scholarly journals IBOA-Based Optimization of Cross-Sectional Dimension of Rods for a 3-RRR PPM to Minimize Energy Consumption

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yin Gao ◽  
Ke Chen ◽  
Hong Gao ◽  
Hongmei Zheng ◽  
Lei Wang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Inverse Dynamics ◽  
Matrix Theory ◽  
Euler Method ◽  
Feasible Region ◽  
Single Object ◽  
Cross Sectional ◽  
Cross Sectional Dimension

For obtaining optimal cross-sectional dimensions of rods for a 3-RRR planar parallel manipulator (PPM) to minimize energy consumption, the inverse dynamics of the manipulator is modeled based on the Newton–Euler method, after which the coefficient matrix of the inverse dynamics equation is decomposed based on matrix theory. Hence, the objective function, that is, the logical relationship between the energy consumption of the manipulator and the cross-sectional dimension of each rod, is established. However, in solving the multidimensional constrained single-object optimization problem, there are difficulties such as the penalty function’s sensitivity to the penalty factors if the problem is transformed into the one of unconstrained multiobjective optimization. Therefore, to properly handle the constraints, an improved butterfly optimization algorithm (IBOA) is presented to ensure that the new iterated point always falls into the feasible region according to the butterfly optimization algorithm (BOA). Finally, the comparisons among the IBOA, particle swarm optimization (PSO), and BOA and further experiments of the physical prototype are implemented to validate the effectiveness of the proposed theoretical model and numerical algorithm. Results indicate that the proposed IBOA is more suitable for solving the constrained single-object optimization problem with better convergence speed and accuracy.

scholarly journals Machine Learning-Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Shuchen Zhou ◽  
Waqas Jadoon ◽  
Junaid Shuja
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Attack Detection ◽  
Edge Computing ◽  
Detection Methods ◽  
Mobile Edge Computing ◽  
Frequency Division ◽  
Iterative Optimization Algorithm

This paper presents an in-depth study and analysis of offloading strategies for lightweight user mobile edge computing tasks using a machine learning approach. Firstly, a scheme for multiuser frequency division multiplexing approach in mobile edge computing offloading is proposed, and a mixed-integer nonlinear optimization model for energy consumption minimization is developed. Then, based on the analysis of the concave-convex properties of this optimization model, this paper uses variable relaxation and nonconvex optimization theory to transform the problem into a convex optimization problem. Subsequently, two optimization algorithms are designed: for the relaxation optimization problem, an iterative optimization algorithm based on the Lagrange dual method is designed; based on the branch-and-bound integer programming method, the iterative optimization algorithm is used as the basic algorithm for each step of the operation, and a global optimization algorithm is designed for transmitting power allocation, computational offloading strategy, dynamic adjustment of local computing power, and receiving energy channel selection strategy. Finally, the simulation results verify that the scheduling strategy of the frequency division technique proposed in this paper has good energy consumption minimization performance in mobile edge computation offloading. Our model is highly efficient and has a high degree of accuracy. The anomaly detection method based on a decision tree combined with deep learning proposed in this paper, unlike traditional IoT attack detection methods, overcomes the drawbacks of rule-based security detection methods and enables them to adapt to both established and unknown hostile environments. Experimental results show that the attack detection system based on the model achieves good detection results in the detection of multiple attacks.

A Hybrid Swarm Optimization Algorithm For Reducing Energy Consumption In The Cloud

2018 ◽  
Vol 11 ◽  
Author(s):  
Mohammed Mostafa Abdulghafoor ◽  
Raed Abdulkareem Hasan ◽  
Zeyad Hussein Salih ◽  
Hayder Ali Nemah Alshara ◽  
Nicolae Tapus
Keyword(s):  
Energy Consumption ◽  
Optimization Algorithm ◽  
Hybrid Swarm ◽  
Swarm Optimization ◽  
Reducing Energy

scholarly journals Optimization Issues of a Hammer Mill Working Process Using Statistical Modelling

2021 ◽  
Vol 13 (2) ◽  
pp. 973
Author(s):  
Gigel Paraschiv ◽  
Georgiana Moiceanu ◽  
Gheorghe Voicu ◽  
Mihai Chitoiu ◽  
Petru Cardei ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Optimization Problem ◽  
Specific Energy Consumption ◽  
Statistical Modelling ◽  
Hammer Mill ◽  
Objective Functions ◽  
Working Process ◽  
Rotor Spinning ◽  
Milled Material ◽  
Different Types

