scholarly journals Image analysis application in metallurgical engineering and quality control

2009 ◽  
Author(s):  
Z. Odanović ◽  
M. Djurdjević ◽  
G. Byczynski ◽  
B. Katavić ◽  
V. Grabulov
Keyword(s):  
Quality Control ◽  
Image Analysis ◽  
Metallurgical Engineering ◽  
Analysis Application

Combinatorial Double Auction Based Meta-scheduler for Medical Image Analysis Application in Grid Environment

2020 ◽  
Vol 13 (5) ◽  
pp. 999-1007
Author(s):  
Karthikeyan Periyasami ◽  
Arul Xavier Viswanathan Mariammal ◽  
Iwin Thanakumar Joseph ◽  
Velliangiri Sarveshwaran
Keyword(s):  
Image Analysis ◽  
Medical Image ◽  
Medical Image Analysis ◽  
Grid Resource ◽  
Resource Broker ◽  
Analysis Application ◽  
Local Grid ◽  
Grid Resource Broker ◽  
Global Grid ◽  
Grid Site

Background: Medical image analysis application has complex resource requirement. Scheduling Medical image analysis application is the complex task to the grid resources. It is necessary to develop a new model to improve the breast cancer screening process. Proposed novel Meta scheduler algorithm allocate the image analyse applications to the local schedulers and local scheduler submit the job to the grid node which analyses the medical image and generates the result sent back to Meta scheduler. Meta schedulers are distinct from the local scheduler. Meta scheduler and local scheduler have the aim at resource allocation and management. Objective: The main objective of the CDAM meta-scheduler is to maximize the number of jobs accepted. Methods: In the beginning, the user sends jobs with the deadline to the global grid resource broker. Resource providers sent information about the available resources connected in the network at a fixed interval of time to the global grid resource broker, the information such as valuation of the resource and number of an available free resource. CDAM requests the global grid resource broker for available resources details and user jobs. After receiving the information from the global grid resource broker, it matches the job with the resources. CDAM sends jobs to the local scheduler and local scheduler schedule the job to the local grid site. Local grid site executes the jobs and sends the result back to the CDAM. Success full completion of the job status and resource status are updated into the auction history database. CDAM collect the result from all local grid site and return to the grid users. Results: The CDAM was simulated using grid simulator. Number of jobs increases then the percentage of the jobs accepted also decrease due to the scarcity of resources. CDAM is providing 2% to 5% better result than Fair share Meta scheduling algorithm. CDAM algorithm bid density value is generated based on the user requirement and user history and ask value is generated from the resource details. Users who, having the most significant deadline are generated the highest bid value, grid resource which is having the fastest processor are generated lowest ask value. The highest bid is assigned to the lowest Ask it means that the user who is having the most significant deadline is assigned to the grid resource which is having the fastest processor. The deadline represents a time by which the user requires the result. The user can define the deadline by which the results are needed, and the CDAM will try to find the fastest resource available in order to meet the user-defined deadline. If the scheduler detects that the tasks cannot be completed before the deadline, then the scheduler abandons the current resource, tries to select the next fastest resource and tries until the completion of application meets the deadline. CDAM is providing 25% better result than grid way Meta scheduler this is because grid way Meta scheduler allocate jobs to the resource based on the first come first served policy. Conclusion: The proposed CDAM model was validated through simulation and was evaluated based on jobs accepted. The experimental results clearly show that the CDAM model maximizes the number of jobs accepted than conventional Meta scheduler. We conclude that a CDAM is highly effective meta-scheduler systems and can be used for an extraordinary situation where jobs have a combinatorial requirement.

scholarly journals Author Correction: Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julian Bär ◽  
Mathilde Boumasmoud ◽  
Roger D. Kouyos ◽  
Annelies S. Zinkernagel ◽  
Clément Vulin
Keyword(s):  
Image Analysis ◽  
Growth Dynamics ◽  
Colony Growth ◽  
Automated Image Analysis ◽  
Analysis Application

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Validation of a new image analysis procedure for quantifying filamentous bacteria in activated sludge

2014 ◽  
Vol 70 (6) ◽  
pp. 955-963 ◽  
Author(s):  
Ewa Liwarska-Bizukojc ◽  
Marcin Bizukojc ◽  
Olga Andrzejczak
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Activated Sludge ◽  
Analysis Procedure ◽  
Automated Image Analysis ◽  
Filamentous Bacteria ◽  
Image Processing And Analysis ◽  
Manual Counting ◽  
Analysis Application ◽  
Activated Sludge Systems

Quantification of filamentous bacteria in activated sludge systems can be made by manual counting under a microscope or by the application of various automated image analysis procedures. The latter has been significantly developed in the last two decades. In this work a new method based upon automated image analysis techniques was elaborated and presented. It consisted of three stages: (a) Neisser staining, (b) grabbing of microscopic images, and (c) digital image processing and analysis. This automated image analysis procedure possessed the features of novelty. It simultaneously delivered data about aggregates and filaments in an individual calculation routine, which is seldom met in the procedures described in the literature so far. What is more important, the macroprogram performing image processing and calculation of morphological parameters was written in the same software which was used for grabbing of images. Previously published procedures required using two different types of software, one for image grabbing and another one for image processing and analysis. Application of this new procedure for the quantification of filamentous bacteria in the full-scale as well as laboratory activated sludge systems proved that it was simple, fast and delivered reliable results.

scholarly journals Development of a Quality Control Tool for Mass Target Image Analysis of Phantoms for Breast Ultrasonography

2013 ◽  
Vol 22 (2) ◽  
pp. 336-342
Author(s):  
Norimitsu Shinohara ◽  
Naoki Kamiya ◽  
Ayumi Wada ◽  
Takako Morita
Keyword(s):  
Quality Control ◽  
Image Analysis ◽  
Target Image ◽  
Breast Ultrasonography ◽  
Quality Control Tool ◽  
Control Tool

scholarly journals Development and Calibration of a Quantitative, Automated Mineralogical Assessment Method Based on SEM-EDS and Image Analysis: Application for Fine Tailings

2011 ◽  
Vol 10 (12) ◽  
pp. 1111-1130 ◽  
Author(s):  
R. Mermillod-Blondin ◽  
M. Benzaazoua ◽  
M. Kongolo ◽  
P. de Donato ◽  
B. Bussière ◽  
...  
Keyword(s):  
Image Analysis ◽  
Assessment Method ◽  
Fine Tailings ◽  
Analysis Application

Bioinformatics-Inspired Algorithms for 2D-Image Analysis-Application to Synthetic and Medical Images Part I

2012 ◽  
Vol 1 (1) ◽  
pp. 14-38
Author(s):  
Perambur S. Neelakanta ◽  
Deepti Pappusetty
Keyword(s):  
Image Analysis ◽  
Medical Images ◽  
Synthetic Image ◽  
Local Alignment ◽  
Brain Scan ◽  
Analysis Application ◽  
Binary Correlation ◽  
Global And Local ◽  
The Brain ◽  
2D Images

To ascertain specific features in bio-/medical-images, a new avenue of using the so-called Needleman-Wunsch (NW) and Smith-Waterman (SW) algorithms (of bioinformatics) is indicated. In general, NW/SW algorithms are adopted in genomic science to obtain optimal (global and local) alignment of two linear sequences (like DNA nucleotide bases) to determine the similarity features between them and such 1D-sequence algorithms are presently extended to compare 2D-images via binary correlation. The efficacy of the proposed method is tested with synthetic images and a brain scan image. Thus, the way of finding the location of a distinct part in a synthetic image and that of a tumour in the brain scan image is demonstrated.

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