The Experts below are selected from a list of 20997 Experts worldwide ranked by ideXlab platform
N J Uhure - One of the best experts on this subject based on the ideXlab platform.
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Diamondlike carbon coatings for Tribology: production techniques, characterization methods and applications
2016Co-Authors: Sarah V Hainsworth, N J UhureAbstract:There are numerous types of surface coatings available to engineers in order to improve the friction and wear resistance of components. In order to successfully use these coatings in practice, it is important to understand the different types of coatings available, and the factors that control their mechanical and tribological properties. This paper will focus on the application of diamond-like carbon (DLC) coatings in tribological applications. Thus far, DLC coatings have found broad industrial application, particularly in optical and electronic areas. In tribological applications, DLC coatings are now being used successfully as coatings for ball bearings where they decrease the friction coefficient between the ball and race, in shaving applications where they increase the life of Razor Blades in wet shaving applications, and increasingly in automotive applications such as racing engines and standard production vehicles. The structure and mechanical properties of DLC coatings are dependent on the deposition method and the incorporation of additional elements such as nitrogen, hydrogen, silicon and metal dopants. These additional elements control the hardness of the resultant film, the level of residual stress and the tribological properties. As diamond-like carbon films increasingly become adopted for use in industry, it is important to review the factors that control their 2 of 42 DLC Review properties, and thus, the ultimate performance of these coated components in practical tribological applications
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diamond like carbon coatings for tribology production techniques characterisation methods and applications
International Materials Reviews, 2007Co-Authors: Sarah V Hainsworth, N J UhureAbstract:AbstractThe application of diamond like carbon (DLC) coatings in tribological applications, the range of deposition methods employed and techniques for characterising the structure and properties of the films produced are reviewed. Thus far, DLC coatings have found broad industrial application, particularly in optical and electronic areas. In tribological applications, DLC coatings are used successfully as coatings for ball bearings where they decrease the friction coefficient between the ball and race; in shaving applications where they increase the life of Razor Blades in wet shaving applications; and increasingly in automotive applications such as racing engines and standard production vehicles. The structure and mechanical properties of DLC coatings are dependent on the deposition method and the incorporation of additional elements such as nitrogen, hydrogen, silicon and metal dopants. These additional elements control the hardness of the resultant film, the level of residual stress and the tribologic...
Domingo Mery - One of the best experts on this subject based on the ideXlab platform.
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Detection of threat objects in baggage inspection with X-ray images using deep learning
Neural Computing and Applications, 2020Co-Authors: Daniel Saavedra, Sandipan Banerjee, Domingo MeryAbstract:In the field of security, baggage-screening with X-rays is used as nondestructive testing for threat object detection. This is a common protocol when inspecting passenger baggage particularly at airports. Unfortunately, the accuracy of such human inspection is around 80–90%, under optimal operator conditions. For this reason, it is quite necessary to assist human inspectors with the aid of computer vision algorithms. This work proposes a deep learning-based methodology designed to detect threat objects in (single spectrum) X-ray baggage scan images. For this purpose, our proposed framework simulates a large number of X-ray images, using a combination of PGGAN (Karras et al. in International conference on learning representations, 2018. https://openreview.net/forum?id=Hk99zCeAb ) and superimposition (Mery and Katsaggelos in 2017 IEEE conference on computer vision and pattern recognition workshops (CVPRW), 2017. https://doi.org/10.1109/CVPRW.2017.37 ) strategies, that are used to train state-of-the-art detection models such as YOLO (Redmon et al. in You only look once: unified, real-time object detection. CoRR abs/1506.02640, 2015. http://arxiv.org/ abs/1506.02640 ), SSD (Liu et al. in SSD: single shot multibox detector. CoRR abs/1512.02325, 2015. http://arxiv. org/abs/1512.02325 ) and RetinaNet (Lin et al. in Focal loss for dense object detection. CoRR abs/1708.02002, 2017. http://arxiv.org/abs/1708.02002 ). Our method has been tested on real X-ray images in the detection of four categories of threat objects: guns, knives, Razor Blades and shuriken (ninja stars). In our experiments, YOLOv3 (Redmon and Farhadi in Yolov3: An incremental improvement. CoRR abs/1804.02767, 2018. http://arxiv.org/abs/1804.02767 ) obtained the best mean average precision (mAP) with 96.3% for guns, 76.2% for knives, 86.9% for Razor Blades and 93.7% for shuriken, while the average mAP for all threat objects was 80.0%. We believe the effectiveness of our method in the detection of threat objects makes its use in checkpoints possible. Moreover, our methodology is scalable and can be easily extended to detect other categories automatically.
