With the end of Moore’s law, new paradigms are investigated for more scalable computing systems. One of the promising directions is to examine the data representation toward higher data density per hardware element. Multiple valued logic (MVL) emerged as a promising system due to its advantages over binary data representation. MVL offers higher information processing within the same number of digits when compared with binary systems. Accessing memory is considered one of the most power- and time-consuming instructions within a microprocessor. In the quest for building an entire ternary computer architecture, we propose investigating the potential opportunities of ternary address decoders. This paper presents three different designs for ternary address decoder based on CNTFET. The first design is based on a cascade of Ternary to Binary blocks (T2B) and a binary decoder. The second design is built using the hierarchical structure and enables signals. The third is designed utilising a pre-decoder and ternary logic gates. A comparison of the proposed designs and the binary address decoder in terms of power and delay under different supply voltage and temperature values is introduced. Simulation results show that the second design has the least power and delay of the proposed ternary designs. © 2022 John Wiley & Sons Ltd.
Ternary SRAM circuit designs with CNTFETs
Static random-access memory (SRAM) is a cornerstone in modern microprocessors architecture, as it has high power consumption, large area, and high complexity. Also, the stability of the data in the SRAM against the noise and the performance under the radian exposure are main concern issues. To overcome these limitations in the quest for higher information density by memory element, the ternary logic system has been investigated, showing promising potential compared with the conventional binary base. Moreover, carbon nanotube field effect transistor (CNTFET) is a new alternative device with proper features like low power consumption and threshold voltage dependency on diameter. This paper proposes a new design for ternary SRAM using CNTFET and its evaluation by comparing it against two other designs in many aspects. Moreover, we investigated the static noise margin for the three designs to discuss their stability. Furthermore, we studied the reliability of the designs by evaluating the soft errors effect. © 2023 John Wiley & Sons Ltd.
FPGA Implementation of Reconfigurable CORDIC Algorithm and a Memristive Chaotic System with Transcendental Nonlinearities
Coordinate Rotation Digital Computer (CORDIC) is a robust iterative algorithm that computes many transcendental mathematical functions. This paper proposes a reconfigurable CORDIC hardware design and FPGA realization that includes all possible configurations of the CORDIC algorithm. The proposed architecture is introduced in two approaches: multiplier-less and single multiplier approaches, each with its advantages. Compared to recent related works, the proposed implementation overpasses them in the included number of configurations. Additionally, it demonstrates efficient hardware utilization and suitability for potential applications. Furthermore, the proposed design is applied to a memristive chaotic system with different transcendental functions computed using the proposed reconfigurable block. The memristive system design is realized on the Artix-7 FPGA board, yielding throughputs of 0.4483 and 0.3972 Gbit/s for the two approaches of reconfigurable CORDIC. © 2004-2012 IEEE.
Active and passive sensitivity analysis for the second-order active RC filter families using operational amplifier: a review
This work is a review article that sheds light on the active and passive sensitivities of the active RC filters based on opamp. This work provides a detailed analysis through different filters realization criteria and sensitivity summary tables and quantitative insight by discussing the most significant. However, some are almost forgotten, filters families in the literature over decades. A detailed mathematical analysis for the passive sensitivity to compare the filters’ realizations is presented. The concept of dealing between filter design theory and filter design circuit realization is highlighted. Some filters families are chosen from the literature for the analysis. Some detailed specifications tables for each filter family are given. Monte Carlo simulation is carried out on some filters to compare their passive sensitivity. Furthermore, the effect of the active sensitivity of some filters is verified through simulation by adjusting the input common-mode voltage to lower the DC gain of the amplifier. The results of the simulation match with the theoretical analysis and the summary provided in the specifications tables. © 2022, The Author(s).
