Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
As Apple, Google, and other high-tech companies team with automakers to make cars smart enough to drive themselves, do roads need to be as dumb as the concrete and asphalt they're made of? Europe doesn't think so. The European Union has invested more than 200 million [euro], or $227 million, over the past few years in a number of research programs aimed at creating intelligent infrastructure that will communicate with smart cars. The goal is to eliminate congestion in growing urban areas, help the environment, and above all, save lives. The costs of auto travel in Europe are large, multifarious, and growing. European Union drivers currently own one third of the world's one billion cars, and congestion costs the region about 1 percent of gross domestic product (GDP) every year, a number that is rising. Transport is also responsible for about a quarter of EU greenhouse gas emissions, which Brussels aims to reduce by as much as 80 percent of 1990 levels by 2050. And nearly 27,000 people died on European roads last year. On average, up to 50 million people are injured in car accidents in Europe each year, with about 600,000 hospitalized at a cost of about 160 billion [euro], according to figures compiled by the World Health Organization and the European Transport Safety Council. Against this background, the European Union has made intelligent transport a priority in its research and innovation programs. Smart roads, capable of warning drivers of hazardous road conditions and approaching cars well before such hazards enter their field of vision, are a leading component of the effort. Powering this smart infrastructure is the latest advances in sensors, wireless communications, and computers, all tied together by the Internet. Smart roads are one part of a system designed to provide vehicles with 360-degree awareness of their surroundings via a set of in-car sensors, transmitters, and processors that allow cars to communicate with each other and gather real-time data from road infrastructure, including signs and traffic signals as well as the road itself. Within this system, roads would incorporate sensors and other technology to provide vehicles and drivers information about hazardous conditions and other critical events, well before they're within eyeshot. The technology, known as vehicle-to-everything, or V2X, could reduce accidents by as much as 80 percent, European researchers claim. Estimates for developing and implementing this advanced road transport infrastructure across Europe range between 80 billion [euro] and 140 billion [euro]. Hermann Mezer, the chief executive of the European Road Transport Telematics Implementation Coordination (ERTICO), a public-private organization involved in the production of intelligent transport systems, called the systems a game changer. Not surprisingly, a number of technology players want to carve out a piece of that business, among them Germany's Siemens, NXP in the Netherlands, and a number of US companies, including Cisco and IBM. Siemens, a key provider of traffic management systems in Europe, has been quick to expand into intelligent infrastructure, especially environmental detection systems and road works warning systems. The Munich-based engineering giant is working closely with NXP, a specialized chipmaker headquartered in Einhoven that is among the first to develop and deliver V2X chipsets for high-volume manufacturing. The Dutch company is also collaborating with Singapore's Nanyang Technological University to build a smart mobility test bed in the southeast Asian city-state. The project involves 100 vehicles and 50 roadside units that will test V2X technologies over the next four years. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle