Research on the impact of mobile terminal on fragmented learning efficiency based on DEA

2021 ◽  
Vol 31 (2) ◽  
pp. 250
Author(s):  
Qi Zhu
Keyword(s):  
Mobile Terminal ◽  
Learning Efficiency ◽  
The Impact

scholarly journals Using long short-term memory networks for river flow prediction

2020 ◽  
Vol 51 (6) ◽  
pp. 1358-1376
Author(s):  
Wei Xu ◽  
Yanan Jiang ◽  
Xiaoli Zhang ◽  
Yi Li ◽  
Run Zhang ◽  
...  
Keyword(s):  
River Flow ◽  
Short Term Memory ◽  
River Basins ◽  
Short Term ◽  
Term Memory ◽  
Learning Efficiency ◽  
Flow Prediction ◽  
Non Linear ◽  
Long Short Term Memory ◽  
The Impact

Abstract Deep learning has made significant advances in methodologies and practical applications in recent years. However, there is a lack of understanding on how the long short-term memory (LSTM) networks perform in river flow prediction. This paper assesses the performance of LSTM networks to understand the impact of network structures and parameters on river flow predictions. Two river basins with different characteristics, i.e., Hun river and Upper Yangtze river basins, are used as case studies for the 10-day average flow predictions and the daily flow predictions, respectively. The use of the fully connected layer with the activation function before the LSTM cell layer can substantially reduce learning efficiency. On the contrary, non-linear transformation following the LSTM cells is required to improve learning efficiency due to the different magnitudes of precipitation and flow. The batch size and the number of LSTM cells are sensitive parameters and should be carefully tuned to achieve a balance between learning efficiency and stability. Compared with several hydrological models, the LSTM network achieves good performance in terms of three evaluation criteria, i.e., coefficient of determination, Nash–Sutcliffe Efficiency and relative error, which demonstrates its powerful capacity in learning non-linear and complex processes in hydrological modelling.

scholarly journals On the impact of adaptive test question selection for learning efficiency

2010 ◽  
Vol 55 (2) ◽  
pp. 846-857 ◽  
Author(s):  
Michal Barla ◽  
Mária Bieliková ◽  
Anna Bou Ezzeddinne ◽  
Tomáš Kramár ◽  
Marián Šimko ◽  
...  
Keyword(s):  
Test Question ◽  
Learning Efficiency ◽  
Adaptive Test ◽  
Question Selection ◽  
Selection For ◽  
The Impact

scholarly journals Learners’ Satisfaction and Commitment Towards Online Learning During COVID-19: A Concept Paper

2021 ◽  
pp. 097226292110567
Author(s):  
D. U. N. Ranadewa ◽  
T. Y. Gregory ◽  
D. N. Boralugoda ◽  
J. A. H. T. Silva ◽  
N. A. Jayasuriya
Keyword(s):  
Online Learning ◽  
Literature Review ◽  
Conceptual Model ◽  
Empirical Studies ◽  
Well Being ◽  
Factors Affecting ◽  
Learning Efficiency ◽  
Accessibility Issues ◽  
The Impact ◽  
Mental Well Being

This study offers a comprehensive literature review on the gaps related to online learning efficiency and a structured conceptual model. The findings would be favourable for the learners, lecturers, future researchers, universities and other educational institutes. This study has presented the results of a systematic literature review on the factors affecting the efficiency of online learning and how they impact on satisfaction and commitment of learners. To conduct the literature review, approximately 40 empirical studies were reviewed and analysed. The results reveal that several factors, including academic issues, accessibility issues, technological skills, mental well-being and lecturer commitment, impact depreciating the online learning efficiency, which has made a significant impact on learner satisfaction and learner commitment during the COVID-19 pandemic. If the pandemic would continue, the institutes can use the deliverables to figure out the difficulties encountered by the learners during the pandemic, how to prevent those issues and to search for a solution: to re-open the universities following necessary health guidelines or to resume delivering education online. The literature evaluates the impact of online learning efficiency on learners’ satisfaction and commitment, and there are no adequate empirical studies available for testing the online learning efficiency with respect to learners’ satisfaction and commitment. Hence, in identifying several gaps related to online learning efficiency, this study offers a new structured conceptual model.

scholarly journals Virtual Electronic Health Record Technology with Simulation-Based Learning in an Acute Care Pharmacotherapy Course

Pharmacy ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 123 ◽  
Author(s):  
James Coons ◽  
Lawrence Kobulinsky ◽  
Deborah Farkas ◽  
John Lutz ◽  
Amy Seybert
Keyword(s):  
Electronic Health Record ◽  
Technology Use ◽  
Clinical Skills ◽  
Pharmacy Practice ◽  
Patient Simulation ◽  
Rank Test ◽  
Health Record ◽  
Learning Efficiency ◽  
Electronic Health ◽  
The Impact

