Selection of Variables for Structural Redesign by Large Admissible Perturbations

2003 ◽  
Author(s):  
Bonhyung Koo ◽  
Michael M. Bernitsas
Keyword(s):  
A Priori ◽  
Structural Elements ◽  
Baseline Design ◽  
Selection Of Variables ◽  
Effective Selection ◽  
Performance Specifications ◽  
Structural Redesign ◽  
Large Admissible Perturbations ◽  
Improved Accuracy ◽  
Selection Of

Redesign or inverse design is the process of generating a new optimal design which satisfies performance specifications starting from a baseline design with undesirable performance. The LargE Admissible Perturbation (LEAP) methodology makes it possible to redesign a structure for large changes in performance objectives and redesign variables without trial and error or repetitive finite element analyses. The next level of challenge in redesign automation is to identify a priori the structural elements and their properties that have the biggest impact and use only those in redesign. Based on LEAP, guidelines are developed in this paper for identifying effective selection of redesign variables for improved accuracy and reduced CPU time. These guidelines enable the designer to define the elements to be redesigned, to partition those elements among redesign groups, and to specify redesign variables in each group. In the numerical applications, an offshore tower is used to verify the developed guidelines. Three models of this tower with 160, 320, and 480 elements are used.

Selection of Variables for Structural Redesign by Large Admissible Perturbations

2003 ◽  
Vol 127 (2) ◽  
pp. 112-121
Author(s):  
Bonhyung Koo ◽  
Michael M. Bernitsas
Keyword(s):  
A Priori ◽  
Structural Elements ◽  
Baseline Design ◽  
Selection Of Variables ◽  
Effective Selection ◽  
Performance Specifications ◽  
Structural Redesign ◽  
Large Admissible Perturbations ◽  
Improved Accuracy ◽  
Selection Of

Redesign or inverse design is the process of generating a new optimal design which satisfies performance specifications starting from a baseline design with undesirable performance. The LargE Admissible Perturbation (LEAP) methodology makes it possible to redesign a structure for large changes in performance objectives and redesign variables without trial and error or repetitive finite element analyses. The next level of challenge in redesign automation is to identify a priori the structural elements and their properties that have the biggest impact and use only those in redesign. Based on LEAP, guidelines are developed in this paper for identifying effective selection of redesign variables for improved accuracy and reduced CPU time. These guidelines enable the designer to define the elements to be redesigned, to partition those elements among redesign groups, and to specify redesign variables in each group. In the numerical applications, an offshore tower is used to verify the developed guidelines. Three models of this tower with 160, 320, and 480 elements are used.

Cognate Space Identification for Forced Response Structural Redesign

2003 ◽  
Vol 127 (3) ◽  
pp. 227-233
Author(s):  
Vincent Y. Blouin ◽  
Michael M. Bernitsas
Keyword(s):  
Direct Method ◽  
A Priori ◽  
Normal Modes ◽  
Forced Response ◽  
Response Amplitude ◽  
Computational Time ◽  
Practical Guidelines ◽  
Structural Redesign ◽  
Large Admissible Perturbations ◽  
Perturbation Equations

Large admissible perturbations (LEAP) is a general methodology, which solves redesign problems of complex structures with, among others, forced response amplitude constraints. In previous work, two LEAP algorithms, namely the incremental method (IM) and the direct method (DM), were developed. A powerful feature of LEAP is the general perturbation equations derived in terms of normal modes, the selection of which is a determinant factor for a successful redesign. The normal modes of a structure may be categorized as stretching, bending, torsional, and mixed modes and grouped into cognate spaces. In the context of redesign by LEAP, the physical interpretation of a mode-to-response cognate space lies in the fact that a mode from one space barely affects change in a mode from another space. Perturbation equations require computation of many perturbation terms corresponding to individual modes. Identifying modes with negligible contribution to the change in forced response amplitude eliminates a priori computation of numerous perturbation terms. Two methods of determining mode-to-response cognate spaces, one for IM and one for DM, are presented and compared. Trade-off between computational time and accuracy is assessed in order to provide practical guidelines to the designer. The developed LEAP redesign algorithms are applied to the redesign of a simple cantilever beam and a complex offshore tower.

