scholarly journals CNN-Based Deep Architecture for Health Monitoring of Civil and Industrial Structures Using UAVs

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 69
Author(s):  
Thomas Harweg ◽  
Annika Peters ◽  
Daniel Bachmann ◽  
Frank Weichert
Keyword(s):  
Health Monitoring ◽  
Real Life ◽  
Image Data ◽  
Steel Structures ◽  
Point Of View ◽  
Object Localization ◽  
Data Annotation ◽  
Industrial Structures ◽  
Multi Stage ◽  
Novel Approach

Health monitoring of civil and industrial structures has been gaining importance since the collapse of the bridge in Genoa (Italy). It is vital for the creation and maintenance of reliable infrastructure. Traditional manual inspections for this task are crucial but time consuming. We present a novel approach for combining Unmanned Aerial Vehicles (UAVs) and artificial intelligence to tackle the above-mentioned challenges. Modern architectures in Convolutional Neural Networks (CNNs) were adapted to the special characteristics of data streams gathered from UAV visual sensors. The approach allows for automated detection and localization of various damages to steel structures, coatings, and fasteners, e.g., cracks or corrosion, under uncertain and real-life environments. The proposed model is based on a multi-stage cascaded classifier to account for the variety of detail level from the optical sensor captured during an UAV flight. This allows for reconciliation of the characteristics of gathered image data and crucial aspects from a steel engineer’s point of view. To improve performance of the system and minimize manual data annotation, we use transfer learning based on the well-known COCO dataset combined with field inspection images. This approach provides a solid data basis for object localization and classification with state-of-the-art CNN architectures.

scholarly journals The Impact of KLT Coder on the Image Distortion in Astronomy

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Petr Pata
Keyword(s):  
Image Data ◽  
Image Distortion ◽  
Point Of View ◽  
The Novel ◽  
Gaussian Probability Density Function ◽  
Novel Approach ◽  
Spread Function ◽  
Karhunen Loeve Transform ◽  
Astronomical Image Processing ◽  
The Impact

Presented paper is devoted to the application of Karhunen-Loève transform (KLT) for compression and to study of KLT impact on the image distortion in astronomy. This transform is an optimal fit for images with Gaussian probability density function in order to minimize the root mean square error (RMSE). The main part of the encoder is proposed in relation to statistical image properties. Selected astronomical image processing algorithms are used for the encoder testing. The astrometry and point spread function distortion are selected as the most important criteria. The results are compared with JPEG2000 standard. The KLT encoder provides better results from the RMSE point of view. These results are promising and show the novel approach to the design of lossy image compression algorithms and also suitability for algorithms of image data structuring for retrieving, transfer, and distribution.

scholarly journals AUGMENTED ANNOTATIONS: INDOOR DATASET GENERATION WITH AUGMENTED REALITY

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 873-879
Author(s):  
V. Saran ◽  
J. Lin ◽  
A. Zakhor
Keyword(s):  
Augmented Reality ◽  
Object Detection ◽  
Human Subjects ◽  
Image Data ◽  
Data Annotation ◽  
3D Computer Vision ◽  
3D Space ◽  
3D Data ◽  
Novel Approach ◽  
3D Scans

<p><strong>Abstract.</strong> The proliferation of machine learning applied to 3D computer vision tasks such as object detection has heightened the need for large, high-quality datasets of labeled 3D scans for training and testing purposes. Current methods of producing these datasets require first scanning the environment, then transferring the resulting point cloud or mesh to a separate tool for it to be annotated with semantic information, both of which are time consuming processes. In this paper, we introduce <i>Augmented Annotations</i>, a novel approach to bounding box data annotation that solves the scanning and annotation processes of an environment in parallel. Leveraging knowledge of the user’s position in 3D space during scanning, we use augmented reality (AR) to place persistent digital annotations directly on top of indoor real world objects. We test our system with seven human subjects, and demonstrate that this approach can produce annotated 3D data faster than the state-of-the-art. Additionally, we show that Augmented Annotations can also be adapted to automatically produce 2D labeled image data from many viewpoints, a much needed augmentation technique for 2D object detection and recognition. Finally, we release our work to the public as an open-source iPad application designed for efficient 3D data collection.</p>

Bleak Weather for Sun-Shine AG: A Case Study of Impairment of Assets

2014 ◽  
Vol 30 (2) ◽  
pp. 113-126 ◽  
Author(s):  
Dominic Detzen ◽  
Tobias Stork genannt Wersborg ◽  
Henning Zülch
Keyword(s):  
Real Life ◽  
Accounting Standards ◽  
Point Of View ◽  
Professional Judgment ◽  
Economic Point ◽  
Instructional Resource

