Unsupervised Learning Method for Events Identification in φ-OTDR

In this paper, an unsupervised-learning method for events-identification in φ-OTDR fiber-optic distributed vibration sensor is proposed. The different vibration-events including blowing, raining, direct and indirect hitting, and noise-induced false vibration are clustered by the k-means algorithm. The equivalent classification accuracy of 99.4% has been obtained, compared with the actual classes of vibration-events in the experiment. With the cluster-number of 3, the maximal Calinski-Harabaz index and Silhouette coefficient are obtained as 2653 and 0.7206, respectively. It is found that our clustering method is effective for the events-identification of φ-OTDR without any prior labels, which provides an interesting application of unsupervised-learning in self-classification of vibration-events for φ-OTDR.

Central and Periodic Multi-Scale Discrete Radon Transforms

The multi-scale discrete Radon transform (DRT) calculates, with linearithmic complexity, the summation of pixels, through a set of discrete lines, covering all possible slopes and intercepts in an image, exclusively with integer arithmetic operations. An inversion algorithm exists and is exact and fast, in spite of being iterative. In this work, the DRT forward and backward pair is evolved to propose two faster algorithms: central DRT, which computes only the central portion of intercepts; and periodic DRT, which computes the line integrals on the periodic extension of the input. Both have an output of size N×4N, instead of 3N×4N, as in the original algorithm. Periodic DRT is proven to have a fast inversion, whereas central DRT does not. An interesting application of periodic DRT is its use as building a block of discrete curvelet transform. Central DRT can provide almost a 2× speedup over conventional DRT, probably becoming the faster Radon transform algorithm available, at the cost of ignoring 15% of the summations in the corners.

Path Driven Dual Arm Mobile Co-Manipulation Architecture for Large Part Manipulation in Industrial Environments

Collaborative part transportation is an interesting application as many industrial sectors require moving large parts among different areas of the workshops, using a large amount of the workforce on this tasks. Even so, the implementation of such kinds of robotic solutions raises technical challenges like force-based control or robot-to-human feedback. This paper presents a path-driven mobile co-manipulation architecture, proposing an algorithm that deals with all the steps of collaborative part transportation. Starting from the generation of force-based twist commands, continuing with the path management for the definition of safe and collaborative areas, and finishing with the feedback provided to the system users, the proposed approach allows creating collaborative lanes for the conveyance of large components. The implemented solution and performed tests show the suitability of the proposed architecture, allowing the creation of a functional robotic system able to assist operators transporting large parts on workshops.

Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective

Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 certified AI products are available for chest radiography or chest CT. These AI products cover a wide range of abnormalities, including pneumonia, pneumothorax and lung cancer. Most applications are aimed at detecting disease, complemented by products that characterize or quantify tissue. At present, none of the thoracic AI products is specifically designed for the pediatric population. However, some products developed to detect tuberculosis in adults are also applicable to children. Software is under development to detect early changes of cystic fibrosis on chest CT, which could be an interesting application for pediatric radiology. In this review, we give an overview of current AI products in thoracic radiology and cover recent literature about AI in chest radiography, with a focus on pediatric radiology. We also discuss possible pediatric applications.

Wastewater-Based Epidemiology as an Early Warning System for the Spreading of SARS-CoV-2 and Its Mutations in the Population

New methodologies based on the principle of “sewage epidemiology” have been successfully applied before in the detection of illegal drugs. The study describes the idea of early detection of a virus, e.g., SARS-CoV-2, in wastewater in order to focus on the area of virus occurrence and supplement the results obtained from clinical examination. By monitoring temporal variation in viral loads in wastewater in combination with other analysis, a virus outbreak can be detected and its spread can be suppressed early. The use of biosensors for virus detection also seems to be an interesting application. Biosensors are highly sensitive, selective, and portable and offer a way for fast analysis. This manuscript provides an overview of the current situation in the area of wastewater analysis, including genetic sequencing regarding viral detection and the technological solution of an early warning system for wastewater monitoring based on biosensors.

A Review of Current Research in Subscale Flight Testing and Analysis of Its Main Practical Challenges

Testing of untethered subscale models, often referred to as subscale flight testing, has traditionally had a relatively minor, yet relevant use in aeronautical research and development. As recent advances in electronics, rapid prototyping and unmanned-vehicle technologies expand its capabilities and lower its cost, this experimental method is seeing growing interest across academia and the industry. However, subscale models cannot meet all similarity conditions required for simulating full-scale flight. This leads to a variety of approaches to scaling and to other alternative applications. Through a literature review and analysis of different scaling strategies, this study presents an overall picture of how subscale flight testing has been used in recent years and synthesises its main issues and practical limitations. Results show that, while the estimation of full-scale characteristics is still an interesting application within certain flight conditions, subscale models are progressively taking a broader role as low-cost technology-testing platforms with relaxed similarity constraints. Different approaches to tackle the identified practical challenges, implemented both by the authors and by other organisations, are discussed and evaluated through flight experiments.

A new extension to the controlled metric type spaces endowed with a graph

In this paper, we initiate a new extension of b-metric spaces, called controlled metric-like spaces, by changing the condition $$ \bigl[\wp (s,r)=0 \Leftrightarrow s=r\bigr]\quad \text{by } \bigl[\wp (s,r)=0 \Rightarrow s=r\bigr] $$ [ ℘ ( s , r ) = 0 ⇔ s = r ] by [ ℘ ( s , r ) = 0 ⇒ s = r ] and that means basically we may have a non-zero self-distance. We prove some fixed point theorems which generalize many results in the literature. Also, we present an interesting application to illustrate our results by considering controlled metric-like spaces endowed with a graph.

The (α, β)-ramification invariants of a number field

Let L be a number field. For a given prime p, we define integers α p L $ \alpha_{p}^{L} $ and β p L $ \beta_{p}^{L} $ with some interesting arithmetic properties. For instance, β p L $ \beta_{p}^{L} $ is equal to 1 whenever p does not ramify in L and α p L $ \alpha_{p}^{L} $ is divisible by p whenever p is wildly ramified in L. The aforementioned properties, although interesting, follow easily from definitions; however a more interesting application of these invariants is the fact that they completely characterize the Dedekind zeta function of L. Moreover, if the residue class mod p of α p L $ \alpha_{p}^{L} $ is not zero for all p then such residues determine the genus of the integral trace.

Kugel ball as an interesting application of designing the hydrosphere

Analytical solutions are not available for the partial hemispherical hydrosphere which called as the Kugel ball fountain or the Kugel ball. However, this study offers a comprehensive idea about this phenomenon presenting a design map that gives a panoramic sight enabling the designers to easily choose whatever specifications needed for their fountain. Through simplifying the author previous formulae for this type of bearings, this paper removes the mystery of the Kugel ball phenomenon and shows that no complicated mathematic or physics are needed, as believed, to be grasped for producing such fountains. A new simple design technique is used and the most two famous fountains (at the House of Science in Patras, Greece and the largest at the Science Museum of Virginia, Richmond, USA.) are checked as an application of this design. One of the most important side results of this study is finding the equilibrium point, discovered in the author previous papers, which was considered as the equilibrium point between the forces of centripetal inertia, viscosity and friction due to the surface roughness. It becomes clear that this point is a natural characteristic of this type of bearings.