Dashboard

About: Dashboard is a research topic. Over the lifetime, 1933 publications have been published within this topic receiving 14928 citations. The topic is also known as: control panel (engineering) & dash.

Electric car charging collision control method and system

Abstract: The invention discloses an electric car charging collision control method and system; when the collision strength cannot reach the detonation threshold of airbags but battery security is affected, power can be cut off. The system comprises a plurality of collision sensors, a plurality of pressure sensors, an entire car controller, a power battery managing system, a power-off protector, a power battery, an airbag control unit, a dashboard, an alarming device, an airbag control unit and a security airbag system. The collision sensors and the pressure sensors are connected with the entire car controller, the entire car controller is connected with the power battery managing system, the airbag control unit, the dashboard and the alarming device, the power battery managing system is connected with the power battery through the power-off protector, and the airbag control unit is connected with the security airbag system. The system has the advantages that when the collision strength cannot reach the detonation threshold of the airbags but battery security is affected, power can be cut off; security risks result from failures of high-voltage power supply of a car can be avoided effectively, and security of the car and passengers can be protected effectively.

Dashboard structural assembly and method for the production of same

Abstract: Dashboard structural assembly comprising a formed elongate metal structure ( 2 ) and a structuring functional member ( 4 ) of plastics material incorporating an air duct, over-moulded on the elongate metal structure. The elongate metal structure ( 2 ) comprises a first portion having a first thickness and a second portion having a second thickness which is less than the first.

SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals

Abstract: The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 in animal hosts. We used two major health databases to extract unstructured data and generated a global dataset of SARS-CoV-2 events in animals. The dataset presents harmonized host names, integrates relevant epidemiological and clinical data on each event, and is readily usable for analytical purposes. We also share the code for technical and visual validation of the data and created a user-friendly dashboard for data exploration. Data on SARS-CoV-2 occurrence in animals is critical to adapting monitoring strategies, preventing the formation of animal reservoirs, and tailoring future human and animal vaccination programs. The FAIRness and analytical flexibility of the data will support research efforts on SARS-CoV-2 at the human-animal-environment interface. We intend to update this dataset weekly for at least one year and, through collaborations, to develop it further and expand its use. Measurement(s) SARS-CoV-2 event in animal hosts Technology Type(s) Manual data collection from text sources Factor Type(s) ID • primary_source • archive_event_number • link_web • secondary_source • secondary_source_ID • secondary_source_web • host_com_orig • host_sci_orig • host_com_res • host_sci_res • host_colloq • host_sci_spec_res • family • epidemiological_unit • number_cases • number_susceptible • number_tested • number_deaths • age • sex • country_iso3 • country_name • subnational_administration • city • location_detail • date_confirmed • date_reported • date_published • related_to_other_entries • related_ID • test • sampling_type • test_2 • sampling_type_2 • test_3 • sampling_type_3 • negative_test • negative_sampling_type • negative_test_2 • negative_sampling_type_2 • reason_for_testing • symptoms • outcome • living_conditions • source_of_infection • variant • control_measures • original_source • link_original_source Sample Characteristic - Organism animal host(s) Sample Characteristic - Environment domestic • wild• captive• farmed Sample Characteristic - Location Global

Industry 4.0 technologies and Lean Production Combination: A Strategic Methodology Based on Links Quantification

Abstract: The current environment faced to economy and sustainability requirements brings to the fore two paradigms sustaining the industrial performance: Lean Production (LP) and Industry 4.0 technologies (I4.0). Whatever business the companies run they have to consider the benefits of both. The methodology of this paper is based not only upon combined analysis identifying nature of links but also on quantifying these links in order to provide a dashboard with Key indexes helpful for decision makers. It involves a strategic method to figure out the technologies and Lean tools deployment priority. It consists in an attempt to quantify links providing a method based on Layers analysis for modular implementation and an approach to settle calculation of an actionable elements. Indicators comes out for strategy deployment: Index of relevancy and Index of coverage. They are built to increase the visibility, followed by modular implementation proposal and Expansion indexto allow monitoring. At the end, the industrial managers initially attempting to deploy Lean and industry 4.0 with reserve impressed by these giant transformations, will beneficiate of a structured roadmap (algorithm-based) culminating to the priority of the implemented tools and technologies.