Visible to the public Biblio

Filters: Keyword is Impedance measurement  [Clear All Filters]
2022-12-07
Chedurupalli, Shivakumar, Karthik Reddy, K, Akhil Raman, T S, James Raju, K.C.  2022.  High Overtone Bulk Acoustic Resonator with improved effective coupling coefficient. 2022 IEEE International Symposium on Applications of Ferroelectrics (ISAF). :1—4.
A High Overtone Bulk Acoustic Wave Resonator (HBAR) is fabricated with the active material being Ba0.5Sr0.5TiO3 (BST). Owing to its strong electrostrictive property, the BST needs an external dc voltage to yield an electromechanical coupling. The variations in resonances with respect to varying dc fields are noted and analyzed with the aid of an Resonant Spectrum Method (RSM) model. Effective coupling coefficient \$(\textbackslashmathrmK\_\textbackslashmathrme\textbackslashmathrmf\textbackslashmathrmfˆ2(%))\$ in the case of employed MIM based structure is observed and the comparisons are drawn with the corresponding values of the CPC structures. An improvement of 70% in the value of \$\textbackslashmathrmK\_\textbackslashmathrme\textbackslashmathrmf\textbackslashmathrmfˆ2\$(%)at 1.34 GHz is witnessed in MIM structures because of direct access to the bottom electrode of the structure.
2020-07-20
Rumez, Marcel, Dürrwang, Jürgen, Brecht, Tim, Steinshorn, Timo, Neugebauer, Peter, Kriesten, Reiner, Sax, Eric.  2019.  CAN Radar: Sensing Physical Devices in CAN Networks based on Time Domain Reflectometry. 2019 IEEE Vehicular Networking Conference (VNC). :1–8.
The presence of security vulnerabilities in automotive networks has already been shown by various publications in recent years. Due to the specification of the Controller Area Network (CAN) as a broadcast medium without security mechanisms, attackers are able to read transmitted messages without being noticed and to inject malicious messages. In order to detect potential attackers within a network or software system as early as possible, Intrusion Detection Systems (IDSs) are prevalent. Many approaches for vehicles are based on techniques which are able to detect deviations from specified CAN network behaviour regarding protocol or payload properties. However, it is challenging to detect attackers who secretly connect to CAN networks and do not actively participate in bus traffic. In this paper, we present an approach that is capable of successfully detecting unknown CAN devices and determining the distance (cable length) between the attacker device and our sensing unit based on Time Domain Reflectometry (TDR) technique. We evaluated our approach on a real vehicle network.