Incorporating the inspection process into a software maintenance organization

Author(s):  
R.J. Kosman ◽  
T.J. Restivo
Author(s):  
Lindsay Johnson ◽  
Marsha B. Keune ◽  
Jennifer Winchel
Keyword(s):  

2019 ◽  
Vol 14 (4) ◽  
pp. 305-313 ◽  
Author(s):  
Suresh Chandra Satapathy ◽  
Steven Lawrence Fernandes ◽  
Hong Lin

Background: Stroke is one of the major causes for the momentary/permanent disability in the human community. Usually, stroke will originate in the brain section because of the neurological deficit and this kind of brain abnormality can be predicted by scrutinizing the periphery of brain region. Magnetic Resonance Image (MRI) is the extensively considered imaging procedure to record the interior sections of the brain to support visual inspection process. Objective: In the proposed work, a semi-automated examination procedure is proposed to inspect the province and the severity of the stroke lesion using the MRI. associations while known disease-lncRNA associations are required only. Method: Recently discovered heuristic approach called the Social Group Optimization (SGO) algorithm is considered to pre-process the test image based on a chosen image multi-thresholding procedure. Later, a chosen segmentation procedure is considered in the post-processing section to mine the stroke lesion from the pre-processed image. Results: In this paper, the pre-processing work is executed with the well known thresholding approaches, such as Shannon’s entropy, Kapur’s entropy and Otsu’s function. Similarly, the postprocessing task is executed using most successful procedures, such as level set, active contour and watershed algorithm. Conclusion: The proposed procedure is experimentally inspected using the benchmark brain stroke database known as Ischemic Stroke Lesion Segmentation (ISLES 2015) challenge database. The results of this experimental work authenticates that, Shannon’s approach along with the LS segmentation offers superior average values compared with the other approaches considered in this research work.</P>


Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 90-92
Author(s):  
Kae Doki ◽  
Yuki Funabora ◽  
Shinji Doki

Every day we are seeing an increasing number of robots being employed in our day-to-day lives. They are working in factories, cleaning our houses and may soon be chauffeuring us around in vehicles. The affordability of drones too has come down and now it is conceivable for most anyone to own a sophisticated unmanned aerial vehicle (UAV). While fun to fly, these devices also represent powerful new tools for several industries. Anytime an aerial view is needed for a planning, surveillance or surveying, for example, a UAV can be deployed. Further still, equipping these vehicles with an array of sensors, for climate research or mapping, increases their capability even more. This gives companies, governments or researchers a cheap and safe way to collect vast amounts of data and complete tasks in remote or dangerous areas that were once impossible to reach. One area UAVs are proving to be particularly useful is infrastructure inspection. In countries all over the world large scale infrastructure projects like dams and bridges are ageing and in need of upkeep. Identifying which ones and exactly where they are in need of patching is a huge undertaking. Not only can this work be dangerous, requiring trained inspectors to climb these megaprojects, it is incredibly time consuming and costly. Enter the UAVs. With a fleet of specially equipped UAVs and a small team piloting them and interpreting the data they bring back the speed and safety of this work increases exponentially. The promise of UAVs to overturn the infrastructure inspection process is enticing, but there remain several obstacles to overcome. One is achieving the fine level of control and positioning required to navigate the robots around 3D structures for inspection. One can imagine that piloting a small UAV underneath a huge highway bridge without missing a single small crack is quite difficult, especially when the operators are safely on the ground hundreds of meters away. To do this knowing exactly where the vehicle is in space becomes a critical variable. The job can be made even easier if a flight plan based on set waypoints can be pre-programmed and followed autonomously by the UAV. It is exactly this problem that Dr Kae Doki from the Department of Electrical Engineering at Aichi Institute of Technology, and collaborators are focused on solving.


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