Redesign of Cylindrical Shells by Large Admissible Perturbations

2001 ◽  
Vol 45 (03) ◽  
pp. 177-186
Author(s):  
Basem Alzahabi ◽  
Michael M. Bernitsas
Keyword(s):  
Cylindrical Shells ◽  
Baseline Design ◽  
Response Characteristics ◽  
Performance Requirements ◽  
Design Variables ◽  
Structural Redesign ◽  
Large Admissible Perturbations ◽  
Design Requirements ◽  
The Given ◽  
Modal Dynamics

Structural redesign is the process of finding a new design that satisfies a set of performance requirements starting from a poorly performing design. Structural redesign is formulated as a two-state problem where the baseline design exhibits undesirable response characteristics and the objective design satisfies the design requirements. A LargE Admissible Perturbations (LEAP) methodology is developed to formulate and solve the problem of structural redesign of cylindrical shells for modal dynamics. First, the nonlinear perturbation equations of cylindrical shells for modal dynamics are derived relating the baseline to the unknown objective design. The redesign problem is formulated as an optimization problem. Next, an algorithm is developed to solve the nonlinear problem and to identify a locally optimal design that satisfies the given modal dynamics specifications. The developed LEAP algorithm calculates incrementally without trial and error or the repetitive finite-element analyses the structural design variables of the objective design. Numerical applications of cylindrical shell redesign for modal requirements are used to verify the methodology and test the algorithm. The developed methodology identifies incompatible frequency requirements where solutions cannot be achieved. Further, systematic redesign applications show that even for strip uniform shells, modes are linked, making satisfaction of multiple frequency objectives impossible.

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

Bioluminescent proteins prediction with voting strategy.

2020 ◽  
Vol 15 ◽  
Author(s):  
Shulin Zhao ◽  
Ying Ju ◽  
Xiucai Ye ◽  
Jun Zhang ◽  
Shuguang Han
Keyword(s):  
Amino Acid ◽  
Model Building ◽  
Prediction Method ◽  
Pair Composition ◽  
Proposed Model ◽  
Counting Rules ◽  
Significant Phenomenon ◽  
Voting Strategy ◽  
Improved Accuracy ◽  
Selection Of

Background: Bioluminescence is a unique and significant phenomenon in nature. Bioluminescence is important for the lifecycle of some organisms and is valuable in biomedical research, including for gene expression analysis and bioluminescence imaging technology.In recent years, researchers have identified a number of methods for predicting bioluminescent proteins (BLPs), which have increased in accuracy, but could be further improved. Method: In this paper, we propose a new bioluminescent proteins prediction method based on a voting algorithm. We used four methods of feature extraction based on the amino acid sequence. We extracted 314 dimensional features in total from amino acid composition, physicochemical properties and k-spacer amino acid pair composition. In order to obtain the highest MCC value to establish the optimal prediction model, then used a voting algorithm to build the model.To create the best performing model, we discuss the selection of base classifiers and vote counting rules. Results: Our proposed model achieved 93.4% accuracy, 93.4% sensitivity and 91.7% specificity in the test set, which was better than any other method. We also improved a previous prediction of bioluminescent proteins in three lineages using our model building method, resulting in greatly improved accuracy.

scholarly journals Incorporating radiomics into clinical trials: expert consensus on considerations for data-driven compared to biologically driven quantitative biomarkers

2021 ◽  
Author(s):  
Laure Fournier ◽  
Lena Costaridou ◽  
Luc Bidaut ◽  
Nicolas Michoux ◽  
Frederic E. Lecouvet ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Quantitative Imaging ◽  
A Priori ◽  
External Validation ◽  
Data Driven ◽  
Imaging Biomarkers ◽  
Clinical Validation ◽  
Biological Processes ◽  
Imaging Data ◽  
Selection Of

Abstract Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. Key Points • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.

Generalization with Precision: The Role of Negative Teaching Examples in the Instruction of Generalized Grocery Item Selection

1986 ◽  
Vol 11 (4) ◽  
pp. 300-308 ◽  
Author(s):  
Robert H. Horner ◽  
Richard W. Albin ◽  
Ginevera Ralph
Keyword(s):  
Young Adults ◽  
Grocery Store ◽  
Item Selection ◽  
Multiple Baseline ◽  
Correct Selection ◽  
Correct Rejection ◽  
Baseline Design ◽  
Dependent Variables ◽  
Selection Of

For generalization to be functional, it must occur with a precision that results in acquired responses occurring under appropriate, nontrained conditions, and acquired responses not occurring under inappropriate, nontrained conditions. This study examines the effect of differing types of negative teaching examples on the precision with which generalized grocery item selection is learned. Within a split-multiple baseline design, six young adults identified as mildly, moderately, or severely mentally retarded were trained to select or to reject grocery items using picture cards as cues. The dependent variables were correct selection of 10 trained “positive” grocery items and the correct rejection of 20 nontrained “negative” grocery items in a nontrained grocery store. Participants were trained in a grocery store to select 10 positive grocery examples matching their picture cards and to reject either (a) a set of negative examples that were maximally different from the positive examples, or (b) a set of negative examples that were minimally different from the positive examples. Both training sets resulted in participants correctly selecting the 10 positive items in a nontrained store. Training with the “minimally different” negative examples was functionally related to improved rejection of nontrained negative items in the nontrained store. The implications of teaching with minimally different, negative examples are discussed.

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