Quality Assessment of Additively Manufactured Fiducial Markers to Support Augmented Reality-Based Part Inspection

Author(s):  
Jayant Mathur ◽  
Saurabh Basu ◽  
Jessica Menold ◽  
Nicholas A. Meisel

Abstract This paper proposes an augmented reality (AR) framework and tool on smartphones as an alternative to conventional inspection for AM parts. The framework attempts to introduce the rapid inspection potential of smartphone based AR within manufacturing by leveraging the manufacturing capability of additive manufacturing (AM) to integrate markers onto AM parts. The key step from this framework that is explored in this paper is the design and quality assessment of AM markers for marker registration. As part of the marker design and quality assessment objectives, this research conducts an evaluation on the effects of different AM processes on the quality of augmentation achieved from AM fiducial markers. Furthermore, it evaluates the minimum fiducial pattern size that on integration onto AM parts will be viable for augmentation. The results suggest that the AM process and the size of the fiducial pattern play a significant role in determining the quality of the AM markers. The paper concludes by stating that dual material extrusion AM markers provide the highest number of detectable features and therefore the highest quality of AM markers, and the smallest viable fiducial pattern for Cybercode/QR code marker can be sized at 19 × 19mm2.

2021 ◽  
Author(s):  
Jayant Mathur ◽  
Saurabh Basu ◽  
Jessica Menold ◽  
Nicholas Meisel

Author(s):  
Svetlana V. Savkina

The article presents the results of testing the complex methodology of assessment of quality of electronic books exhibitions (EBE). The author describes the project of the expert system, allowing to implement the EBE assessment without the experts’ participation. There is given the comparison of the results of assessments, carried out by experts and by the expert system.


Author(s):  
В.Г. Антоненко ◽  
Н.В. Шилова ◽  
Е.Н. Лукаш ◽  
Э.Р. Бабкеева ◽  
В.Н. Малахов

Представлены результаты экспертной оценки качества цитогенетических исследований в лабораториях РФ в системе межлабораторных сличительных испытаний «ФСВОК» в 2018-2019 гг. Обсуждаются наиболее частые причины неудовлетворительных результатов экспертизы и возможные пути улучшения качества цитогенетических исследований. We report the results of quality assessment for preparation of cytogenetic slides and chromosomal analysis in the laboratories of Russian Federation in the system of the interlaboratory comparative examinations “FSVOK” in 2018-2019. Common causes of poor results of assessment and the ways for improvement of quality for cytogenetic investigations are discussed.


2017 ◽  
pp. 139-145
Author(s):  
R. I. Hamidullin ◽  
L. B. Senkevich

A study of the quality of the development of estimate documentation on the cost of construction at all stages of the implementation of large projects in the oil and gas industry is conducted. The main problems that arise in construction organizations are indicated. The analysis of the choice of the perfect methodology of mathematical modeling of the investigated business process for improving the activity of budget calculations, conducting quality assessment of estimates and criteria for automation of design estimates is performed.


Author(s):  
Тетяна Грунтова ◽  
Юлія Єчкало ◽  
Андрій Стрюк ◽  
Андрій Пікільняк

Hruntova T. V., Yechkalo YU. V., Stryuk A. M. and Pikilʹnyak A. V. Augmented Reality Tools in Physics Training at Higher Technical Educational Institutions. Research goal: the research is aimed at theoretical substantiation of applying the augmented reality technology and its peculiarities at higher technical educational institutions. Research objectives: the research is to solve the problems of determining the role and place of the technology in the educational process and its possible application to physics training. Object of research: teaching physics to students of higher technical educational institutions. Subject of research: the augmented reality technology as a component of the training process at higher educational institutions. Research methods used: theoretical methods include analysis of scientific and methodological literature; empirical methods include studying and observation of the training process. Research results: analysis of scientific publications allows defining the notion of augmented reality; application of augmented reality objects during laboratory practical works on physics is suggested. Main conclusions. introduction of the augmented reality technology in thetraining process at higher technical educational institutions increases learning efficiency, facilitates students’ training and cognitive activities, improves the quality of knowledge acquisition, provokes interest in a subject, promotesdevelopment of research skills and a future specialist’s competent personality.


