Bradygood7697

Face recognition is a well-researched domain however many issues for instance expression changes, illumination variations, and presence of occlusion in the face images seriously affect the performance of such systems. A recent survey shows that COVID-19 will also have a considerable and long-term impact on biometric face recognition systems. The work has presented two novel Savitzky-Golay differentiator (SGD) and gradient-based Savitzky-Golay differentiator (GSGD) feature extraction techniques to elevate issues related to face recognition systems. The SGD and GSGD feature descriptors are able to extract discriminative information present in different parts of the face image. In this paper, an efficient and robust person identification using symbolic data modeling approach and similarity analysis measure is devised and employed for feature representation and classification tasks to address the aforementioned issues of face recognition. Extensive experiments and comparisons of the proposed descriptors experimental results indicated that the proposed approaches can achieve optimal performance of 96-97, 92-96, 100, 84-93, and 87-96% on LFW, ORL, AR, IJB-A datasets, and newly devised VISA database, respectively.In practical applications of graph theory, indeterminacy factors always appear in graphs. Uncertain random graph was proposed via chance theory, in which some edges exist with degrees in probability measure and others exist with degrees in uncertain measure. This paper discusses the contributions of edges for connectivity of an uncertain random graph and proposes concepts about significance of edges, according to which edges are classified. In addition, this paper presents algorithms for calculating connectivity index and significance of edges of an uncertain random graph. Examples are given to illustrate algorithms and methods.In Basel (CH), the thermal impact of various subsurface structures on urban groundwater resources, including five underground parking lots and a freeway tunnel, were investigated by monitoring systems. Data were analyzed together with meteorological and groundwater temperature data and results from heat-transport modelling.Significantly elevated temperatures between 18.8 and 21.1 °C were recorded in the underground parking lots, even in winter. Thus, underground parking lots emit heat into the surroundings all year. In comparison, data recorded in the freeway tunnel indicate that in the winter months heat can also be absorbed from below ground.In addition, the temperatures of underground parking lots show a clear dependence on the type of use with a higher number of daily entrances and exits, greater daily temperature increases were detected, with differences of up to 2 °C. This became particularly clear in the "lockdown" period during the COVID-19 pandemic between March and May 2020.Interactions between humans and machines that include artificial intelligence are increasingly common in nearly all areas of life. Meanwhile, AI-products are increasingly endowed with emotional characteristics. That is, they are designed and trained to elicit emotions in humans, to recognize human emotions and, sometimes, to simulate emotions (EAI). The introduction of such systems in our lives is met with some criticism. There is a rather strong intuition that there is something wrong about getting attached to a machine, about having certain emotions towards it, and about getting involved in a kind of affective relationship with it. In this paper, I want to tackle these worries by focusing on the last aspect in what sense could it be problematic or even wrong to establish an emotional relationship with EAI-systems? I want to show that the justifications for the widespread intuition concerning the problems are not as strong as they seem at first sight. To do so, I discuss three arguments the argument from self-deception, the argument from lack of mutuality, and the argument from moral negligence.By collecting more data at a higher resolution and by creating the capacity to implement detailed crop management, autonomous crop equipment has the potential to revolutionise precision agriculture (PA), but unless farmers find autonomous equipment profitable it is unlikely to be widely adopted. The objective of this study was to identify the potential economic implications of autonomous crop equipment for arable agriculture using a grain-oilseed farm in the United Kingdom as an example. The study is possible because the Hands Free Hectare (HFH) demonstration project at Harper Adams University has produced grain with autonomous equipment since 2017. That practical experience showed the technical feasibility of autonomous grain production and provides parameters for farm-level linear programming (LP) to estimate farm management opportunities when autonomous equipment is available. The study shows that arable crop production with autonomous equipment is technically and economically feasible, allowing medium size farms to approach minimum per unit production cost levels. The ability to achieve minimum production costs at relatively modest farm size means that the pressure to "get big or get out" will diminish. Costs of production that are internationally competitive will mean reduced need for government subsidies and greater independence for farmers. The ability of autonomous equipment to achieve minimum production costs even on small, irregularly shaped fields will improve environmental performance of crop agriculture by reducing pressure to remove hedges, fell infield trees and enlarge fields.

The online version contains supplementary material available at 10.1007/s11119-021-09822-x.

The online version contains supplementary material available at 10.1007/s11119-021-09822-x.The modern mobile phones and the complete digitalization of the public and private transport networks have allowed to access useful information to understand the user's mean of transportation. This enables a plethora of old and new applications in the fields of sustainable mobility, smart transportation, assistance, and e-health. The precise understanding of the travel means is at the basis of the development of a large range of applications. TAK-243 in vitro In this paper, a number of metrics has been identified to understand whether an individual on the move is stationary, walking, on a motorized private or public transport, with the aim of delivering to city users personalized assistance messages for sustainable mobility, health, and/or for a better and enjoyable life, etc. Differently from the state-of-the-art solutions, the proposed approach has been designed to provide results, and thus collect metrics, in real operating conditions (imposed on the mobile phones as a range of different mobile phone kinds, operating system constraints managing Applications, active battery consumption manager, etc.