Electronic health record (EHR) technology use in the educational setting to advance pharmacy practice skills with patient simulation has not been described previously in the literature. Therefore, the purpose of this study was to evaluate the impact of a virtual EHR on learning efficiency, perceptions of clinical skills, communication, and satisfaction. This was a prospective study conducted in a cardiovascular therapeutics course in the Doctor of Pharmacy curriculum. Students were randomized to use of a virtual EHR with patient simulation or to patient simulation alone (control). The efficiency of learning was assessed by the time to optimal recommendation for each scenario. Surveys (n = 12 questions) were administered electronically to evaluate perceptions of clinical skills, communication, and learning satisfaction. Data were analyzed with the Mann–Whitney U or Wilcoxon signed-rank test as appropriate. Use of the virtual EHR decreased the amount of time needed to provide the optimal treatment recommendations by 25% compared to control. The virtual EHR also significantly improved students’ perceptions of their clinical skills, communication, and satisfaction compared to control. The virtual EHR demonstrated value in learning efficiency while providing students with an engaging means of practicing essential pharmacist functions in a simulated setting.

scholarly journals Credible Navigation Algorithm for GNSS Attack Detection Using Auxiliary Sensor System

2021 ◽  
Vol 11 (14) ◽  
pp. 6321
Author(s):  
Jiahui Song ◽  
Haitao Wu ◽  
Xuqiang Guo ◽  
Siyuan Li ◽  
Yingkui Gong ◽  
...  
Keyword(s):  
Mobile Terminal ◽  
Satellite System ◽  
Attack Detection ◽  
Sensor System ◽  
Measurement Information ◽  
Mobile Terminals ◽  
Gnss Positioning ◽  
Navigation Algorithm ◽  
Global Navigation Satellite ◽  
The Impact

In order to effectively reduce the impact of Global Navigation Satellite System (GNSS) attacks while providing mobile terminals with credible navigation and positioning results, this paper proposes a credible navigation algorithm for GNSS attack detection using an auxiliary sensor system. Based on a credible Kalman filter and measurement information provided by the auxiliary sensor system on mobile terminals, the proposed algorithm can verify the credibility of the GNSS positioning result and determine whether it has suffered from a GNSS attack using the credible verification window and the credible verification threshold. According to the verification results, the algorithm can adaptively select an updated model for measurement correction and achieve a credible navigation result. The algorithm proposed in this paper has been verified on a self-developed mobile terminal, and the experimental results show that the algorithm can provide credible navigation and positioning services for mobile terminals in the context of GNSS attacks.

scholarly journals The Rapid Construction Method of Human Body Model for Virtual Try-On on Mobile Terminal Based on MDD-Net

2021 ◽  
Author(s):  
Naiyu Fang ◽  
Lemiao Qiu ◽  
Shuyou Zhang ◽  
Zili Wang ◽  
Ye Gu ◽  
...  
Keyword(s):  
Human Body ◽  
Fault Tolerant ◽  
Mobile Terminal ◽  
Small Error ◽  
Mobile Internet ◽  
Reconstruction Method ◽  
Human Body Model ◽  
Data Set ◽  
Body Model ◽  
The Impact

Abstract Traditional anthropometric evaluation needs professional measuring tools and operations, which is time- consuming, expensive, and not suitable for virtual try-on. As the mobile internet develops, the issue of human body reconstruction toward virtual try-on needs to be solved. This paper proposes a rapid human body reconstruction method for virtual try-on based on Multidimensional Dense Net (MDD-Net) on mobile terminal. MDD-Net takes the input of fusion features acquired by mobile as input and outputs 3D human body model to mobile supporting for virtual try-on. In the learning fuzzy anthropometric feature module, the example-guided fuzzy anthropometric feature matrix is acquired and default coding elements are interpolated. In the learning multi-perspective silhouette feature module, the fine human body shape features are learned based on DenseNet201. A corresponding fusion feature data set based on SMPL also is generated for MDD-Net training. In the experiments, without append fault-tolerant training samples, on the segmentation noise, nonstandard pose, and perspective error test set, the predicted accuracy of MDD-Net is improved by 13.34%, 55.77%, 34.6% and 43.4%, 37.2%, 9.0% respectively compared to Hs-Net and BfSNet proving its robust with the impact of uncertain positions and poses. And MDD-Net has a small error and standard deviation on critical anthropometric features explaining the effectiveness of our method.

scholarly journals Modeling of the Land Mobile Satellite Channel considering the Terminal’s Driving Direction

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Marie Rieche ◽  
Alexander Ihlow ◽  
Daniel Arndt ◽  
Fernando Pérez-Fontán ◽  
Giovanni Del Galdo
Keyword(s):  
Channel Model ◽  
Elevation Angle ◽  
Estimation Method ◽  
Mobile Terminal ◽  
Channel Statistics ◽  
Environment Type ◽  
Mobile Satellite ◽  
The Impact ◽  
Significant Effort

A precise characterization of the Land Mobile Satellite (LMS) channel, that is, the channel between a satellite and a mobile terminal, is of crucial importance while designing a satellite-based communication system. State-of-the-art statistical LMS channel models offer the advantage of requiring only a few input parameters, which include the environment type and the elevation angle of the satellite. However, the azimuth angle relative to the driving direction of the mobile terminal is usually ignored, as its proper modeling requires either an extensive measurement campaign or a significant effort from the user, as a precise geometrical description of the scenario is required. In this contribution we show that the impact of the driving direction on the channel statistics is not negligible and requires to be modeled explicitly. Moreover, we propose a statistical LMS channel model whose parameters are obtained via an image-based state estimation method. The image-based method is verified by a comparison with measured radio frequency signal levels. The proposed method allows obtaining a complete statistical description of the channel for arbitrary elevation and azimuth angles.

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