Search results for "Percentage"
showing 10 items of 101 documents
Trends and cycles in U.S. job mobility
2021
Recent studies document a decline in U.S. labor-market fluidity from as early as the 1970s on. Making use of the Annual Social and Economic (ASEC) supplement to the Current Population Survey (CPS), I uncover a pronounced increase in job-to-job mobility from the 1970s to the 1990s, i.e., the annual share of continuously employed job-to-job movers rises from 5.9 percent of the labor force in 1975–1979 to 8.8 percent in 1995–1999. Job-to-job mobility exhibits a downward trend only since the turn of the millennium. In order to provide a formal economic interpretation, I additionally estimate the parameters of the random on-the-job search model. Furthermore, I document that job-to-job mobility h…
Comparing Recurrent Neural Networks using Principal Component Analysis for Electrical Load Predictions
2021
Electrical demand forecasting is essential for power generation capacity planning and integrating environment-friendly energy sources. In addition, load predictions will help in developing demand-side management in coordination with renewable power generation. Meteorological conditions influence urban area load pattern; therefore, it is vital to include weather parameters for load predictions. Machine Learning algorithms can effectively be used for electrical load predictions considering impact of external parameters. This paper explores and compares the basic Recurrent Neural Networks (RNN); Simple Recurrent Neural Networks (Vanilla RNN), Gated Recurrent Units (GRU), and Long Short-Term Me…
Relative evaluation of regression tools for urban area electrical energy demand forecasting
2019
Abstract Load forecasting is the most fundamental application in Smart-Grid, which provides essential input to Demand Response, Topology Optimization and Abnormally Detection, facilitating the integration of intermittent clean energy sources. In this work, several regression tools are analyzed using larger datasets for urban area electrical load forecasting. The regression tools which are used are Random Forest Regressor, k-Nearest Neighbour Regressor and Linear Regressor. This work explores the use of regression tool for regional electric load forecasting by correlating lower distinctive categorical level (season, day of the week) and weather parameters. The regression analysis has been do…
ANN modelling of CO2 refrigerant cooling system COP in a smart warehouse
2020
Author's accepted manuscript Industrial cooling systems consume large quantities of energy with highly variable power demand. To reduce environmental impact and overall energy consumption, and to stabilize the power requirements, it is recommended to recover surplus heat, store energy, and integrate renewable energy production. To control these operations continuously in a complex energy system, an intelligent energy management system can be employed using operational data and machine learning. In this work, we have developed an artificial neural network based technique for modelling operational CO2 refrigerant based industrial cooling systems for embedding in an overall energy management s…
Limited Usefulness of Capture Procedure and Capture Percentage for Evaluating Reproducibility in Psychological Science
2018
In psychological science, there is an increasing concern regarding the reproducibility of scientific findings. For instance, Replication Project: Psychology (Open Science Collaboration, 2015) found that the proportion of successful replication in psychology was 41%. This proportion was calculated based on Cumming and Maillardet’s (2006) widely employed capture procedure (CPro) and capture percentage (CPer). Despite the popularity of CPro and CPer, we believe that using them may lead to an incorrect conclusion of (a) successful replication when the population effect sizes in the original and replicated studies are different; and (b) unsuccessful replication when the population effect sizes i…
A new method for forecasting energy output of a large-scale solar power plant based on long short-term memory networks a case study in Vietnam
2021
Abstract This paper proposes a new model for short-term forecasting power generation capacity of large-scale solar power plant (SPP) in Vietnam considering the fluctuations of weather factors when applying the Long Short-Term Memory networks (LSTM) algorithm. At first, a configuration of the model based on the LSTM algorithm is selected in accordance with the weather and operating conditions of SPP in Vietnam. Not only different structures of LSTM model but also other conventional forecasting methods for time series data are compared in terms of error accuracy of forecast on test data set to evaluate the effectiveness and select the most suitable LSTM configuration. The most suitable config…
2020
Introduction/Purpose: Physical activity and sedentary time may associate with physical fitness and body composition. Yet, there exists some observational studies that have investigated the associations of device-based measures of sedentary time and physical activity (PA) with cardiorespiratory fitness (CRF) and body composition but associations with muscular fitness (MF) are less studied.Methods: Objective sedentary time and physical activity was measured by a hip worn accelerometer from 415 young adult men (age: mean 26, standard deviation 7 years). Cardiorespiratory fitness (VO2max) (CRF) was determined using a graded cycle ergometer test until exhaustion. Maximal force of lower extremiti…
Wave and Wind Energy Systems Integration in Vietnam: Analysis of Energy Potential and Economic Feasibility
2020
Vietnam energy demand is currently growing at a very high annual rate, with the government being very interested in investments in renewable energies. Since the region with the highest solar and wind potential is far away from the big load centers, an investigation of offshore energy resources is here proposed. In this study, a review of previous energy potential assessments is provided. Moreover, the minimum feed-in-tariff to make the investments profitable is evaluated, showing that the current tariff for offshore wind plants is largely unattractive.
Genetic parameters for somatic cell score according to udder infection status in Valle del Belice dairy sheep and impact of imperfect diagnosis of in…
2010
Abstract Background Somatic cell score (SCS) has been promoted as a selection criterion to improve mastitis resistance. However, SCS from healthy and infected animals may be considered as separate traits. Moreover, imperfect sensitivity and specificity could influence animals' classification and impact on estimated variance components. This study was aimed at: (1) estimating the heritability of bacteria negative SCS, bacteria positive SCS, and infection status, (2) estimating phenotypic and genetic correlations between bacteria negative and bacteria positive SCS, and the genetic correlation between bacteria negative SCS and infection status, and (3) evaluating the impact of imperfect diagno…
Cost to the cavity-nest ant Temnothorax crassispinus (Hymenoptera : Formicidae) of overwintering aboveground
2013
Most species of ants inhabiting the temperate zone overwinter underground, whereas those of the genus Temnothorax remain in nests aboveground. I studied the cost of aboveground overwintering. Workers of Temnothorax crassispinus survived in higher numbers (median = 88%) in artificial nests experimentally buried at a depth of 5 cm than those in nests on the surface (48%) of the soil. The results support the hypothesis that overwintering aboveground could be a consequence of a limited supply of nests and/or the advantage of being able to respond quickly to warm temperatures in spring.