Logic Applications Research Articles

MODIFIED FUZZY SPEED CONTROLLER OF INDUCTION MOTOR DRIVE USING EXTENDED KALMAN FILTERING

This paper focuses on application of fuzzy logic to enhance induction motor drive performance in case where the measured stator currents are distorted by Gaussian noise. For different load torques, the fixed proportional-integral (PI) speed controller provides an undesired drive performance for both transient and steady-state responses. At first, load torque is computed thanks to extended-Kalman-filtered stator currents. Next, load magnitude is employed to adjust the proportional gain and integral constant time of the fuzzy logic (FL) proportional-integral (PI) speed controller. Simulations of drive using two controllers: FL-PI and fixed PI ones, are carried out in different cases of stator current noise and load variation. Performance evaluations indicate that the FL-PI speed controller reduces the assessed indices and increases robustness to noise and load variation.

Bistable Soft Shells for Programmable Mechanical Logic.

Mechanical computing promises to integrate semiconductor-based digital logic in several applications, but it needs straightforward programmable devices for changing computing rules in situ. A methodology based on strain-governed, bistable soft shells that process digital information by interchanging their internal/external surfaces is proposed. This bistable behavior, explained via model-based design, safeguards robustness by working only once for each input pulse. Thus, these shells are leveraged to create a buffer and a NOT gate that lead to six fundamental gates (AND, OR, NAND, NOR, XOR, and XNOR). All these functions are integrated into a unique programmable device, making mechanically integrated circuits more adaptable with rule-changeable logic operations. This design ensures continuous processes and general applicability to multiple types of signals (a pressurized fluid can replace mechanical driving signals is shown). It also empowers more complex logic functions suitable for expanded applications, such as the half and full adders is addressed.

Voucher tokenisation using blockchain and smart contracts to support people in need

In South Africa, many people are homeless or doing informal work for which they receive small amounts of cash from caring individuals. The world is moving towards cashless transactions, but devices are needed to support that move. Many people in need cannot afford such devices and usually receive cash, but fewer donors carry cash. Consequently, people in need receive less informal financial support. We propose a system that allows donors to give digital vouchers that can be redeemed at participating stores and institutions of care. This study aimed to investigate the use of blockchain technology in digital voucher management and to demonstrate the application of smart contracts to disintermediate the value transfer process specific to the donation process. A demonstrator was built to include a front end for the user to interact with and a back end containing the application logic, which was built on the Polygon blockchain, a second-layer solution for the Ethereum blockchain. The model included tokenising vouchers as non-fungible tokens, and the smart contracts governed their logic and the conditions to be met. The demonstrator was validated using smart contract and unit tests to evaluate the security and functionality. While the model was not implemented in reality, a fully functioning demonstrator was developed. The platform achieved the aim of disintermediating the voucher management process. A real-world implementation could help many in need to receive tokens for food, shelter and clothing from direct, individual donors.

The Complementarity of Programme Logic and Critical Systems Heuristics: Critical Systems Practice for the Evaluation of Emergency Relief in Australia

ABSTRACTThe research aim was to improve the outcomes of Australia's Emergency Relief programme by applying the multiperspective multimethodological critical systems thinking and practice. Emergency Relief was designed as a short‐term intervention to assist people facing a financial crisis; however, it was evident and considered problematic that many beneficiaries had an ongoing reliance on the programme. The application of programme logic, the prevailing best practice approach to social services design and evaluation in Australia, demonstrated its strength by revealing opportunities to improve service delivery models through staff training, referral systems, colocation and case management. The application of critical systems heuristics revealed that unintended adverse consequences could result from ‘payment by outcomes’ commissioning and welfare conditionality. The research makes a methodological contribution to systems and evaluation literature by demonstrating the complementarity of programme logic and critical systems heuristics, and the strength in the multiperspective multimethodological approach of critical systems thinking and practice.

Application of Fuzzy Logic in Air Conditioner Temperature Control in Rooms with Partitions in Boarding Houses

This research investigates the application of fuzzy logic with the Mamdani method to regulate room temperature using an air conditioner (AC) in a boarding house environment with a partition at Bogor City, Indonesia. By considering variables such as room size, external temperature (weather), and air conditioner specifications, this research aims to achieve a balance between occupant comfort and energy efficiency. The optimal temperature for each room in the boarding house will be determined through fuzzy logic calculations. This research aims to open up new potentials in intelligent and sustainable temperature regulation in a boarding house or similar environment. This research method uses fuzzy logic for room temperature control using Matlab software.

