scholarly journals Equivalent Shell Model of Elastic Gridshells Including the Effect of the Geometric Curvature

2021 ◽  
Vol 2 (3) ◽  
pp. 630-649
Author(s):  
Maria Luisa Regalo ◽  
Stefano Gabriele ◽  
Valerio Varano ◽  
Ginevra Salerno
Keyword(s):  
Constitutive Law ◽  
Periodic Homogenization ◽  
Identification Procedure ◽  
Proposed Model ◽  
Geometric Curvature ◽  
Representative Element Volume ◽  
Equivalent Continuum ◽  
Load Conditions ◽  
Selection Of ◽  
The Continuum

In this work, an equivalent continuum of a barrel gridshell is introduced. Constitutive identification procedures based on periodic homogenization are provided in the literature for this purpose, based on a flat Representative Element Volume (REV), notwithstanding that the geometry of the structures concerned is curved. Therefore, the novelty of the present study is the selection of a curved REV to obtain the equivalent elastic constants. The numerical validation of the identification procedure is made comparing gridshell response to that of the equivalent shell under homogeneous load conditions. Finally, in order to highlight the effect of the curved geometry on the constitutive law of the continuum, the response of the proposed model is also compared to that of a continuum obtained from a flat REV.

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.

Automated Image Denoising Model: Contribution Towards Optimized Internal and External Basis

2021 ◽  
pp. 2150051
Author(s):  
S. Elavaar Kuzhali ◽  
D. S. Suresh
Keyword(s):  
Image Denoising ◽  
Image Patch ◽  
The Past ◽  
Local Means ◽  
Hybrid Optimization Algorithm ◽  
Proposed Model ◽  
Processing Step ◽  
Non Local ◽  
Chicken Swarm Optimization ◽  
Selection Of

For handling digital images for various applications, image denoising is considered as a fundamental pre-processing step. Diverse image denoising algorithms have been introduced in the past few decades. The main intent of this proposal is to develop an effective image denoising model on the basis of internal and external patches. This model adopts Non-local means (NLM) for performing the denoising, which uses redundant information of the image in pixel or spatial domain to reduce the noise. While performing the image denoising using NLM, “denoising an image patch using the other noisy patches within the noisy image is done for internal denoising and denoising a patch using the external clean natural patches is done for external denoising”. Here, the selection of optimal block from the entire datasets including internal noisy images and external clean natural images is decided by a new hybrid optimization algorithm. The two renowned optimization algorithms Chicken Swarm Optimization (CSO), and Dragon Fly Algorithm (DA) are merged, and the new hybrid algorithm Rooster-based Levy Updated DA (RLU-DA) is adopted. The experimental results in terms of some relevant performance measures show the promising results of the proposed model with remarkable stability and high accuracy.

scholarly journals Topology Optimization and Performance Calculation for Control Arms of a Suspension

2014 ◽  
Vol 6 ◽  
pp. 734568 ◽  
Author(s):  
Liang Tang ◽  
Jie Wu ◽  
Jinhao Liu ◽  
Cuicui Jiang ◽  
Wen-Bin Shangguan
Keyword(s):  
Topology Optimization ◽  
Ride Comfort ◽  
Constitutive Law ◽  
Fea Model ◽  
Proposed Model ◽  
Rubber Bushing ◽  
And Performance ◽  
Motion Characteristics ◽  
Ball Joints ◽  
Performance Calculation

Control Arm (CA) of a suspension plays an important role in the automotive ride comfort and handling stability. In this paper, the topology optimization model including ball joints and bushing for topology optimization of an aluminium CA is established, where a ball joint is simplified as rigid elements and the elastic properties of a rubber bushing are estimated using Mooney-Rivlin constitutive law. A method for treating with multiple loads in topology optimization of CA is presented. Inertia relief theory is employed in the FEA model of the CA in order to simulate the large displacement motion characteristics of the CA. A CA is designed based on the topology optimization results, and the strength, natural frequency, and rigidity of the optimized CA are calculated. The calculated results show that the performances of the optimized CA with the proposed model meet the predetermined requirements.

scholarly journals A Proposed Heuristic Optimization Algorithm for Detecting Network Attacks

