scholarly journals Dynamic Selection of a Video Content Adaptation Strategy from a Pareto Front

2008 ◽  
Vol 52 (4) ◽  
pp. 413-428 ◽  
Author(s):  
A. A. Sofokleous ◽  
M. C. Angelides
Keyword(s):  
Pareto Front ◽  
Adaptation Strategy ◽  
Content Adaptation ◽  
Video Content ◽  
Dynamic Selection ◽  
Selection Of

scholarly journals Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes

Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
Ferdaws Ennaiem ◽  
Abdelbadiâ Chaker ◽  
Juan Sebastián Sandoval Arévalo ◽  
Med Amine Laribi ◽  
Sami Bennour ◽  
...  
Keyword(s):  
Pareto Front ◽  
Parallel Robot ◽  
Elastic Stiffness ◽  
Upper Limb Rehabilitation ◽  
Daily Life Activities ◽  
System A ◽  
The Monte Carlo Method ◽  
Genetic Algorithm Method ◽  
Limb Rehabilitation ◽  
Selection Of

This paper deals with the design of an optimal cable-driven parallel robot (CDPR) for upper limb rehabilitation. The robot’s prescribed workspace is identified with the help of an occupational therapist based on three selected daily life activities, which are tracked using a Qualisys motion capture system. A preliminary architecture of the robot is proposed based on the analysis of the tracked trajectories of all the activities. A multi-objective optimization process using the genetic algorithm method is then performed, where the cable tensions and the robot size are selected as the objective functions to be minimized. The cables tensions are bounded between two limits, where the lower limit ensures a positive tension in the cables at all times and the upper limit represents the maximum torque of the motor. A sensitivity analysis is then performed using the Monte Carlo method to yield the optimal design selected out of the non-dominated solutions, forming the obtained Pareto front. The robot with the highest robustness toward the disturbances is identified, and its dexterity and elastic stiffness are calculated to investigate its performance.

Dynamic selection of dispatching rules for job shop scheduling

2000 ◽  
Vol 11 (1) ◽  
pp. 73-81 ◽  
Author(s):  
V. Subramaniam ◽  
G. K. Lee ◽  
G. S. Hong ◽  
Y. S. Wong ◽  
T. Ramesh
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Dispatching Rules ◽  
Dynamic Selection ◽  
Shop Scheduling ◽  
Selection Of

scholarly journals A Mating Selection Based on Modified Strengthened Dominance Relation for NSGA-III

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2837
Author(s):  
Saykat Dutta ◽  
Sri Srinivasa Raju M ◽  
Rammohan Mallipeddi ◽  
Kedar Nath Das ◽  
Dong-Gyu Lee
Keyword(s):  
Pareto Front ◽  
State Of The Art ◽  
Weight Vector ◽  
Dominance Relation ◽  
Additional Parameter ◽  
Pareto Dominance ◽  
Environmental Selection ◽  
Dominance Relationships ◽  
Test Suites ◽  
Selection Of

In multi/many-objective evolutionary algorithms (MOEAs), to alleviate the degraded convergence pressure of Pareto dominance with the increase in the number of objectives, numerous modified dominance relationships were proposed. Recently, the strengthened dominance relation (SDR) has been proposed, where the dominance area of a solution is determined by convergence degree and niche size (θ¯). Later, in controlled SDR (CSDR), θ¯ and an additional parameter (k) associated with the convergence degree are dynamically adjusted depending on the iteration count. Depending on the problem characteristics and the distribution of the current population, different situations require different values of k, rendering the linear reduction of k based on the generation count ineffective. This is because a particular value of k is expected to bias the dominance relationship towards a particular region on the Pareto front (PF). In addition, due to the same reason, using SDR or CSDR in the environmental selection cannot preserve the diversity of solutions required to cover the entire PF. Therefore, we propose an MOEA, referred to as NSGA-III*, where (1) a modified SDR (MSDR)-based mating selection with an adaptive ensemble of parameter k would prioritize parents from specific sections of the PF depending on k, and (2) the traditional weight vector and non-dominated sorting-based environmental selection of NSGA-III would protect the solutions corresponding to the entire PF. The performance of NSGA-III* is favourably compared with state-of-the-art MOEAs on DTLZ and WFG test suites with up to 10 objectives.

scholarly journals Improving the energy efficiency of VoIP applications in IEEE 802.11 networks through control of the packetization rate

2017 ◽  
Author(s):  
Rafael Estepa ◽  
Antonio Estepa ◽  
Germán Madinabeitia ◽  
Mark Davis
Keyword(s):  
Energy Efficiency ◽  
Ieee 802.11 ◽  
Rate Control ◽  
Control Algorithm ◽  
Energy Savings ◽  
Dynamic Selection ◽  
802.11 Networks ◽  
Ieee 802.11 Networks ◽  
Rate Control Algorithm ◽  
Selection Of

This paper presents an adaptive algorithm that improves the energy efficiency of VoIP applications over IEEE 802.11 networks. The algorithm seeks to achieve the largest energy savings subject to reaching a minimum speech quality under the prevailing network conditions. The control mechanism used is the dynamic selection of the packet size during the communication.This algorithm has been implemented in an experimental testbed and the results demonstrate that our packetization rate control algorithm can provide energy savings in uncongested IEEE 802.11 networks (up to 30%). Furthermore, under poor network conditions the algorithm can prolong the duration of the call before it is dropped at the expense of a higher energy consumption.

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