difficult task because of the inherent difficulty to model and control time-delay nonlinear models. In order to handle tractable models, typically there have been two ways to tackle this problem: i) The first approach is to assume that the system is fast enough and thus the time delay can be neglected, in this way time-delay-free differential equations are obtained such that the controller is time-delay-free. This approach needs further formal study to validate this assumption, and so far there is neither strict nor rigorous result that support this claim, when considering the full nonlinear telerobotic dyanmics. ii) In the second approach, the time delay is considered explicitly, however typically nonlinear dynamics is neglected and then linear models are used to derive time-delay-based control systems. The second approach ignores that the robots are nonlinear systems with strong nonlinear inertial couplings, and therefore controllers based on linear time-delay models render low performance. In this paper, the teleoperation of robots is modeled, including nonlinear dynamics in the continuous domain, without any time delay, and model-based nonlinear continuous second order sliding mode controllers are proposed which guarantee finite-time convergence. Thus, this approach attempts to propose a scheme for the second approach outlined above. The teleoperation system provides force reflection to the human operator, and a kinematic-based predictive display yields visual stimuli while the master robot yields kinesthetic feedback to the operator to allow planning better desired trajectories, including contact forces, in contrast to other predictive displays that have been proposed in the literature. Therefore, the theoretical foundations of finite-time convergent telecontrol system and its advantages are discussed.

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