Our paper presents the hammer mill working process optimization problem destined for milling energetic biomass (MiscanthusGiganteus and Salix Viminalis). For the study, functional and constructive parameters of the hammer mill were taken into consideration in order to reduce the specific energy consumption. The energy consumption dependency on the mill rotor spinning frequency and on the sieve orifices in use, as well as on the material feeding flow, in correlation with the vegetal biomass milling degree was the focus of the analysis. For obtaining this the hammer mill was successively equipped with 4 different types of hammers that grind the energetic biomass, which had a certain humidity content and an initial degree of reduction ratio of the material. In order to start the optimization process of hammer mill working process, 12 parameters were defined. The objective functions which minimize hammer mill energy consumption and maximize the milled material percentage with a certain specific granulation were established. The results obtained can serve as the basis for choosing the optimal working, constructive, and functional parameters of hammer mills in this field, and for a better design of future hammer mills.

scholarly journals Efficient Placement of Service Function Chains in Cloud Computing Environments

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 323
Author(s):  
Marwa A. Abdelaal ◽  
Gamal A. Ebrahim ◽  
Wagdy R. Anis
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Response Time ◽  
Optimization Problem ◽  
Service Providers ◽  
Virtual Network ◽  
Placement Problem ◽  
Service Function ◽  
Network Functions ◽  
Bandwidth Consumption

The widespread adoption of network function virtualization (NFV) leads to providing network services through a chain of virtual network functions (VNFs). This architecture is called service function chain (SFC), which can be hosted on top of commodity servers and switches located at the cloud. Meanwhile, software-defined networking (SDN) can be utilized to manage VNFs to handle traffic flows through SFC. One of the most critical issues that needs to be addressed in NFV is VNF placement that optimizes physical link bandwidth consumption. Moreover, deploying SFCs enables service providers to consider different goals, such as minimizing the overall cost and service response time. In this paper, a novel approach for the VNF placement problem for SFCs, called virtual network functions and their replica placement (VNFRP), is introduced. It tries to achieve load balancing over the core links while considering multiple resource constraints. Hence, the VNF placement problem is first formulated as an integer linear programming (ILP) optimization problem, aiming to minimize link bandwidth consumption, energy consumption, and SFC placement cost. Then, a heuristic algorithm is proposed to find a near-optimal solution for this optimization problem. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that VNFRP can significantly improve load balancing by 80% when the number of replicas is increased. Additionally, VNFRP provides more than a 54% reduction in network energy consumption. Furthermore, it can efficiently reduce the SFC placement cost by more than 67%. Moreover, with the advantages of a fast response time and rapid convergence, VNFRP can be considered as a scalable solution for large networking environments.

scholarly journals Associations between Fasting Duration, Timing of First and Last Meal, and Cardiometabolic Endpoints in the National Health and Nutrition Examination Survey

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2686
Author(s):  
Michael D. Wirth ◽  
Longgang Zhao ◽  
Gabrielle M. Turner-McGrievy ◽  
Andrew Ortaglia
Keyword(s):  
Energy Consumption ◽  
National Health ◽  
Survey Design ◽  
Glycosylated Hemoglobin ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Nutrition Examination Survey ◽  
Cross Sectional ◽  
Health And Nutrition ◽  
Fasting Duration

Background: Research indicates potential cardiometabolic benefits of energy consumption earlier in the day. This study examined the association between fasting duration, timing of first and last meals, and cardiometabolic endpoints using data from the National Health and Nutrition Examination Survey (NHANES). Methods: Cross-sectional data from NHANES (2005–2016) were utilized. Diet was obtained from one to two 24-h dietary recalls to characterize nighttime fasting duration and timing of first and last meal. Blood samples were obtained for characterization of C-reactive protein (CRP); glycosylated hemoglobin (HbA1c %); insulin; glucose; and high-density lipoprotein (HDL), low-density lipoprotein (LDL), and total cholesterol. Survey design procedures for adjusted linear and logistic regression were performed. Results: Every one-hour increase in nighttime fasting duration was associated with a significantly higher insulin and CRP, and lower HDL. Every one-hour increase in timing of the last meal of the day was statistically significantly associated with higher HbA1c and lower LDL. Every one-hour increase in first mealtime was associated with higher CRP (β = 0.044, p = 0.0106), insulin (β = 0.429, p < 0.01), and glucose (β = 0.662, p < 0.01), and lower HDL (β = −0.377, p < 0.01). Conclusion: In this large public health dataset, evidence for the beneficial effect of starting energy consumption earlier in the day on cardiometabolic endpoints was observed.

