fraux.fr évaluation et analyse
Robots.txt Information
| Robot | Path | Permission |
| GoogleBot | / | ✔ |
| BingBot | / | ✔ |
| BaiduSpider | / | ✔ |
| YandexBot | / | ✔ |
User-agent: * Disallow: Sitemap: sitemap.xml | ||
Meta Tags
| Title | Guillaume Fraux | Postdoctoral researcher at |
| Description | About Guillaume Fraux About Publications Software Contact CV About me I am postdoctoral researcher in computational chemistry, working at the interface between |
| Keywords | N/A |
Server Information
| WebSite | |
| Host IP | 213.186.33.5 |
| Location | France |
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fraux.fr Évaluation
|
Euro€308,788
Dernière mise à jour: 2022-10-23 17:20:50
fraux.fr a un classement mondial Semrush de 34,277,001. fraux.fr a une valeur estimée à € 308,788, sur la base de ses revenus publicitaires estimés. fraux.fr reçoit environ 35,630 visiteurs uniques chaque jour. Son serveur Web est situé au France, avec l'adresse IP 213.186.33.5.Selon SiteAdvisor, fraux.fr est sûr à visiter. |
Trafic & Estimations de la valeur
| Valeur d'achat/vente | Euro€308,788 |
| Revenus publicitaires quotidiens | Euro€286 |
| Revenus publicitaires mensuels | Euro€8,552 |
| Revenus publicitaires annuels | Euro€102,613 |
| Visiteurs uniques quotidiens | 2,376 |
| Remarque: Toutes les valeurs de trafic et de revenus sont des estimations. | |
DNS Records
| Host | Type | TTL | Data |
| fraux.fr. | A | 3599 | IP: 213.186.33.5 |
| fraux.fr. | NS | 3600 | NS Record: dns102.ovh.net. |
| fraux.fr. | NS | 3600 | NS Record: ns102.ovh.net. |
| fraux.fr. | MX | 3600 | MX Record: 100 mx3.mail.ovh.net. |
| fraux.fr. | MX | 3600 | MX Record: 5 mx2.mail.ovh.net. |
| fraux.fr. | MX | 3600 | MX Record: 1 mx1.mail.ovh.net. |
| fraux.fr. | TXT | 60 | TXT Record: v=spf1 include:mx.ovh.com ~all |
| fraux.fr. | TXT | 60 | TXT Record: 4|guillaume.fraux.fr |
HtmlToTextCheckTime:2022-10-23 17:20:50
| Guillaume Fraux About Publications Software Contact CV About me I am postdoctoral researcher in computational chemistry, working at the interface between physics, chemistry and computer science in Michele Ceriotti ’s group at EPFL in Lausanne. I currently work on application of machine learning, and in particular unsupervised learning to material science and chemistry. In our everyday life, we rely on a relatively small number of materials, with very specific characteristics: ceramics, metallic alloys, polymers, etc. However, the number of possible materials created by combining different chemical elements in various proportions and arrangements is gigantic. Because of this, exploring the universe of possible materials to find the best one for a given application is a daunting task, which can be helped by using dimensionality reduction techniques and visualization algorithms. I am particularly interested in devising, implementing and studying algorithms used to simulate complex |
HTTP Headers
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fraux.fr Whois Information
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