2019 ◽  
Vol 2 (4) ◽  
pp. 530
Author(s):  
Amr Hassan Yassin ◽  
Hany Hamdy Hussien
Keyword(s):  
Neural Network ◽  
Heuristic Algorithms ◽  
Feed Forward Neural Network ◽  
Data Set ◽  
Network Attacks ◽  
Security Issues ◽  
Proposed Model ◽  
Network Intrusions ◽  
Attack Patterns ◽  
Selection Of

Due to the exponential growth of E-Business and computing capabilities over the web for a pay-for-use groundwork, the risk factors regarding security issues also increase rapidly. As the usage increases, it becomes very difficult to identify malicious attacks since the attack patterns change. Therefore, host machines in the network must continually be monitored for intrusions since they are the final endpoint of any network. The purpose of this work is to introduce a generalized neural network model that has the ability to detect network intrusions. Two recent heuristic algorithms inspired by the behavior of natural phenomena, namely, the particle swarm optimization (PSO) and gravitational search (GSA) algorithms are introduced. These algorithms are combined together to train a feed forward neural network (FNN) for the purpose of utilizing the effectiveness of these algorithms to reduce the problems of getting stuck in local minima and the time-consuming convergence rate. Dimension reduction focuses on using information obtained from NSL-KDD Cup 99 data set for the selection of some features to discover the type of attacks. Detecting the network attacks and the performance of the proposed model are evaluated under different patterns of network data.

scholarly journals Profiling Suicide Exposure Risk Factors for Psychological Distress: An Empirical Test of the Proposed Continuum of Survivorship Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Navjot Bhullar ◽  
Rebecca L. Sanford ◽  
Myfanwy Maple
Keyword(s):  
Risk Factors ◽  
Psychological Distress ◽  
Latent Profile Analysis ◽  
Community Sample ◽  
Exposure Risk ◽  
Suicide Death ◽  
Proposed Model ◽  
Survivorship Model ◽  
The Continuum

The Continuum of Survivorship proposes a way in which individuals may experience the suicide death of someone known to them along a continuum from being exposed to the death through to long-term bereavement. The present study provides a first empirical testing of the proposed model in an Australian community sample exposed to suicide. Using a Latent Profile Analysis, we tested the suicide exposure risk factors (time since death, frequency of pre-death contact, reported closeness, and perceived impact) to map to the Continuum of Survivorship model. Results revealed identification of five profiles, with four ranging from suicide exposed to suicide bereaved long-term broadly aligning with the proposed model, with one further profile being identified that represented a discordant profile of low closeness and high impact of suicide exposure. Our findings demonstrate that while the proposed model is useful to better understand the psychological distress related to exposure to suicide, it cannot be used as “shorthand” for identifying those who will be most distressed, nor those who may most likely need additional support following a suicide death. Implications and future research directions are discussed.

A Comprehensive Energy Formulation for General Nonlinear Material Continua

1997 ◽  
Vol 64 (2) ◽  
pp. 353-360 ◽  
Author(s):  
A. Carini ◽  
O. De Donato
Keyword(s):  
Initial Boundary ◽  
Initial Boundary Value Problem ◽  
Small Strain ◽  
Constitutive Law ◽  
Nonlinear Material ◽  
Total Potential ◽  
Initial Boundary Value ◽  
Energy Formulation ◽  
The Continuum

By specialization to the continuum problem of a general formulation of the initial/boundary value problem for every nonpotential operator (Tonti, 1984) and by virtue of a suitable choice of the “integrating operator,” a comprehensive energy formulation is established. Referring to the small strain and displacement case in the presence of any inelastic generally nonlinear constitutive law, provided that it is differentiable, this formulation allows us to derive extensions of well-known principles of elasticity (Hu-Washizu, Hellinger-Reissner, total potential energy, and complementary energy). An illustrative example is given. Peculiar properties of the formulation are the energy characterization of the functional and the use of Green functions of the same problem in the elastic range for every inelastic, generally nonlinear material considered.

