Autor/Autorin: Bhargava Cherry
Cherry Bhargava is working as Assistant Professor and Head VLSI domain, Lovely Professional University, India. She is an alumnus of Thapar University, Patiala and she has submitted PhD at IKG PTU, India. Pardeep Sharma is working as Assistant Professor at Lovely Professional University. Jaya is working with CSS Corp as a Network Engineer
From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS).
Über den Autor
Cherry Bhargava arbeitet als Assistenzprofessorin und Leiterin des VLSI-Bereichs an der Lovely Professional University, Indien. Sie ist eine Absolventin der Thapar Universität, Patiala. Sie hat ihre Doktorarbeit an der IKGPTU eingereicht. Pardeep Kumar Sharma arbeitet als Assistenzprofessor und promoviert an der LPU. Sahib Ali ist ein Forschungsstipendiat an der LPU.
Klappentext
From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS).