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Threat Objects Detection in X-ray Images Using an Active Vision Approach
Journal of Nondestructive Evaluation, 2017Co-Authors: Vladimir Riffo, Sebastian Flores, Domingo MeryAbstract:X-ray testing for baggage inspection has been increasingly used at airports, reducing the risk of terrorist crimes and attacks. Nevertheless, this task is still being carried out by human inspectors and with limited technological support. The technology that is being used is not always effective, as it depends mainly on the position of the object of interest, occlusion, and the accumulated experience of the inspector. Due to this problem, we have developed an approach that inspects X-ray images using active vision in order to automatically detect objects that represent a threat. Our method includes three steps: detection of potential threat objects in single views based on the similarity of features and spatial distribution; estimation of the best-next-view using Q-learning; and elimination of false alarms based on multiple view constraints. We tested our algorithm on X-ray images that included handguns and Razor Blades. In the detection of handguns we registered good results for recall and precision ( Re = 67%, Pr = 83%) along with a high performance in the detection of Razor Blades ( Re = 82%, Pr = 100%) taking into consideration 360 inspections in each case. Our results indicate that non-destructive inspection actively using X-ray images, leads to more effective object detection in complex environments, and helps to offset certain levels of occlusion and the internal disorder of baggage.
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Automated X-ray object recognition using an efficient search algorithm in multiple views
2016Co-Authors: Domingo Mery, Vladimir Riffo, Irene Zuccar, Christian PieringerAbstract:In order to reduce the security risk of a commercial air-craft, passengers are not allowed to take certain items in their carry-on baggage. For this reason, human operators are trained to detect prohibited items using a manually con-trolled baggage screening process. In this paper, we pro-pose the use of an automated method based on multiple X-ray views to recognize certain regular objects with highly defined shapes and sizes. The method consists of two steps: ‘monocular analysis’, to obtain possible detections in each view of a sequence, and ‘multiple view analysis’, to rec-ognize the objects of interest using matchings in all views. The search for matching candidates is efficiently performed using a lookup table that is computed off-line. In order to illustrate the effectiveness of the proposed method, experi-mental results on recognizing regular objects –clips, springs and Razor Blades – in pen cases are shown achieving around 93 % accuracy for 120 objects. We believe that it would be possible to design an automated aid in a target detection task using the proposed algorithm. 1
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1Automated Detection of Threat Objects Using Adapted Implicit Shape Model
2016Co-Authors: Vladimir Riffo, Domingo MeryAbstract:Abstract—Baggage inspection using X-ray screening is a pri-ority task that reduces the risk of crime and terrorist attacks. Manual detection of threat items is tedious because very few bags actually contain threat items and the process requires a high degree of concentration. An automated solution would be a welcome development in this field. We propose a methodology for automatic detection of threat objects using single X-ray images. Our approach is an adaptation of a methodology originally created for recognizing objects in photographs based on Implicit Shape Models. Our detection method uses a visual vocabulary and an occurrence structure generated from a training dataset that contains representative X-ray images of the threat object to be detected. Our method can be applied to single views of grayscale X-ray images obtained using a single energy acquisition system. We tested the effectiveness of our method for the detection of three different threat objects: Razor Blades, shuriken (ninja stars) and handguns. The testing dataset for each threat object consisted of 200 X-ray images of bags. The true positive and false positive rates (TPR, FPR) are: (0.99, 0.02) for Razor Blades, (0.97, 0.06) for shuriken and (0.89, 0.18) for handguns. If other representative training datasets were utilized, we believe that our methodology could aid in the detection of other kinds of threat objects. Index Terms—Object categorization; object recognition; object detection; implicit shape model; X-ray testing; baggage screen-ing; threat objects. I
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Detection of Regular Objects in Baggages Using Multiple X-ray Views
2016Co-Authors: Domingo Mery, Vladimir Riffo, German Mondragon, Irene ZuccarAbstract:In order to reduce the security risk of a commercial aircraft, passengers are not allowed to take certain items in carry-on baggage. For this reason, human operators are trained to detect prohibited items using a manually controlled baggage screening process. In this paper, we propose the use of a method based on multiple X-ray views to detect some regular prohibited items with very defined shapes and sizes. The method consists of two steps: ‘structure estimation’, to obtain a geometric model of the multiple views from the object to be inspected (a baggage), and ‘parts detection’, to detect the parts of interest (prohibited items). The geometric model is estimated using a structure from motion algorithm. The detection of the parts of interest is performed by an ad-hoc segmentation algorithm (object dependent) followed by a general tracking algorithm based on geometric and appearance constraints. In order to illustrate the effectiveness of the proposed method, experimental results on detecting regular objects −Razor Blades and guns − are shown yielding promising results
Jonatha R Medverd - One of the best experts on this subject based on the ideXlab platform.
