scholarly journals Hierarchical Analysis of Thorax Models to Measure Tidal Volume

2018 ◽  
Vol 4 (1) ◽  
pp. 429-432
Author(s):  
Bernhard Laufer ◽  
Sabine Krueger-Ziolek ◽  
Knut Moeller ◽  
Paul David Docherty ◽  
Fabian Hoeflinger ◽  
...  
Keyword(s):  
Tidal Volume ◽  
Motion Tracking ◽  
Optimization Method ◽  
Optimal Combination ◽  
Hierarchical Optimization ◽  
Hierarchical Analysis ◽  
Hierarchical Method ◽  
Computational Costs ◽  
Sensor Configuration ◽  
Time Required

AbstractMotion tracking of thorax kinematics can be used to determine respiration. However, determining a minimal sensor configuration from 64 candidate sensor locations is associated with high computational costs. Hence, a hierarchical optimization method was proposed to determine the optimal combination of sensors. The hierarchical method was assessed by its ability to quickly determine the sensor combination that will yield optimal modelled tidal volume compared to body plethysmograph measurements. This method was able to find the optimal sensor combinations, in approximately 2% of the estimated time required by an exhaustive search.

Sensor Optimization for Fault Diagnosis in Multi-Fixture Assembly Systems With Distributed Sensing

1998 ◽  
Vol 122 (1) ◽  
pp. 215-226 ◽  
Author(s):  
A. Khan ◽  
D. Ceglarek
Keyword(s):  
Optimization Procedure ◽  
Hierarchical Optimization ◽  
Dual Purpose ◽  
Distributed Sensor ◽  
Sensor Optimization ◽  
Multi Level ◽  
Sensor Configuration ◽  
Limited Sensing ◽  
Sheet Metal Assembly ◽  
Efficient Distribution

Sensing for the system-wide diagnosis of dimensional faults in multi-fixture sheet metal assembly presents significant issues of complexity due to the number of levels of assembly and the number of possible faults at each level. The traditional allocation of sensing at a single measurement station is no longer sufficient to guarantee adequate fault diagnostic information for the increased parts and levels of a complex assembly system architecture. This creates a need for an efficient distribution of limited sensing resources to multiple measurement locations in assembly. The proposed methodology achieves adequate diagnostic performance by configuring sensing to provide an optimally distinctive signature for each fault in assembly. A multi-level, two-step, hierarchical optimization procedure using problem decomposition, based on assembly structure data derived directly from CAD files, is used to obtain such a novel, distributed sensor configuration. Diagnosability performance is quantified in the form of a defined index, which serves the dual purpose of guiding the optimization and establishing the diagnostic worth of any candidate sensor distribution. Examples, using a multi-fixture layout, are presented to illustrate the methodology. [S1087-1357(00)70801-X]

scholarly journals Principal Component Gradiometer technique for removal of spacecraft-generated disturbances from magnetic field data

2020 ◽  
Author(s):  
Ovidiu Dragoş Constantinescu ◽  
Hans-Ulrich Auster ◽  
Magda Delva ◽  
Olaf Hillenmaier ◽  
Werner Magnes ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Principal Component ◽  
Field Measurements ◽  
Magnetic Field Data ◽  
Service Oriented ◽  
Sensor Configuration ◽  
Time Required ◽  
First Time ◽  
The Magnetic Field

Abstract. In situ measurement of the magnetic field using space borne instruments requires either a magnetically clean platform and/or a very long boom for accommodating magnetometer sensors at a large distance from the spacecraft body. This significantly drives up the costs and time required to build a spacecraft. Here we present an alternative sensor configuration and an algorithm allowing for ulterior removal of the spacecraft generated disturbances from the magnetic field measurements, thus lessening the need for a magnetic cleanliness program and allowing for shorter boom length. The proposed algorithm is applied to the Service Oriented Spacecraft Magnetometer (SOSMAG) onboard the Korean geostationary satellite GeoKompsat-2A (GK2A) which uses for the first time a multi-sensor configuration for onboard data cleaning. The successful elimination of disturbances originating from several sources validates the proposed cleaning technique.

Optimal Design of a Gas Turbine Cogeneration Plant by a Hierarchical Optimization Method With Parallel Computing

2018 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Yuji Shinano ◽  
Yuki Wakayama ◽  
Tetsuya Wakui
Keyword(s):  
Optimal Design ◽  
Energy Supply ◽  
Optimization Method ◽  
Optimal Operation ◽  
Hierarchical Optimization ◽  
Cogeneration Plant ◽  
Design Problems ◽  
Computation Efficiency ◽  
Supply Systems ◽  
Energy Supply Systems

To attain the highest performance of energy supply systems, it is necessary to rationally determine types, capacities, and numbers of equipment in consideration of their operational strategies corresponding to seasonal and hourly variations in energy demands. Mixed-integer linear programming (MILP) approaches have been applied widely to such optimal design problems. The authors have proposed a MILP method utilizing the hierarchical relationship between design and operation variables to solve the optimal design problems of energy supply systems efficiently. In addition, some strategies to enhance the computation efficiency have been adopted: bounding procedures at both the levels and ordering of the optimal operation problems at the lower level. In this paper, as an additional strategy to enhance the computation efficiency, parallel computing is adopted to solve multiple optimal operation problems in parallel at the lower level. In addition, the effectiveness of each and combinations of the strategies adopted previously and newly is investigated. This hierarchical optimization method is applied to an optimal design of a gas turbine cogeneration plant, and its validity and effectiveness are clarified through some case studies.

