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Speed-Power Efficient Novel CMOS Unary-to-Ternary Encoder

A new full-custom design of Unary-to-Ternary-Encoder (UTE) using standard Enhancement-Type-Metal–Oxide-Semiconductor-Field-Effect-Transistor reporting low-PDP (Power-Delay-Product) and low-area is presented. The inherent pass characteristic of the E-MOS-transistor is exploited here to develop the proposed Ternary-Encoder. Theoretical aspects along with the operation of proposed 9:2 and 27:3 UTE are discussed. The complete UTE is designed and optimized on 32 nm standard CMOS technology at 0.9 V supply-rail and 27°C. Ternary digits “0”, “1” and “2” are represented with 0 V, 0.45 V and 0.9 V respectively. The proposed design is validated through extensive T-Spice front-end transient simulations with all possible test patterns. The layout of the proposed design is completed on 32 nm Single-Poly-Double-Metal (SPDM) CMOS--Technology. After DRC and LVS post-layout simulation with extracted parasitic and 1 fF load, is carried out. The valuated performance of the 9:2 UTE is next compared with a recent candidate design to this end, from open literature to benchmark. The Power-Delay-Product (PDP) of proposed UTE is measured by applying ±10% supply variation from nominal on slow, typical and fast MOSFET at −40°C, 27°C and 85°C. Finally, the speed-power characteristic of the proposed 9:2 UTE is explored under different load conditions from 1 to 10 fF.

RETRACTED ARTICLE: Three-Periods Optimization Algorithm: A New Method for Solving Various Optimization Problems

We, the Editor, Institution and Publisher of the journal IETE Journal of Research, have retracted the following article, which is part of the Special Issue titled “Federated Learning for Blockchain Systems and Industrial Internet of Things”: Mohammad Dehghani, Pavel Trojovský, Štěpán Hubálovský, Theyab R. Alsenani & Jaswinder Singh (2022) Three-Periods Optimization Algorithm: A New Method for Solving Various Optimization Problems, IETE Journal of Research, DOI: 10.1080/03772063.2022.2052982 Following publication, concerns were raised about the peer review and decision-making processes for this special issue. After an investigation by the Taylor & Francis Publishing Ethics & Integrity team, in full cooperation with the Editor-in-Chief and the Institution, it was confirmed that the articles included in this special issue were not reviewed appropriately, in line with the Journal's peer review standards and policy. As the stringency of the peer review process is core to the integrity of the publication process, the Editor and Publisher have decided to retract all of the articles within the above-named Special Issue. The journal has not confirmed if the authors were aware of this compromised peer review process. The journal is committed to correcting the scientific record and will fully cooperate with any institutional investigations into this matter. The authors have been informed of this decision. We have been informed in our decision-making by our editorial policies and the COPE guidelines.  The retracted articles will remain online to maintain the scholarly record, but they will be digitally watermarked on each page as ‘Retracted’.

A Meander Delay System Design Using Caps-Triple GAN Optimized with the Remora Optimization Algorithm for IOT Application

In this manuscript, a Meander Delay System design using Caps-Triple GAN optimized with the Remora Optimization Algorithm (ROA) is proposed for the Internet of Things (IoT) application. For designing the Meander Microstrip Delay Line (MMDL) Antenna, the Capsule Triple generative adversarial network (Caps-Triple GAN) is used. The Caps-Triple GAN error and delay parameters are optimized using the ROA. Hence, the designed MMDL Antenna is available in the IoT application. The proposed method is executed in the commercial Sonnet software package. The performance of the proposed method is examined under performance metrics, such as delay time with resistance characteristic, one-step delay time resistance characteristic, delay time, one-step delay time, error, and speed. The prediction results of the proposed MMDL-CAPS-Triple GAN-ROA method predict lower delay times of 14.77%, 15.89%, and 11.50%, higher speed of 32.57%, 16.25%, and 8.44% compared with the existing methods, such as Prediction of the meander delay system parameters for internet-of-things devices utilizing a Pareto-optimal artificial neural network and multiple linear regression (MDS-ANN-MLR), Predicting the frequency characteristics of hybrid meander systems utilizing the feed-forward back propagation network (MDS-FFBPN), Frequency Characteristic Analysis of Meander Structures with Different Connecting Electrodes (MDS-MoM), respectively.