scholarly journals Minimization of energy consumption by building shape optimization using an improved Manta-Ray Foraging Optimization algorithm

2021 ◽  
Vol 7 ◽  
pp. 1068-1078
Author(s):  
Jiaying Feng ◽  
Xiaoguang Luo ◽  
Mingzhe Gao ◽  
Adnan Abbas ◽  
Yi-Peng Xu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Shape Optimization ◽  
Optimization Algorithm ◽  
Building Shape ◽  
Manta Ray

Dietary intake among under-, normal- and overweight 9- and 15-year-old Estonian and Swedish schoolchildren

2007 ◽  
Vol 10 (3) ◽  
pp. 311-322 ◽  
Author(s):  
Inga Villa ◽  
Agneta Yngve ◽  
Eric Poortvliet ◽  
Andrej Grjibovski ◽  
Krystiine Liiv ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Dietary Intake ◽  
Dietary Habits ◽  
Age Groups ◽  
Meat Products ◽  
Food Group ◽  
Biological Factors ◽  
Cross Sectional ◽  
Total Food ◽  
Country Specific

AbstractObjectivesTo determine the differences in macronutrient and food group contribution to total food and energy intakes between Estonian and Swedish under-, normal- and overweight schoolchildren, and to estimate the association between diet and body mass index (BMI).DesignCross-sectional comparison between Estonian and Swedish children and adolescents of different BMI groups.SettingTwenty-five schools from one region in Estonia and 42 in two regions of central Sweden.SubjectsIn total 2308 participants (1176 from Estonia and 1132 from Sweden), including 1141 children with a mean age of 9.6 ± 0.5 years and 1167 adolescents with a mean age of 15.5 ± 0.6 years.ResultsOverweight was more prevalent among younger girls in Sweden (17.0 vs. 8.9%) and underweight among girls of both age groups in Estonia (7.9 vs. 3.5% in younger and 10.5 vs. 5.1% in older age group of girls). Compared with that of normal- and underweight peers, the diet of overweight Estonian children contained more energy as fat (36.8 vs. 31.7%) but less as carbohydrates, and they consumed more milk and meat products. Absolute BMI of Estonian participants was associated positively with energy consumption from eggs and negatively with energy consumption from sweets and sugar. Swedish overweight adolescents tended to consume more energy from protein and milk products. Risk of being overweight was positively associated with total energy intake and energy from fish or meat products. In both countries the association of overweight and biological factors (pubertal maturation, parental BMI) was stronger than with diet.ConclusionThe finding that differences in dietary intake between under-, normal- and overweight schoolchildren are country-specific suggests that local dietary habits should be considered in intervention projects addressing overweight.

Review of Fire Performance Experiment of Concrete-Filled Steel Tubular Columns

2014 ◽  
Vol 638-640 ◽  
pp. 1397-1401
Author(s):  
Kai Xiang ◽  
Guo Hui Wang ◽  
Yan Chong Pan
Keyword(s):  
Load Ratio ◽  
Experimental Results ◽  
Research Progress ◽  
Future Research ◽  
Fire Performance ◽  
Cross Sectional ◽  
Tubular Columns ◽  
Cross Sectional Dimension ◽  
Cfst Columns ◽  
In Fire

This paper presents a review of research progress in fire performance of concrete-filled steel tubular (CFST) columns. Experimental results of CFST columns in fire are reviewed with influence parameters, such as heights, cross-sectional dimension, section types, concrete types, concrete strengths, load ratio, load eccentricity, fire exposed sides and so on. Some conclusions of CFST columns under fire conditions are summarized. Deficiencies in the fire performance experiments of CFST columns are identified, which provide the focus for future research in the field.

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