scholarly journals Multiobjective Optimization Method for Polymer Injection Molding Based on a Genetic Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Zhijun Yuan ◽  
Hui Wang ◽  
Xuebing Wei ◽  
Kui Yan ◽  
Cheng Gao
Keyword(s):  
Genetic Algorithm ◽  
Injection Molding ◽  
Multiobjective Optimization ◽  
Optimization Method ◽  
Optimal Combination ◽  
Cover Plate ◽  
Polymer Injection ◽  
Impact Parameters ◽  
Sink Marks ◽  
The Impact

To solve the quality problem of polymer injection parts, a quality prediction and multiobjective optimization method is established. In this method, the parameters that have an important effect on the part quality are selected using an orthogonal testing method, and then a central composite design experiment is performed using these parameters. A mathematical model considering an objective and impact factors is developed using the response surface method. The optimal combination of the impact parameters is determined using a multiobjective genetic algorithm. The injection molding of a typical interior trim part of a car, i.e., the seat belt cover plate, is used as an example to demonstrate the method. The two most troublesome problems in this process—the sink marks and warpage—are multiobjectively analyzed using the established method, and the optimal combination of impact parameters that minimized the defects is determined. The errors of the sink marks and warpage between the experimental and theoretical values were 7.95% and 0.2%, respectively. The optimized parameters were tested in actual injection molding. The results show that the shrinkage and warpage of the parts are obviously improved by optimization using the proposed method, allowing the parts to satisfy the requirements of assembly and appearance.

EFFECTS OF DURATIONS OF 32 °C AND 20 °C POSTHARVEST BULB TREATMENTS ON EARLY FORCING OF IDEAL IRIS

1981 ◽  
Vol 61 (3) ◽  
pp. 647-652
Author(s):  
R. P. DOSS
Keyword(s):  
Storage Conditions ◽  
Optimal Combination ◽  
Postharvest Storage ◽  
C Storage ◽  
Storage Treatment ◽  
Harvest Dates ◽  
Duration Of Storage ◽  
Time Required ◽  
Optimal Set

The effect of the duration of an initial 32 °C and a subsequent 20 °C storage treatment on the performance of greenhouse-forced Ideal iris was investigated. Bulbs from several size categories and from several harvest dates were used with the goal of finding an optimal set of postharvest storage conditions for early forcing. Flowering percentage increased and the length of time required for glasshouse forcing decreased with longer storage (up to 5 wk) at 32 °C. With increasing duration of storage at 20 °C (up to 6 wk) the time required for glasshouse forcing decreased, whereas flowering percentage was influenced only slightly. A near optimal combination for early forcing of 10–11 cm circumference bulbs harvested after 1 Aug., was 4 wk of storage at 32 °C followed by 2 wk at 20 °C and 6 wk at 10 °C. The Dutch treatment for early forcing was unsatisfactory for use with Washington-grown bulbs.

Multi-Agent System for Distributed Adaptive Design

2011 ◽  
Vol 486 ◽  
pp. 217-220 ◽  
Author(s):  
Leszek Kotulski ◽  
Barbara Strug
Keyword(s):  
Adaptive Design ◽  
Graph Transformation ◽  
Design System ◽  
Multi Agent System ◽  
Agent System ◽  
Parallel Application ◽  
Computational Costs ◽  
Transformation Rules ◽  
Multi Agent ◽  
Time Required

This paper deals with the design of a multi-agent system for distributed design. The design processes are often complex and require high computational costs. Yet in many situations many elements of a design process can be computed simultaneously and thus lowering the total time required to finish the design. In this paper an approach based on hypergraph representation and using a formal background of the parallel application of the graph transformation rules is presented (parallel derivation process). The system is illustrated with examples from the floor layout design system.

A Hierarchical Optimization Method for Reaction Path Synthesis

2000 ◽  
Vol 39 (11) ◽  
pp. 4315-4319 ◽  
Author(s):  
Mingheng Li ◽  
Shanying Hu ◽  
Yourun Li ◽  
Jingzhu Shen
Keyword(s):  
Reaction Path ◽  
Optimization Method ◽  
Hierarchical Optimization ◽  
Path Synthesis

scholarly journals Fast Hierarchical Optimization Method for High Speed Channel Design Using Channel Operating Margin

2020 ◽  
Author(s):  
Bo Pu
Keyword(s):  
High Speed ◽  
Impedance Matching ◽  
Optimization Method ◽  
Design Flow ◽  
Hierarchical Optimization ◽  
Physical Parameters ◽  
Channel Design ◽  
Horizontal Structure ◽  
Full Wave ◽  
Operating Margin

This paper proposes a design flow for channel design by a fast hierarchical optimization method based on Channel Operating Margin (COM). Unlike the common design of experiment (DOE), the method performs the design by a hierarchical flow in the level of electrical characteristic while not the usual horizontal structure of physical parameters. It significantly reduces the number of huge samples used in DOE, and thus is able to offer a fast estimation approach for channel in the early design period. In each stage of the vertical flow, the electrical properties of component are extracted by 2.5D or 3D full wave simulator, and thus ensure the accuracy of the channel design. Design strategy for the most crucial discontinuity, Via, to achieve an impedance matching is addressed. Package effect on the COM is also discussed as a reference for adjusting the 3dB criterion of COM in the future.

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