Organizing inter-firm project governance – a contextual model for empirical investigation

2018 ◽  
Vol 11 (1) ◽  
pp. 144-157 ◽  
Author(s):  
Simon von Danwitz
Keyword(s):  
Organization Theory ◽  
Contextual Factors ◽  
Project Performance ◽  
Future Research ◽  
Content Type ◽  
Project Governance ◽  
Proposed Model ◽  
Key Characteristics ◽  
Conceptual Paper ◽  
Selection Of

Purpose The management of major inter-firm projects requires a coherent, holistic governance framework to be effective. However, most existing models of project governance are limited to a narrow selection of contractual, structural or procedural aspects, and further neglect contextual factors, such as key characteristics of a project and its partners. The paper aims to discuss these issues. Design/methodology/approach This conceptual paper proposes an integrative analytical model of inter-firm project governance, building upon contingency theory and drawing from established constructs rooted in organization theory. Findings The paper aims to integrate two largely distinct streams of research and synthesize the respective constitutive dimensions of project governance into a coherent conceptual model. Further, interrelationships with contextual factors, such as project-related and partner-related characteristics, and project performance are discussed. Originality/value The proposed model purposefully merges two complementary streams of project governance research. As the model further provides clear contextual factors, it strengthens an emerging stream of project research by systematically examining external influences of project organizing. Future research may utilize this model and the suggested operationalization for each of the constructs as a basis to empirically investigate the design and effectiveness of governance regimes of major projects.

An Integrated Methodology for Evaluation of Electric Vehicles Under Sustainable Automotive Environment

2019 ◽  
pp. 41-62 ◽  
Author(s):  
Tapas Kumar Biswas ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Electric Vehicles ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Compromise Solution ◽  
Holistic Model ◽  
Proposed Model ◽  
Criteria Importance ◽  
Assessment Problems ◽  
Selection Of

In this chapter, a holistic model based on a newly developed combined compromise solution (CoCoSo) and criteria importance through intercriteria correlation (CRITIC) method for selection of battery-operated electric vehicles (BEVs) has been propounded. A sensitivity analysis has been performed to verify the robustness of the proposed model. Performance of the proposed model has also been compared with some of the popular MCDM methods. It is observed that the model has the competency of precisely ranking the BEV alternatives for the considered case study and can be applied to other sustainability assessment problems.

A Hybrid AHP-ELECTRE I Multicriteria Model for Performance Assessment and Team Selection

2017 ◽  
pp. 115-127
Author(s):  
Ikram Khatrouch ◽  
Lyes Kermad ◽  
Abderrahman el Mhamedi ◽  
Younes Boujelbene
Keyword(s):  
Human Resources ◽  
Decision Maker ◽  
Human Resources Management ◽  
Real Data ◽  
Assessment Model ◽  
Team Selection ◽  
Proposed Model ◽  
Electre I ◽  
Multicriteria Model ◽  
Selection Of

Human resources management is essential to any health care system. This paper proposes an assessment model to help the decision maker in the selection of an optimal team. In the proposed model, AHP method is applied to identify the weights of each criterion in the decision model. ELECTRE I method is used to obtain the best team that satisfies most of the decision maker preferences. We test the effectiveness of the model on the real data collected from the ‘Habib Bourguiba' Hospital in Tunisia.

Development of a new empirical method for Tunnel Squeezing Classification (TSC)

2020 ◽  
Vol 53 (4) ◽  
pp. 655-660 ◽  
Author(s):  
Hadi Farhadian ◽  
Arash Nikvar-Hassani
Keyword(s):  
Quality Index ◽  
Empirical Method ◽  
Point Of View ◽  
Geological Hazard ◽  
Case Histories ◽  
Proposed Model ◽  
Two Parameters ◽  
Classification Tool ◽  
Selection Of

The characterization of squeezing phenomena as a geological hazard is of great importance because squeezing has a crucial role in the selection of the route and type of tunnels and in the characteristics of the excavation device. Tunnel squeezing is also the basis for the designation and construction of tunnelling-related structures. We present a new tunnel squeezing classification tool to predict tunnel squeezing based on two parameters: Q, the tunnelling quality index; and H, the depth of the tunnel. We used data collected from published papers to train the model; these data included 225 case histories from different countries, including Andorra, India, Iran, Japan, Nepal, Spain, Turkey and Venezuela. Validation of the model indicated that our tunnel squeezing classification tool is more accurate than the speculative and analytical methods currently in use. The proposed model will help tunnelling experts to classify tunnelling media from the point of view of squeezing hazards.

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