scholarly journals A Large Scale Evaluation of Distributional Semantic Models: Parameters, Interactions and Model Selection

2014 ◽  
Vol 2 ◽  
pp. 531-546 ◽  
Author(s):  
Gabriella Lapesa ◽  
Stefan Evert
Keyword(s):  
Model Selection ◽  
Large Scale ◽  
Evaluation Study ◽  
Model Parameters ◽  
Scale Evaluation ◽  
Semantic Models ◽  
Parameter Interactions ◽  
Distributional Semantic Models ◽  
Selection Methodology

This paper presents the results of a large-scale evaluation study of window-based Distributional Semantic Models on a wide variety of tasks. Our study combines a broad coverage of model parameters with a model selection methodology that is robust to overfitting and able to capture parameter interactions. We show that our strategy allows us to identify parameter configurations that achieve good performance across different datasets and tasks.

Smartphone-Based Adaptive Driving Maneuver Detection: A Large-Scale Evaluation Study

2017 ◽  
Vol 18 (9) ◽  
pp. 2330-2339 ◽  
Author(s):  
German Castignani ◽  
Thierry Derrmann ◽  
Raphael Frank ◽  
Thomas Engel
Keyword(s):  
Large Scale ◽  
Evaluation Study ◽  
Scale Evaluation

Detecting linguistic idiosyncratic interests in autism using distributional semantic models

2014 ◽  
Author(s):  
Masoud Rouhizadeh ◽  
Emily Prud'hommeaux ◽  
Jan van Santen ◽  
Richard Sproat
Keyword(s):  
Semantic Models ◽  
Distributional Semantic Models

scholarly journals Why ability point estimates can be pointless: a primer on using skill measures from large-scale assessments in secondary analyses

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Clemens M. Lechner ◽  
Nivedita Bhaktha ◽  
Katharina Groskurth ◽  
Matthias Bluemke
Keyword(s):  
Measurement Error ◽  
Statistical Models ◽  
Test Scores ◽  
Large Scale ◽  
Equation Modeling ◽  
Model Parameters ◽  
Advantages And Disadvantages ◽  
Point Estimates ◽  
Secondary Analyses ◽  
Large Scale Assessments

AbstractMeasures of cognitive or socio-emotional skills from large-scale assessments surveys (LSAS) are often based on advanced statistical models and scoring techniques unfamiliar to applied researchers. Consequently, applied researchers working with data from LSAS may be uncertain about the assumptions and computational details of these statistical models and scoring techniques and about how to best incorporate the resulting skill measures in secondary analyses. The present paper is intended as a primer for applied researchers. After a brief introduction to the key properties of skill assessments, we give an overview over the three principal methods with which secondary analysts can incorporate skill measures from LSAS in their analyses: (1) as test scores (i.e., point estimates of individual ability), (2) through structural equation modeling (SEM), and (3) in the form of plausible values (PVs). We discuss the advantages and disadvantages of each method based on three criteria: fallibility (i.e., control for measurement error and unbiasedness), usability (i.e., ease of use in secondary analyses), and immutability (i.e., consistency of test scores, PVs, or measurement model parameters across different analyses and analysts). We show that although none of the methods are optimal under all criteria, methods that result in a single point estimate of each respondent’s ability (i.e., all types of “test scores”) are rarely optimal for research purposes. Instead, approaches that avoid or correct for measurement error—especially PV methodology—stand out as the method of choice. We conclude with practical recommendations for secondary analysts and data-producing organizations.

scholarly journals Greenspace and depression in Japanese Older Adults considering physical activities: JAGES study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Nishigaki ◽  
C Koga ◽  
M Hanazato ◽  
K Kondo
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Large Scale ◽  
Depression Scale ◽  
Public Health Problem ◽  
Evaluation Study ◽  
Physical Activities ◽  
Residential Areas ◽  
Cross Sectional ◽  
Local Climate

Abstract Introduction Older adult's depression is a public health problem. In recent years, exposure to local greenspace is beneficial to mental health via increased physical activity in people. However, few studies approach the relationship between greenspace and depression while simultaneously considering the frequency, time, and the number of types of physical activity, and large-scale surveys targeting the older adults. Methods Cross-sectional data conducted in 2016 by the Japan Gerontological Evaluation Study was used. The analysis included older adults aged 65 and over who did not require care or assistance, and a total of 126,878 people in 881 School districts. The explanatory variable is the percentage of the greenspace of the area, and the greenspace data used is data created from satellite photographs acquired by observation satellites of the Japan Aerospace Exploration Agency. The objective variable was depression (Geriatric Depression Scale 5 points or more). The analysis method was a multi-level logistic regression analysis. Physical activity was the number of sports-related hobbies, the frequency of participation in sports meetings, and walking time in daily life. Other factors such as personal attributes, population density of residential areas, and local climate were also considered. Results Depression in the survey was 20.4%. The abundance of greenspace was still associated with depression, considering all physical activity. The odds ratio of depression in areas with more greenspace was 0.92 (95% CI 0.87 - 0.98) compared to areas with less greenspace. Conclusions It became clear that areas with many greenspace were still associated with low depression, even considering the frequency, time and number of physical activities. It is conceivable that the healing effect of seeing greenspace, the reduction of air pollution and noise, etc. are related to the lack of depression without going through physical activity. Key messages In Japan, older adults are less depressed when there are many local greenspace. It became clear that areas with many greenspace were still associated with low depression, even considering physical activities.

scholarly journals Power-to-Green Methanol via CO2 Hydrogenation—A Concept Study Including Oxyfuel Fluidized Bed Combustion of Biomass

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4638
Author(s):  
Simon Pratschner ◽  
Pavel Skopec ◽  
Jan Hrdlicka ◽  
Franz Winter
Keyword(s):  
Large Scale ◽  
Positive Impact ◽  
Renewable Energy Sources ◽  
Air Separation ◽  
Model Parameters ◽  
Processing Unit ◽  
Fluidized Bed Combustion ◽  
Separation Unit ◽  
Oxyfuel Combustion ◽  
Wind Park

A revolution of the global energy industry is without an alternative to solving the climate crisis. However, renewable energy sources typically show significant seasonal and daily fluctuations. This paper provides a system concept model of a decentralized power-to-green methanol plant consisting of a biomass heating plant with a thermal input of 20 MWth. (oxyfuel or air mode), a CO2 processing unit (DeOxo reactor or MEA absorption), an alkaline electrolyzer, a methanol synthesis unit, an air separation unit and a wind park. Applying oxyfuel combustion has the potential to directly utilize O2 generated by the electrolyzer, which was analyzed by varying critical model parameters. A major objective was to determine whether applying oxyfuel combustion has a positive impact on the plant’s power-to-liquid (PtL) efficiency rate. For cases utilizing more than 70% of CO2 generated by the combustion, the oxyfuel’s O2 demand is fully covered by the electrolyzer, making oxyfuel a viable option for large scale applications. Conventional air combustion is recommended for small wind parks and scenarios using surplus electricity. Maximum PtL efficiencies of ηPtL,Oxy = 51.91% and ηPtL,Air = 54.21% can be realized. Additionally, a case study for one year of operation has been conducted yielding an annual output of about 17,000 t/a methanol and 100 GWhth./a thermal energy for an input of 50,500 t/a woodchips and a wind park size of 36 MWp.

Sign in / Sign up

Export Citation Format

Share Document