Demystifying the Relationship Between Use-Phase Attributes and Energy Consumption: A Case Study of Personal Computers

2017 ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Sara Behdad
Keyword(s):  
Energy Consumption ◽  
Consumer Electronics ◽  
Computer Usage ◽  
Data Set ◽  
Self Monitoring ◽  
Hard Drives ◽  
Usage Behavior ◽  
Residential Energy Consumption Survey ◽  
Use Phase ◽  
The Relationship

Understanding the use-phase energy consumption of consumer electronics is of great importance, as it has significant effects on both policy and product designs. Inaccurate estimations of the use phase energy consumption can offset the results of the life cycle assessment and impeach the effectiveness of the energy intervention policies. The use phase energy consumption is governed by the consumers’ usage behavior. However, the relationship between consumers’ attributes and their usage behavior, and energy consumption is not clear. This paper analyzes two data sets, a data set of hard drives’ Self-Monitoring, Analysis and Reporting Technology (S.M.A.R.T) and the Residential Energy Consumption Survey (RECS) to shed light on the relationship between usage behavior and energy consumption. Several supervised and unsupervised machine-learning methods have been used to reveal possible trends in the consumers’ use-phase attributes. The results of the study suggest that various demographic properties and behavioral variables related to computer usage affect the energy consumption profile of households.

The Relationship Between Self-Monitoring, Extraversion, Neuroticism, and Choice of Potential Partners

2000 ◽  
Author(s):  
Laura J. Blalock ◽  
Janet A. Carter ◽  
Angela N. Dennis ◽  
Sandra L. Wiper ◽  
Helen C. Harton
Keyword(s):  
Self Monitoring ◽  
The Relationship

scholarly journals Empirical Research on the Relationship amongst Renewable Energy Consumption, Economic Growth and Foreign Direct Investment in Kazakhstan and Uzbekistan

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 332
Author(s):  
Janusz Grabara ◽  
Arsen Tleppayev ◽  
Malika Dabylova ◽  
Leonardus W. W. Mihardjo ◽  
Zdzisława Dacko-Pikiewicz
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Direct Investment ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Renewable Energy Consumption ◽  
Integration Test ◽  
The Relationship

In this contemporary era, environmental problems spread at different levels in all countries of the world. Economic growth does not just depend on prioritizing the environment or improving the environmental situation. If the foreign direct investment is directed to the polluting industries, they will increase pollution and damage the environment. The purpose of the study is to consider the relationship between foreign direct investment in Kazakhstan and Uzbekistan and economic growth and renewable energy consumption. The study is based on data obtained from 1992 to 2018. The results show that there is a two-way link between foreign direct investment and renewable energy consumption in the considered two countries. The Granger causality test approach is applied to explore the causal relationship between the variables. The Johansen co-integration test approach is also employed to test for a relationship. The empirical results verify the existence of co-integration between the series. The main factors influencing renewable energy are economic growth and electricity consumption. To reduce dependence on fuel-based energy sources, Kazakhstan and Uzbekistan need to attract energy to renewable energy sources and implement energy efficiency based on rapid progress. This is because renewable energy sources play the role of an engine that stimulates the production process in the economy for all countries.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals The Relationship between Economic Growth and Pollution in Some New European Union Member States: A Dynamic Panel ARDL Approach

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2363
Author(s):  
Mihaela Simionescu ◽  
Carmen Beatrice Păuna ◽  
Mihaela-Daniela Vornicescu Niculescu
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Ghg Emissions ◽  
Kuznets Curve ◽  
Renewable Energy Consumption ◽  
Panel Ardl ◽  
Domestic Credit ◽  
The Impact ◽  
The Relationship

Considering the necessity of achieving economic development by keeping the quality of the environment, the aim of this paper is to study the impact of economic growth on GHG emissions in a sample of Central and Eastern European (CEE) countries (V4 countries, Bulgaria and Romania) in the period of 1996–2019. In the context of dynamic ARDL panel and environmental Kuznets curve (EKC), the relationship between GHG and GDP is N-shaped. A U-shaped relationship was obtained in the renewable Kuznets curve (RKC). Energy consumption, domestic credit to the private sector, and labor productivity contribute to pollution, while renewable energy consumption reduces the GHG emissions. However, more efforts are required for promoting renewable energy in the analyzed countries.

scholarly journals Energy Efficient SWIPT Based Mobile Edge Computing Framework for WSN-Assisted IoT

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4798
Author(s):  
Fangni Chen ◽  
Anding Wang ◽  
Yu Zhang ◽  
Zhengwei Ni ◽  
Jingyu Hua
Keyword(s):  
Energy Consumption ◽  
Transmission Rate ◽  
Edge Computing ◽  
Energy Harvest ◽  
Total System ◽  
Mobile Edge Computing ◽  
Weight Factor ◽  
Iot Devices ◽  
System Variables ◽  
The Relationship

With the increasing deployment of IoT devices and applications, a large number of devices that can sense and monitor the environment in IoT network are needed. This trend also brings great challenges, such as data explosion and energy insufficiency. This paper proposes a system that integrates mobile edge computing (MEC) technology and simultaneous wireless information and power transfer (SWIPT) technology to improve the service supply capability of WSN-assisted IoT applications. A novel optimization problem is formulated to minimize the total system energy consumption under the constraints of data transmission rate and transmitting power requirements by jointly considering power allocation, CPU frequency, offloading weight factor and energy harvest weight factor. Since the problem is non-convex, we propose a novel alternate group iteration optimization (AGIO) algorithm, which decomposes the original problem into three subproblems, and alternately optimizes each subproblem using the group interior point iterative algorithm. Numerical simulations validate that the energy consumption of our proposed design is much lower than the two benchmark algorithms. The relationship between system variables and energy consumption of the system is also discussed.

Railroad Integration and Uneven Development on the European Periphery, 1870–1910

2021 ◽  
Vol 45 (2) ◽  
pp. 261-289
Author(s):  
Eduard J. Alvarez-Palau ◽  
Alfonso Díez-Minguela ◽  
Jordi Martí-Henneberg
Keyword(s):  
Economic Development ◽  
Positive Impact ◽  
Data Set ◽  
Per Capita Gdp ◽  
Catching Up ◽  
Nation States ◽  
Railroad Network ◽  
Per Capita ◽  
European Periphery ◽  
The Relationship

AbstractThis study explores the relationship between railroad integration and regional development on the European periphery between 1870 and 1910, based on a regional data set including 291 spatial units. Railroad integration is proxied by railroad density, while per capita GDP is used as an indicator of economic development. The period under study is of particular relevance as it has been associated with the second wave of railroad construction in Europe and also coincides with the industrialization of most of the continent. Overall, we found that railroads had a significant and positive impact on the growth of per capita GDP across Europe. The magnitude of this relationship appears to be relatively modest, but the results obtained are robust with respect to a number of different specifications. From a geographical perspective, we found that railroads had a significantly greater influence on regions located in countries on the northern periphery of Europe than in other outlying areas. They also helped the economies of these areas to begin the process of catching up with the continent’s industrialized core. In contrast, the regions on the southern periphery showed lower levels of economic growth, with this exacerbating the preexisting divergence in economic development. The expansion of the railroad network in them was unable to homogenize the diffusion of economic development and tended to further benefit the regions that were already industrialized. In most of the cases, the capital effect was magnified, and this contributed to the consolidation of newly created nation-states.

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