scholarly journals An Overview of Trust Models and Proposal of New Model Based on Reputation for Resource Selection in Grid Computing

2010 ◽  
Vol 2 (4) ◽  
pp. 387-389 ◽  
Author(s):  
Vivekananth. P
Keyword(s):  
Grid Computing ◽  
Resource Selection ◽  
New Model ◽  
Model Based ◽  
Trust Models

Bovine Serum Albumin Adsorption onto Colloidal Al2O3Particles:  A New Model Based on Zeta Potential and UV−Vis Measurements

Langmuir ◽  
2004 ◽  
Vol 20 (23) ◽  
pp. 10055-10061 ◽  
Author(s):  
Kurosch Rezwan ◽  
Lorenz P. Meier ◽  
Mandana Rezwan ◽  
Janos Vörös ◽  
Marcus Textor ◽  
...  
Keyword(s):  
Bovine Serum Albumin ◽  
Zeta Potential ◽  
Serum Albumin ◽  
Bovine Serum ◽  
New Model ◽  
Model Based ◽  
Bovine Serum Albumin Adsorption ◽  
Albumin Adsorption

scholarly journals An Improved Image Denoising Model Based on Nonlocal Means Filter

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yan Jin ◽  
Wenyu Jiang ◽  
Jianlong Shao ◽  
Jin Lu
Keyword(s):  
Image Denoising ◽  
Natural Images ◽  
Nonlocal Means ◽  
New Model ◽  
Model Based ◽  
Better Than

The nonlocal means filter plays an important role in image denoising. We propose in this paper an image denoising model which is a suitable improvement of the nonlocal means filter. We compare this model with the nonlocal means filter, both theoretically and experimentally. Experiment results show that this new model provides good results for image denoising. Particularly, it is better than the nonlocal means filter when we consider the denoising for natural images with high textures.

New Model of a Basin-Type Solar Still

2002 ◽  
Vol 124 (3) ◽  
pp. 311-314 ◽  
Author(s):  
Irene De Paul
Keyword(s):  
Flow Visualization ◽  
Physical Model ◽  
Thermal Inertia ◽  
Thermal Conditions ◽  
Salt Deposit ◽  
Solar Still ◽  
New Model ◽  
Model Based ◽  
Productivity Measurements ◽  
Real Scale

Thermal and productivity measurements and flow visualization experiences were performed on a real scale module of a basin type solar still, whose geometry and thermal conditions could be changed in a controlled way. The convective stage was studied with the aim of acquiring information about the nature of the medium inside it and the influence of different parameters over the productivity. Literature shows a great number of experimental and numerical works dealing with different aspects of the performance of solar stills: thermal losses, vapor losses, salt deposit on the tray, geometry, thermal inertia, etc. Few works are reported that take into account convective phenomena and the fluiddynamic characteristics of the medium inside the still. Most of these works are based on Dunkle’s and Copper’s models of the still that does not take into account the characteristics of the environment. A new physical model based on these experiments is presented.

Grid Resource Allocation with Genetic Algorithm Using Population Based on Multisets

2017 ◽  
Vol 26 (1) ◽  
pp. 169-184 ◽  
Author(s):  
Absalom E. Ezugwu ◽  
Nneoma A. Okoroafor ◽  
Seyed M. Buhari ◽  
Marc E. Frincu ◽  
Sahalu B. Junaidu
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Grid Computing ◽  
Resource Selection ◽  
Computing System ◽  
Population Based ◽  
Fine Tuning ◽  
Grid Resource ◽  
Performance Results ◽  
Grid Resources

AbstractThe operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of genetic algorithm (GA) using populations based on multisets is made. Furthermore, the paper presents a hybrid GA-based scheduling framework that efficiently searches for the best available resources for user jobs in a typical grid computing environment. For the proposed resource allocation method, additional mechanisms (populations based on multiset and adaptive matching) are introduced into the GA components to enhance their search capability in a large problem space. Empirical study is presented in order to demonstrate the importance of operator improvement on traditional GA. The preliminary performance results show that the proposed introduction of an additional operator fine-tuning is efficient in both speed and accuracy and can keep up with high job arrival rates.

A new model-based framework for lung tissue segmentation in three-dimensional thoracic CT images

2017 ◽  
Vol 12 (2) ◽  
pp. 339-346 ◽  
Author(s):  
Zeinab Naseri Samaghcheh ◽  
Fatemeh Abdoli ◽  
Hamid Abrishami Moghaddam ◽  
Mohammadreza Modaresi ◽  
Neda Pak
Keyword(s):  
Lung Tissue ◽  
Three Dimensional ◽  
Ct Images ◽  
Tissue Segmentation ◽  
New Model ◽  
Model Based ◽  
Thoracic Ct

Developing a new model based on neuro-fuzzy system for predicting roof fall in coal mines

2012 ◽  
Vol 23 (S1) ◽  
pp. 129-137 ◽  
Author(s):  
Mohammad Farid ◽  
Mehdi Mohamadi HosseinAbadi ◽  
Abdolreza Yazdani-Chamzini ◽  
Siamak Haji Yakhchali ◽  
Mohammad Hossein Basiri
Keyword(s):  
Fuzzy System ◽  
Coal Mines ◽  
New Model ◽  
Model Based ◽  
Neuro Fuzzy ◽  
Roof Fall

scholarly journals Towards an Automated Model-Based Test Generation Approach from Controlled Natural Language Specifications Written in Arabic

2021 ◽  
Author(s):  
Moez Krichen ◽  
Seifeddine Mechti
Keyword(s):  
Natural Language ◽  
Test Generation ◽  
Arabic Language ◽  
Test Cases ◽  
New Model ◽  
Controlled Natural Language ◽  
Model Based ◽  
Case Grammar ◽  
Model Based Testing ◽  
Testing Approach

<div>We propose a new model-based testing approach which takes as input a set of requirements described in Arabic Controlled Natural Language (CNL) which is a subset of the Arabic language generated by a specific grammar. The semantics of the considered requirements is defined using the Case Grammar Theory (CTG). The requirements are translated into Transition Relations which serve as an input for test cases generation tools.</div>

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