Dual-gated MOSFETs of α-In2Se3 monolayer for high performance and low power logic applications

As a well-known van der Waals 2D material with entangled ferroelectricity and semiconductivity, α-In2Se3 has garnered significant attention in recent years to develop novel nonvolatile (photo) electronic devices mainly based on its ferroelectricity. However, the ability of its semiconductivity to design 2D transistors for high-performance (HP) and low-power (LP) logic applications remains unclear. Herein, this article reveals the potential of α-In2Se3 as a semiconductor in sub-10 nm 2D transistors. We analyze a dual-gated metal–oxide–semiconductor field-effect transistor (MOSFET) based on monolayer (ML) α-In2Se3 with a 5 nm channel-length, utilizing density functional theory (DFT) in combination with non-equilibrium Green’s function method. The transport performance indicators of n-type MOSFET along the zigzag direction can satisfy or nearly satisfy the HP and LP application requirements of the International Technology Roadmap for Semiconductor (ITRS) 2013, while p-type MOSFET along the armchair direction exhibits an outstanding on-current attributed to effective mass and the density of states modulation. The p-type MOSFETs also exhibit ultralow leakage current and subthreshold swing below 60 mV/dec. Meanwhile, our simulated MOSFETs demonstrate large on-current and high ON/OFF ratios. These findings highlight the application prospect of α-In2Se3 as a conventional 2D semiconductor material for further 2D FETs in HP and LP logic applications.

AI-Based Supply Chain Risk Management

As the complexity of global supply chains increases, supply chain risk management becomes increasingly important. The development of artificial intelligence (AI) technology provides new tools and methods for managing supply chain risks. This paper aims to review the application of AI in supply chain risk management, exploring current research progress, challenges, and future development trends. Through a systematic literature search and analysis, this paper examines relevant papers from databases such as Google Scholar, Web of Science, EI, and Scopus, discussing the specific applications of machine learning, deep learning, neural networks, fuzzy logic, genetic algorithms, and evolutionary algorithms in supply chain risk management. The study finds that these AI technologies demonstrate significant advantages in risk prediction, anomaly detection, image recognition, text mining, supply chain optimization, and emergency strategy formulation. However, issues related to data privacy and security, technical complexity, and implementation difficulties remain major challenges in current applications. In the future, as AI technology advances and interdisciplinary integration develops, supply chain risk management will have more opportunities. This study provides specific application suggestions for enterprises and decision-makers and points the way for future research.

Quantification of Interfacial Charges in Multilayered Nanocapacitors by Operando Electron Holography.

Interfaces in heterostructures play a major role in the functionality of electronic devices. Phenomena such as charge trapping/detrapping at interfaces under electric field affect the dynamics of metal/oxide/metal capacitors and metal/oxide/semiconductor transistors used for memory and logic applications. Charge traps are also key for the stabilization of a ferroelectric polarization and its ability to switch in ferroelectric devices such as ferroelectric tunnel junctions (FTJs). However, electric-field induced charging phenomena remain unclear even in conventional dielectric heterostructures due to a lack of direct measurement methods. Here, it is shown how operando off-axis electron holography can be used to quantify the charges trapped at the dielectric/dielectric interfaces as well as metal/dielectric interfaces in HfO2- and Al2O3-based nanocapacitors. By mapping the electrostatic potential at sub-nanometer spatial resolution while applying a bias, it is demonstrated that these interfaces present a high density of trapped charges, which strongly influence the electric field distribution within the device. The unprecedented sensitivity of the electron holography experiments coupled with numerical simulations highlights for the first time the linear relationship between the trapped charges at each interface and the applied bias, and the effect of the trapped charges on the local electrical behavior.

Prediction of seam strength of cotton canvas fabric using fuzzy logic

This study investigates the application of fuzzy logic in predicting seam strength in cotton plain canvas fabric, focusing on both warp and weft directions. The precise prediction of seam strength is crucial for manufacturers to uphold quality standards, enhance production efficiency, and minimize waste. The fuzzy logic model in this study uses thread linear density and stitch per inch as input parameters and warp and weft seam strength as output variables. The modeling was conducted using MATLAB, specifically utilizing the Mamdani fuzzy inference system with triangle membership functions. The fuzzy logic model was found to be very accurate, as shown by coefficients of determination (R2) of 0.9841 for the warp way and 0.9888 for the weft way, along with correlation coefficients (R) of 0.992 and 0.9944. The mean absolute percentage error (MAPE) was calculated to be 4.8719 % for the warp way and 4.7561 % for the weft way, each below 5 %, underscoring the model's reliability and robustness in seam strength prediction. This research provides findings with substantial implications for the textile industry, where the application of predictive models is on the rise to enhance production efficiency and product quality. Manufacturers can improve their ability to forecast regarding fabric properties and adjust production processes through the implementation of fuzzy logic models. This approach is consistent with current industry trends emphasizing automation and digitalization, wherein predictive models are essential for facilitating smart manufacturing and quality control.

