Metamaterials, Metasurfaces, and Nanotechnology, and their Applications to Antennas, Sensors, and Cognitive Radar
Notice bibliographique
Résumé
Dr. Amir Zaghloul presents seminar on "Metamaterials, Metasurfaces, and Nanotechnology and Their Applications to Antennas, Sensors, and Cognitive Radar" On March 19th, Professor Amir I. Zaghloul, presented a seminar on "Metamaterials, Metasurfaces, and Nanotechnology and Their Applications to Antennas, Sensors, and Cognitive Radar" to Wireless@VT students and faculty. In addition, the seminar was streamed live allowing W@VT's IAP members to watch the event remotely in real time. Abstract: Metamaterials and metasurfaces are engineered materials and special surfaces that have parameters and features that do not exist in natural materials and simple surfaces. The prefix "meta" has been extensively used in recent years and has encompassed techniques that have been known under different names such as frequency selective surfaces (FSS), electromagnetic band-gap (EBG) structures, high permeability materials, and others. Among desirable features in metamaterials are: negative refractive index, coherent reflection, cloaking capability, and manipulation for transformation optics operations. The talk goes through some of the research work in this area, including the introduction of random metamaterials, which offer features that differ from those of conventional periodic materials. Examples include adaptive metasurfaces of special reflection phases that have applications in low-profile antennas, and introduce new tools in cognitive radar and anti-jamming operations. Nanotechnology is another area of intensive research in antennas and special surfaces for wide range of applications. This includes carbon nanotubes (CNT) and graphene-based structures and designs. Nanotechnology does not only offer light-weight and high tensile strength, it also introduces polarization selectivity in antennas and detection capability in gas sensors, among other features for communications and medical applications. Examples are given on antenna, sensor, and metamaterial designs. The talk will also address a variety of research topics of interest to the Army Research Laboratory, and will explain new initiatives for collaboration between ARL and academia. Opportunities for internship programs that benefit faculty and students will be discussed. Bio: Amir I. Zaghloul has been with the ECE Department at Virginia Tech since 2001, currently as a Research Professor and with the US Army Research Laboratory, Adelphi, MD. Prior to 2001, he was at COMSAT Laboratories for 24 years performing and directing R&D work on satellite communications and antennas. He is a Life Fellow of the IEEE, Fellow of the Applied Computational Electromagnetics Society (ACES), Associate Fellow of The American Institute of Aeronautics and Astronautics (AIAA), and Member of Commissions A, and B, and Chair of Commission C of the US National Committee (USNC) of the International Union of Radio Science (URSI). He was the General Chair of the 2005 "IEEE International Symposium on Antennas and Propagation and USNC/URSI Meeting," held in Washington, D.C., and is the Co-Chair of the 2014 ACES conference, to be held in Jacksonville, FL. He served as an Ad Com member of the IEEE AP Society, member of the IEEE Publication Services and Products Board (PSPB) and member of the Editorial Board of "The Institute." He was a Distinguished Lecturer for the IEEE Sensors Council. He received several research and patent awards, including the Exceptional Patent Award at COMSAT and the 1986 Wheeler Prize Award for Best Application Paper in the IEEE Transactions on Antennas and Propagation. He has over 300 publications, books, book chapters and patents in the areas of antennas, electromagnetics, and communications. Dr. Zaghloul received the Ph.D. and M.A.Sc. degrees from the University of Waterloo, Canada in 1973 and 1970, respectively, and the B.Sc. degree (Honors) from Cairo University, Egypt in 1965, all in electrical engineering.
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».