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digital tomosynthesis for detection of ingested foreign objects in the emergency department a case of Razor blade ingestion
Emergency Radiology, 2019Co-Authors: Maham Jehangi, Christophe Mallory, Jonatha R MedverdAbstract:A 46-year-old schizophrenic male presented to the emergency department (ED) after deliberate ingestion of an undetermined number of open Razor Blades. Abdominal radiograph revealed one Razor blade but raised suspicion of a second blade which was subsequently confirmed by digital tomosynthesis (DTS), seen as two Razor Blades superimposed upon each other placed at slightly different angles. A careful search was made during endoscopy and the two Razor Blades were retrieved from the stomach and duodenum, respectively. This case illustrates the use of digital tomosynthesis as a smart, timely, cost-effective, and low-dose alternative to conventional computed tomography (CT) that can be conveniently employed in the ED for foreign body localization.
Ohio. Office Of Inspector General - One of the best experts on this subject based on the ideXlab platform.
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Other title: Ohio Department of Rehabilitation & Correction; Other title: Ohio Department of Rehabilitation and Correction
2018Co-Authors: Ohio. Office Of Inspector GeneralAbstract:"Date of report: May 22, 2018."On August 9, 2016, the Office of the Ohio Inspector General was notified that Marion Correctional Institution (MCI) inmate David Dean, during an interview with an Ohio Department of Rehabilitation and Correction (ODRC) investigator, disclosed the location of prison contraband, including a hidden computer hard drive, Razor Blades, drill bits, and miscellaneous tools. These items were concealed inside an HP8000 printer in the Ohio Penal Industries (OPI) area of MCI. Dean claimed MCI-OPI staff instructed him to keep the contraband items in his work area " ... to keep them safe." Dean also claimed the hard drive contained thousands of dollars' worth of software programs illegally obtained
Sarah V Hainsworth - One of the best experts on this subject based on the ideXlab platform.
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Diamondlike carbon coatings for Tribology: production techniques, characterization methods and applications
2016Co-Authors: Sarah V Hainsworth, N J UhureAbstract:There are numerous types of surface coatings available to engineers in order to improve the friction and wear resistance of components. In order to successfully use these coatings in practice, it is important to understand the different types of coatings available, and the factors that control their mechanical and tribological properties. This paper will focus on the application of diamond-like carbon (DLC) coatings in tribological applications. Thus far, DLC coatings have found broad industrial application, particularly in optical and electronic areas. In tribological applications, DLC coatings are now being used successfully as coatings for ball bearings where they decrease the friction coefficient between the ball and race, in shaving applications where they increase the life of Razor Blades in wet shaving applications, and increasingly in automotive applications such as racing engines and standard production vehicles. The structure and mechanical properties of DLC coatings are dependent on the deposition method and the incorporation of additional elements such as nitrogen, hydrogen, silicon and metal dopants. These additional elements control the hardness of the resultant film, the level of residual stress and the tribological properties. As diamond-like carbon films increasingly become adopted for use in industry, it is important to review the factors that control their 2 of 42 DLC Review properties, and thus, the ultimate performance of these coated components in practical tribological applications
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diamond like carbon coatings for tribology production techniques characterisation methods and applications
International Materials Reviews, 2007Co-Authors: Sarah V Hainsworth, N J UhureAbstract:AbstractThe application of diamond like carbon (DLC) coatings in tribological applications, the range of deposition methods employed and techniques for characterising the structure and properties of the films produced are reviewed. Thus far, DLC coatings have found broad industrial application, particularly in optical and electronic areas. In tribological applications, DLC coatings are used successfully as coatings for ball bearings where they decrease the friction coefficient between the ball and race; in shaving applications where they increase the life of Razor Blades in wet shaving applications; and increasingly in automotive applications such as racing engines and standard production vehicles. The structure and mechanical properties of DLC coatings are dependent on the deposition method and the incorporation of additional elements such as nitrogen, hydrogen, silicon and metal dopants. These additional elements control the hardness of the resultant film, the level of residual stress and the tribologic...