Field-free spin–orbit torque devices for logic and neural network applications

Field-free spin–orbit torque devices for logic and neural network applications

Guided motion of a magnetic skyrmion by a voltage-controlled strained channel, and logic applications

Guided motion of a magnetic skyrmion by a voltage-controlled strained channel, and logic applications

Geophysical Methods Applied to the Mineralization Discovery of Rare-Earth Elements at the Fazenda Buriti Alkaline Complex, Goiás Alkaline Province, Brazil

In this case study, exploratory techniques were applied for the selection of potential targets for rare-earth elements (REEs) in the Fazenda Buriti Mafic–Ultramafic Complex, part of the Goiás Alkaline Province. The results of the processing and interpretation of aeromagnetic and radiometric data associated with the direct measurements of magnetic susceptibility and radiometry in rock samples collected in the study area allowed for the characterization and delimitation of the geological units. The application of Boolean logic in the radiometric data of uranium (U), thorium (Th), and the U/Th ratio allowed for the generation of a prospective map with the delimitation of two exploration targets. A 100 m deep exploratory drill hole was drilled at the main target, intercepting REE mineralization and validating the developed prospective technique. The results contributed to the detailing of a 1:25,000 scale geological map and the interpretation of shallow and deep magnetic structures. Petrophysical data allowed for the estimation of the magnetite content in the main units of the study area. The delimitation of targets with the applied method proved to be efficient after positive geochemical results for REE from the drilled rocks. The total sum of ∑REEs reached 19,629 ppm in the superficial part of the hole and 3,560 ppm in the fresh rock. Mineralogical results in two follow-up drill core samples indicated that monazite was the main REE mineral. Total REE ranged from 34,746 ppm in HG1 to 30,017 ppm in HG2, with LREEs in its majority. The bulk and clay XRD analyses indicated that monazite consisted of 5.7% (HG1) and 5.1% (HG2). The mineral abundance from the TIMA-X analysis indicated 4.2% (HG1) and 4.4% (HG2) in monazite content.

Evolving to find optimizations humans miss: using evolutionary computation to improve GPU code for bioinformatics applications

GPUs are used in many settings to accelerate large-scale scientific computation, including simulation, computational biology, and molecular dynamics. However, optimizing codes to run efficiently on GPUs requires developers to have both detailed understanding of the application logic and significant knowledge of parallel programming and GPU architectures. This paper shows that an automated GPU program optimization tool, GEVO, can leverage evolutionary computation to find code edits that reduce the runtime of three important applications, multiple sequence alignment, agent-based simulation and molecular dynamics codes, by 28.9%, 29%, and 17.8% respectively. The paper presents an in-depth analysis of the discovered optimizations, revealing that (1) several of the most important optimizations involve significant epistasis, (2) the primary sources of improvement are application-specific, and (3) many of the optimizations generalize across GPU architectures. In general, the discovered optimizations are not straightforward even for a GPU human expert, showcasing the potential of automated program optimization tools to both reduce the optimization burden for human domain experts and provide new insights for GPU experts.

Fuzzy logic as a method of analysis of hot forging process of 80MnSi8-6 steel

A novel approach was proposed, based on the application of the fuzzy logic (FL) method for the fast analysis of the hot deformation process of 80MnSi8-6 steel. In the first stage, the curves developed from plastometric tests and the results of studies of the microstructure of the deformed samples were used as input data for the analysis. Input and output variables were adopted and a set of rules based on cause-and-effect relationships was defined, defining the interactions between the variables. A fast FL-controller was designed, and the correctness of its operation was verified by comparison with experimental results and the results of finite element method (FEM) analysis, carried out taking into account the evolution of the microstructure. The process of hot compression under isothermal conditions of 80MnSi8-6 steel specimens was simulated on the Warmumformsimulator (WUMSI), assuming such parameters and other conditions as were used in real tests. It was confirmed that the proposed method, based on the analysis of flow curves and prior austenite grain size using a fuzzy controller, gave satisfactory results. Subsequently, a novel FL-controller was developed to analyze the kinetics of dynamic recrystallization (DRX), using data obtained from the author’s model of this phenomenon for its construction and calibration. The correctness of the controller was confirmed by comparing the results of its DRX volume fraction calculations with the distributions of this value determined by the model and the model-based FEM analysis method, respectively. It was shown that FL is applicable also when a model of the analyzed phenomenon is available. Unlike model-based calculations, a properly designed controller allows the indication of deviations from general trends that can be pointed out and interpreted by a human expert, but significantly faster. It can also serve as a component of a system analyzing complex processes, such as hot multi-stage forging. Fuzzy controller can be used in parallel with modeling or replace models in calculations.