ABSTRACT This case originates from a real-life business situation and illustrates the application of impairment tests in accordance with IFRS and U.S. GAAP. In the first part of the case study, students examine conceptual questions of impairment tests under IFRS and U.S. GAAP with respect to applicable accounting standards, definitions, value concepts, and frequency of application. In addition, the case encourages students to discuss the impairment regime from an economic point of view. The second part of the instructional resource continues to provide instructors with the flexibility of applying U.S. GAAP and/or IFRS when students are asked to test a long-lived asset for impairment and, if necessary, allocate any potential impairment. This latter part demonstrates that impairment tests require professional judgment that students are to exercise in the case.

scholarly journals The contribution of the Italian residents in neurology to the COVID-19 crisis: admirable generosity but neurological training remains their priority

2021 ◽  
Author(s):  
Cristina Tassorelli ◽  
Vincenzo Silani ◽  
Alessandro Padovani ◽  
Paolo Barone ◽  
Paolo Calabresi ◽  
...  
Keyword(s):  
Clinical Training ◽  
Real Life ◽  
Healthcare Management ◽  
Point Of View ◽  
Research Activity ◽  
High Quality ◽  
Research Activities ◽  
Italian Regions ◽  
Training And Research

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic has severely impacted the Italian healthcare system, underscoring a dramatic shortage of specialized doctors in many disciplines. The situation affected the activity of the residents in neurology, who were also offered the possibility of being formally hired before their training completion. Aims (1) To showcase examples of clinical and research activity of residents in neurology during the COVID-19 pandemic in Italy and (2) to illustrate the point of view of Italian residents in neurology about the possibility of being hired before the completion of their residency program. Results Real-life reports from several areas in Lombardia—one of the Italian regions more affected by COVID-19—show that residents in neurology gave an outstanding demonstration of generosity, collaboration, reliability, and adaptation to the changing environment, while continuing their clinical training and research activities. A very small minority of the residents participated in the dedicated selections for being hired before completion of their training program. The large majority of them prioritized their training over the option of earlier employment. Conclusions Italian residents in neurology generously contributed to the healthcare management of the COVID-19 pandemic in many ways, while remaining determined to pursue their training. Neurology is a rapidly evolving clinical field due to continuous diagnostic and therapeutic progress. Stakeholders need to listen to the strong message conveyed by our residents in neurology and endeavor to provide them with the most adequate training, to ensure high quality of care and excellence in research in the future.

scholarly journals New fractional approaches for n-polynomial P-convexity with applications in special function theory

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Shu-Bo Chen ◽  
Saima Rashid ◽  
Muhammad Aslam Noor ◽  
Zakia Hammouch ◽  
Yu-Ming Chu
Keyword(s):  
Fractional Calculus ◽  
Convex Functions ◽  
Special Functions ◽  
Real Life ◽  
Fractional Integrals ◽  
Digamma Function ◽  
Novel Approach ◽  
Inequality Theory ◽  
New Strategy ◽  
Significant Mechanism

Abstract Inequality theory provides a significant mechanism for managing symmetrical aspects in real-life circumstances. The renowned distinguishing feature of integral inequalities and fractional calculus has a solid possibility to regulate continuous issues with high proficiency. This manuscript contributes to a captivating association of fractional calculus, special functions and convex functions. The authors develop a novel approach for investigating a new class of convex functions which is known as an n-polynomial $\mathcal{P}$ P -convex function. Meanwhile, considering two identities via generalized fractional integrals, provide several generalizations of the Hermite–Hadamard and Ostrowski type inequalities by employing the better approaches of Hölder and power-mean inequalities. By this new strategy, using the concept of n-polynomial $\mathcal{P}$ P -convexity we can evaluate several other classes of n-polynomial harmonically convex, n-polynomial convex, classical harmonically convex and classical convex functions as particular cases. In order to investigate the efficiency and supremacy of the suggested scheme regarding the fractional calculus, special functions and n-polynomial $\mathcal{P}$ P -convexity, we present two applications for the modified Bessel function and $\mathfrak{q}$ q -digamma function. Finally, these outcomes can evaluate the possible symmetric roles of the criterion that express the real phenomena of the problem.

New Multi-View Classification Method with Uncertain Data

2021 ◽  
Vol 16 (1) ◽  
pp. 1-23
Author(s):  
Bo Liu ◽  
Haowen Zhong ◽  
Yanshan Xiao
Keyword(s):  
Learning Strategy ◽  
State Of The Art ◽  
Uncertain Data ◽  
Real Life ◽  
Support Vector ◽  
Classification Methods ◽  
Complementary Information ◽  
Novel Approach ◽  
Svm Model ◽  
Iterative Framework

Multi-view classification aims at designing a multi-view learning strategy to train a classifier from multi-view data, which are easily collected in practice. Most of the existing works focus on multi-view classification by assuming the multi-view data are collected with precise information. However, we always collect the uncertain multi-view data due to the collection process is corrupted with noise in real-life application. In this case, this article proposes a novel approach, called uncertain multi-view learning with support vector machine (UMV-SVM) to cope with the problem of multi-view learning with uncertain data. The method first enforces the agreement among all the views to seek complementary information of multi-view data and takes the uncertainty of the multi-view data into consideration by modeling reachability area of the noise. Then it proposes an iterative framework to solve the proposed UMV-SVM model such that we can obtain the multi-view classifier for prediction. Extensive experiments on real-life datasets have shown that the proposed UMV-SVM can achieve a better performance for uncertain multi-view classification in comparison to the state-of-the-art multi-view classification methods.