Smart Irrigation Systems: Overview
Countries are collaborating to make agriculture more efficient by combining new technologies to improve its procedure. Improving irrigation efficiency in agriculture is thus critical for the survival of sustainable agricultural production. Smart irrigation methods can enhance irrigation efficiency, specially with the introduction of wireless communication systems, monitoring devices, and enhanced control techniques for efficient irrigation scheduling. The study compared on a wide range of study subjects to investigate scientific approaches for smart irrigation. As a result, this project included a wide range of topics related to irrigation methods, decision-making, and technology used. Information was gathered from a variety of scientific papers. So, our research relied on several published documents, the majority of which were published during the last four years, and authors from all over the world. In the meantime, various irrigation initiatives were given special attention. Following that, the evaluation focuses on the key components of smart irrigation, such as real-time irrigation scheduling, IoT, the importance of an internet connection, smart sensing, and energy harvesting. Author
Plant stem tissue modeling and parameter identification using metaheuristic optimization algorithms
Bio-impedance non-invasive measurement techniques usage is rapidly increasing in the agriculture industry. These measured impedance variations reflect tacit biochemical and biophysical changes of living and non-living tissues. Bio-impedance circuit modeling is an effective solution used in biology and medicine to fit the measured impedance. This paper proposes two new fractional-order bio-impedance plant stem models. These new models are compared with three commonly used bio-impedance fractional-order circuit models in plant modeling (Cole, Double Cole, and Fractional-order Double-shell). The two proposed models represent the characterization of the biological cellular morphology of the plant stem. Experiments are conducted on two samples of three different medical plant species from the family Lamiaceae, and each sample is measured at two inter-electrode spacing distances. Bio-impedance measurements are done using an electrochemical station (SP150) in the range of 100 Hz to 100 kHz. All employed models are compared by fitting the measured data to verify the efficiency of the proposed models in modeling the plant stem tissue. The proposed models give the best results in all inter-electrode spacing distances. Four different metaheuristic optimization algorithms are used in the fitting process to extract all models parameter and find the best optimization algorithm in the bio-impedance problems. © 2022, The Author(s).
Design and control of soft biomimetic pangasius fish robot using fin ray effect and reinforcement learning
Soft robots provide a pathway to accurately mimic biological creatures and be integrated into their environment with minimal invasion or disruption to their ecosystem. These robots made from soft deforming materials possess structural properties and behaviors similar to the bodies and organs of living creatures. However, they are difficult to develop in terms of integrated actuation and sensing, accurate modeling, and precise control. This article presents a soft-rigid hybrid robotic fish inspired by the Pangasius fish. The robot employs a flexible fin ray tail structure driven by a servo motor, to act as the soft body of the robot and provide the undulatory motion to the caudal fin of the fish. To address the modeling and control challenges, reinforcement learning (RL) is proposed as a model-free control strategy for the robot fish to swim and reach a specified target goal. By training and investigating the RL through experiments on real hardware, we illustrate the capability of the fish to learn and achieve the required task. © 2022, The Author(s).
Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control
Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Modeling of Soft Pneumatic Actuators with Different Orientation Angles Using Echo State Networks for Irregular Time Series Data
Modeling of soft robotics systems proves to be an extremely difficult task, due to the large deformation of the soft materials used to make such robots. Reliable and accurate models are necessary for the control task of these soft robots. In this paper, a data-driven approach using machine learning is presented to model the kinematics of Soft Pneumatic Actuators (SPAs). An Echo State Network (ESN) architecture is used to predict the SPA’s tip position in 3 axes. Initially, data from actual 3D printed SPAs is obtained to build a training dataset for the network. Irregularintervals pressure inputs are used to drive the SPA in different actuation sequences. The network is then iteratively trained and optimized. The demonstrated method is shown to successfully model the complex non-linear behavior of the SPA, using only the control input without any feedback sensory data as additional input to the network. In addition, the ability of the network to estimate the kinematics of SPAs with different orientation angles ? is achieved. The ESN is compared to a Long Short-Term Memory (LSTM) network that is trained on the interpolated experimental data. Both networks are then tested on Finite Element Analysis (FEA) data for other ? angle SPAs not included in the training data. This methodology could offer a general approach to modeling SPAs with varying design parameters. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
FPGA realization of fractals based on a new generalized complex logistic map
This paper introduces a new generalized complex logistic map and the FPGA realization of a corresponding fractal generation application. The chaotic properties of the proposed map are studied through the stability conditions, bifurcation behavior and maximum Lyapunov exponent (MLE). A relation between the mathematical analysis and fractal behavior is demonstrated, which enables formulating the fractal limits. A compact fractal generation process is presented, which results in designing and implementing an optimized hardware architecture. An efficient FPGA implementation of the fractal behavior is validated experimentally on Artix-7 FPGA board. Two examples of fractal implementation are verified, yielding frequencies of 34.593 MHz and 31.979 MHz and throughputs of 0.415 Gbit/s, 0.384 Gbit/s. Compared to recent related works, the proposed implementation demonstrates its efficient hardware utilization and suitability for potential applications. © 2021 Elsevier Ltd