Asphaltic Material in the Context of Generalized Porothermoelasticity

Mohammad H. Alawi

College of engineering and Islamic architecture, p.o.box:7398 Makkah, Saudi Arabia

ABSTRACT

In this work, a mathematical model of generalized porothermoelasticity with one relaxation time for poroelastic half-space saturated with fluid will be constructed in the context of Youssef model (2007). We will obtain the general solution in the Laplace transform domain and apply it in a certain asphalt material which is thermally shocked on its bounding plane. The inversion of the Laplace transform will be obtained numerically and the numerical values of the temperature, stresses, strains and displacements will be illustrated graphically for the solid and the liquid.

KEY-WORDS:

Porothermoelasticity; asphaltic Material; Thermal shock. 

ORIGINAL SOURCE URL: https://aircconline.com/ijsc/V8N1/8117ijsc03.pdf

http://airccse.org/journal/ijsc/current2017.html

Call for Papers - International Journal on Soft Computing ( IJSC )

 

ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]

http://airccse.org/journal/ijsc/ijsc.html

 

Scope & Topics

Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field

Topics considered include but are not limited to: 

●        Fuzzy Systems ●        Neural Networks ●        Machine learning ●        Probabilistic Reasoning ●        Evolutionary Computing ●        Pattern recognition ●        Hybrid intelligent systems, ●        Software agents ●        Morphic Computing ●        Image processing, ●        E-commerce, e-medicine

●        Rough Sets ●        Symbolic machine learning, ●        Wavelet ●        Signal or Image Processing ●        Vision Recognition ●        Biomedical Engineering ●        Telecommunications ●        Reactive Distributed AI ●        Nano & Micro-systems ●        Data Visualization

Paper Submission

Authors are invited to submit papers for this journal through E-mail: ijsc@aircconline.com or through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

Important Dates 

Submission Deadline : May 22, 2021

 Notification                 : June 22, 2021

 Final Manuscript Due : June 30, 2021

Publication Date          : Determined by the Editor-in-Chief

Contact Us

Here's where you can reach us : ijscjournal@yahoo.com or ijsc@aircconline.com Submission System 

http://coneco2009.com/submissions/imagination/home.html

Google scholar link: https://scholar.google.co.in/citations?user=4BpotHUAAAAJ&hl=en

BFO – AIS: A Framework for Medical Image Classification Using Soft Computing Techniques

D. Chitra and M. Karthikeyan

Assistant Professor, Dept. of Computer Science, Govt. Arts College (A), Salem-7, Tamil Nadu, India

ABSTRACT

Medical images provide diagnostic evidence/information about anatomical pathology. The growth in database is enormous as medical digital image equipment’s like Magnetic Resonance Images (MRI), Computed Tomography (CT), and Positron Emission Tomography CT (PET-CT) are part of clinical work. CT images distinguish various tissues according to gray levels to help medical diagnosis. Ct is more reliable for early tumours and haemorrhages detection as it provides anatomical information to plan radio therapy. Medical information systems goals are to deliver information to right persons at the right time and place to improve care process quality and efficiency. This paper proposes an Artificial Immune System (AIS) classifier and proposed feature selection based on hybrid Bacterial Foraging Optimization (BFO) with Local Search (LS) for medical image classification.

KEYWORDS

Computed Tomography (CT), Feature Selection, Artificial immune classifier, Correlation based Feature Selection (CFS), Bacterial Foraging Optimization (BFO), Local Search (LS) 

Original Source URL: https://aircconline.com/ijsc/V8N1/8117ijsc02.pdf

http://airccse.org/journal/ijsc/current2017.html