Adherence, Persistence, and Effectiveness in Real Life. Multicenter Long-Term Study on the Use of Pirfenidone and Nintedanib in the Treatment of Idiopathic Pulmonary Fibrosis

2021 ◽  
pp. 089719002110086
Author(s):  
Fiorenzo Santoleri ◽  
Luigia Auriemma ◽  
Antonella Spacone ◽  
Stefano Marinari ◽  
Fabio Esposito ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Pharmacological Study ◽  
Functional Decline ◽  
Real Life ◽  
Point Of View ◽  
Response To Treatment ◽  
First Year ◽  
Long Term Study ◽  
Second Year

Background: In the treatment of idiopathic pulmonary fibrosis (IPF), nintedanib and pirfenidone, with their different mechanisms of action, lead to a reduction in the rate of progression of the fibrosis process measured by the reduction of functional decline, and, in particular, the decrease in forced vital capacity (FVC) and of the diffusion capacity of the lungs for carbon monoxide (DLCO). The objective of this study was to analyze real-life adherence, persistence and efficacy in the use of pirfenidone and nintedanib in the treatment of IPF. Methods: A non-interventional multicenter retrospective observational pharmacological study in real-life treat-ment at 1 and 2 years was conducted. Furthermore, we analyzed the levels of FVC and DLCO at 6 and 12 months, respectively, from the start of treatment. Results: We identified 144 patients in the period between January 2013 and April 2019. From the point of view of adherence, there is no difference between the two drugs, even though patients who used pirfenidone had increasingly higher values: 0.90 vs 0.89, in the first year, and 0.91 vs 0.84, in the second year. In the first year of treatment, the percentage of persistent patients was 67% and 76%, while in the second year, it dropped to 47% and 53% for pirfenidone and nintedanib, respectively. Conclusion: The stratification of the adherence values as a function of the response to treatment in terms of FVC at 12 months for both study drugs showed that patients with optimal response scored adherence of more than 90%.

scholarly journals ALVIC versus the Internet: Redesigning a Networked Virtual Environment Architecture

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
Peter Quax ◽  
Jeroen Dierckx ◽  
Bart Cornelissen ◽  
Wim Lamotte
Keyword(s):  
Virtual Environment ◽  
Large Scale ◽  
Virtual Communities ◽  
Real Life ◽  
Point Of View ◽  
The Internet ◽  
Generic Framework ◽  
Short Period ◽  
Networked Virtual Environment ◽  
Near Future

The explosive growth of the number of applications based on networked virtual environment technology, both games and virtual communities, shows that these types of applications have become commonplace in a short period of time. However, from a research point of view, the inherent weaknesses in their architectures are quickly exposed. The Architecture for Large-Scale Virtual Interactive Communities (ALVICs) was originally developed to serve as a generic framework to deploy networked virtual environment applications on the Internet. While it has been shown to effectively scale to the numbers originally put forward, our findings have shown that, on a real-life network, such as the Internet, several drawbacks will not be overcome in the near future. It is, therefore, that we have recently started with the development of ALVIC-NG, which, while incorporating the findings from our previous research, makes several improvements on the original version, making it suitable for deployment on the Internet as it exists today.

Positive evaluation in the language of human resources: textbooks versus reality

2021 ◽  
Vol 11 (1) ◽  
pp. 133-152
Author(s):  
Pavel Reich
Keyword(s):  
Human Resources ◽  
Real Life ◽  
Point Of View ◽  
Business English ◽  
Evaluative Language ◽  
English Textbooks ◽  
General Business ◽  
Hr Managers ◽  
Authentic Language ◽  
Positive Evaluation

Abstract The aim of the present paper is to focus on the language of Human Resources (HR) as one of the subfields of English for business purposes in respect of positive evaluation and stancetaking and to identify to what extent evaluative language common in real-life situations is reflected in currently available textbooks of English for HR (EHR). Authentic language is taken from blogs and interviews with prominent HR managers on www.thehrdirector.com, which is a global online magazine dedicated to HR professionals. The corpus created from these texts is analysed from the point of view of evaluative language and the data ascertained are put into contrast with the language presented in three commonly available HR English textbooks. The analysis focusses on the lexical level of language and is based on the Appraisal framework (and the system of Attitude) of Systemic Functional Linguistics. Even though the present study is intended as qualitative rather than quantitative, the findings are quantified in order to shed some light on the commonality and frequency of some of the phenomena ascertained and their reflection in the textbooks. The outcomes of the analysis might serve as food for thought and inspiration for tertiary-level teachers of general business English courses as well as highly specialised courses focusing on the language of human resources.

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