Author(s):  
Jacob Stegenga

Medical scientists employ ‘quality assessment tools’ to assess evidence from medical research, especially from randomized trials. These tools are designed to take into account methodological details of studies, including randomization, subject allocation concealment, and other features of studies deemed relevant to minimizing bias. There are dozens of such tools available. They differ widely from each other, and empirical studies show that they have low inter-rater reliability and low inter-tool reliability. This is an instance of a more general problem called here the underdetermination of evidential significance. Disagreements about the quality of evidence can be due to different—but in principle equally good—weightings of the methodological features that constitute quality assessment tools. Thus, the malleability of empirical research in medicine is deep: in addition to the malleability of first-order empirical methods, such as randomized trials, there is malleability in the tools used to evaluate first-order methods.


2021 ◽  
Vol 11 (6) ◽  
pp. 2666
Author(s):  
Hafiz Muhammad Usama Hassan Alvi ◽  
Muhammad Shahid Farid ◽  
Muhammad Hassan Khan ◽  
Marcin Grzegorzek

Emerging 3D-related technologies such as augmented reality, virtual reality, mixed reality, and stereoscopy have gained remarkable growth due to their numerous applications in the entertainment, gaming, and electromedical industries. In particular, the 3D television (3DTV) and free-viewpoint television (FTV) enhance viewers’ television experience by providing immersion. They need an infinite number of views to provide a full parallax to the viewer, which is not practical due to various financial and technological constraints. Therefore, novel 3D views are generated from a set of available views and their depth maps using depth-image-based rendering (DIBR) techniques. The quality of a DIBR-synthesized image may be compromised for several reasons, e.g., inaccurate depth estimation. Since depth is important in this application, inaccuracies in depth maps lead to different textural and structural distortions that degrade the quality of the generated image and result in a poor quality of experience (QoE). Therefore, quality assessment DIBR-generated images are essential to guarantee an appreciative QoE. This paper aims at estimating the quality of DIBR-synthesized images and proposes a novel 3D objective image quality metric. The proposed algorithm aims to measure both textural and structural distortions in the DIBR image by exploiting the contrast sensitivity and the Hausdorff distance, respectively. The two measures are combined to estimate an overall quality score. The experimental evaluations performed on the benchmark MCL-3D dataset show that the proposed metric is reliable and accurate, and performs better than existing 2D and 3D quality assessment metrics.


Author(s):  
Mingliang Xu ◽  
Qingfeng Li ◽  
Jianwei Niu ◽  
Hao Su ◽  
Xiting Liu ◽  
...  

Quick response (QR) codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the visual quality, but subtle changes in their appearance may cause scanning failure. In this article, a new method to generate scanning-robust aesthetic QR codes is proposed, which is based on a module-based scanning probability estimation model that can effectively balance the tradeoff between visual quality and scanning robustness. Our method locally adjusts the luminance of each module by estimating the probability of successful sampling. The approach adopts the hierarchical, coarse-to-fine strategy to enhance the visual quality of aesthetic QR codes, which sequentially generate the following three codes: a binary aesthetic QR code, a grayscale aesthetic QR code, and the final color aesthetic QR code. Our approach also can be used to create QR codes with different visual styles by adjusting some initialization parameters. User surveys and decoding experiments were adopted for evaluating our method compared with state-of-the-art algorithms, which indicates that the proposed approach has excellent performance in terms of both visual quality and scanning robustness.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3279
Author(s):  
Maria Habib ◽  
Mohammad Faris ◽  
Raneem Qaddoura ◽  
Manal Alomari ◽  
Alaa Alomari ◽  
...  

Maintaining a high quality of conversation between doctors and patients is essential in telehealth services, where efficient and competent communication is important to promote patient health. Assessing the quality of medical conversations is often handled based on a human auditory-perceptual evaluation. Typically, trained experts are needed for such tasks, as they follow systematic evaluation criteria. However, the daily rapid increase of consultations makes the evaluation process inefficient and impractical. This paper investigates the automation of the quality assessment process of patient–doctor voice-based conversations in a telehealth service using a deep-learning-based classification model. For this, the data consist of audio recordings obtained from Altibbi. Altibbi is a digital health platform that provides telemedicine and telehealth services in the Middle East and North Africa (MENA). The objective is to assist Altibbi’s operations team in the evaluation of the provided consultations in an automated manner. The proposed model is developed using three sets of features: features extracted from the signal level, the transcript level, and the signal and transcript levels. At the signal level, various statistical and spectral information is calculated to characterize the spectral envelope of the speech recordings. At the transcript level, a pre-trained embedding model is utilized to encompass the semantic and contextual features of the textual information. Additionally, the hybrid of the signal and transcript levels is explored and analyzed. The designed classification model relies on stacked layers of deep neural networks and convolutional neural networks. Evaluation results show that the model achieved a higher level of precision when compared with the manual evaluation approach followed by Altibbi’s operations team.


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