Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Fuzzy logic. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Biodegradable nanofibrous polymeric substrates for generating elastic and flexible electronics.

Abstract: Biodegradable nanofibrous polymeric substrates are used to fabricate suturable, elastic, and flexible electronics and sensors. The fibrous microstructure of the substrate makes it permeable to gas and liquid and facilitates the patterning process. As a proof-of-principle, temperature and strain sensors are fabricated on this elastic substrate and tested in vitro. The proposed system can be implemented in the field of bioresorbable electronics and the emerging area of smart wound dressings.

Reversible circuit synthesis using a cycle-based approach

Abstract: Reversible logic has applications in various research areas, including signal processing, cryptography and quantum computation. In this article, direct NCT-based synthesis of a given k-cycle in a cycle-based synthesis scenario is examined. To this end, a set of seven building blocks is proposed that reveals the potential of direct synthesis of a given permutation to reduce both quantum cost and average runtime. To synthesize a given large cycle, we propose a decomposition algorithm to extract the suggested building blocks from the input specification. Then, a synthesis method is introduced that uses the building blocks and the decomposition algorithm. Finally, a hybrid synthesis framework is suggested that uses the proposed cycle-based synthesis method in conjunction with one of the recent NCT-based synthesis approaches which is based on Reed-Muller (RM) spectra.The time complexity and the effectiveness of the proposed synthesis approach are analyzed in detail. Our analyses show that the proposed hybrid framework leads to a better quantum cost in the worst-case scenario compared to the previously presented methods. The proposed framework always converges and typically synthesizes a given specification very fast compared to the available synthesis algorithms. Besides, the quantum costs of benchmark functions are improved about 20p on average (55p in the best case).