Breaking the digitalization barrier for SMEs: a fuzzy logic approach to overcoming challenges in business transformation

The purpose of this study was to investigate the barriers and drivers of digitalization in small- and medium-sized enterprises (SMEs). Specifically, the study aimed to identify the key factors influencing the adoption and implementation of digital technologies in SMEs, understand the challenges faced by these organizations in their digital transformation journey. In this study, a fuzzy logic methodology was employed to assess the digitalization process of 4531 SMEs. Additionally, an analytical hierarchy process (AHP) was applied to determine the weights of the dimensions in the fuzzy analysis. This allowed for a more accurate and precise assessment of the digitalization levels in SMEs. Furthermore, statistical analysis techniques were utilized to analyze the data and draw meaningful conclusions. The study revealed that insufficient financial resources, high investment costs, resistance from workers, a shortage of well-qualified staff, lack of knowledge about technology providers, high IT security requirements, the absence of a digital transformation-oriented business culture, and the application of fuzzy logic as a methodology were the key findings in the digitalization process of SMEs. These findings highlight the complex challenges faced by SMEs and emphasize the need to address these barriers to facilitate successful digital transformation.

Enhancing Urban Traffic Flow Through Fuzzy Logic-Based Signal Light Control Optimization

Urban traffic congestion is an urgent problem, which is aggravated by the fixed-time urban traffic signal control system. In order to solve this problem, optimization based on fuzzy logic provides flexibility to adapt to real-time traffic conditions. This study discusses the application of fuzzy logic in traffic control and puts forward the optimization scheme of urban traffic light system, including the design of fuzzy controller, the formulation of fuzzy rules, and the system implementation. The results show that compared with the traditional method, the traffic flow and efficiency have been improved, which shows that it has great potential in the real world. By considering the dynamic characteristics of traffic conditions, this method can realize a more flexible and effective control strategy. It is possible to significantly improve the quality of urban transportation system by implementing this method in real scenes.

PLC/HMI Based Portable Workbench for PLC and Digital Logic Learning and Application Development

A Programmable logic controller (PLC) uses the digital logic circuits and their operating concepts in its hardware structure and its programming instructions and algorithms. Therefore, the deep understanding of these two items is staple for the development of control applications using the PLC. This target is only possible through the practical sensing of the various components or instructions of these two items and their applications. In this work, a user-friendly and re-configurable ladder, digital logic learning and application development design and testing platform has been designed and implemented using a Programmable Logic Controller (PLC), Human Machine Interface panel (HMI), four magnetic contactors, one Single-phase power line controller and one Variable Frequency Drive (VFD) unit. The PLC role is to implement the ladder and digital logic functions. The HMI role is to establish the virtual circuit wiring and also to drive and monitor the developed application in real time mode of application. The magnetic contactors are to play the role of industrial field actuators or to link the developed application control circuit to another field actuator like three phase induction motor. The Single -phase power line controller is to support an application like that of the soft starter. The VFD is to support induction motor driven applications like that of cut-to-length process in which steel coils are uncoiled and passed through cutting blade to be cut into required lengths. The proposed platform has been tested through the development of 14 application examples. The test results proved the validity of the proposed platform.

Nash meets Łukasiewicz: computing equilibria through logic

Abstract A Nash equilibrium is a strategy profile of a game in which none of the players involved has any gain by changing alone his/her own strategy. Given a two-player game, we show a codification of all of its Nash equilibria into Łukasiewicz infinitely-valued logic, that is, we derive a propositional theory in this logic whose models codify all the Nash equilibria. Based on such propositional theory, we derive a polynomial reduction from the problem of computing a Nash equilibrium to the problem of satisfiability of (sets of) formulas of Łukasiewicz infinitely-valued logic. These applications of logic to game theory lead to new methods for computing Nash equilibria.

Substantially Enhanced Spin Polarization in Epitaxial CrTe2 Quantum Films.

2D van der Waals (vdW) magnets, which extend to the monolayer (ML) limit, are rapidly gaining prominence in logic applications for low-power electronics. To improve the performance of spintronic devices, such as vdW magnetic tunnel junctions, a large effective spin polarization of valence electrons is highly desired. Despite its considerable significance, direct probe of spin polarization in these 2D magnets has not been extensively explored. Here, using 2D vdW ferromagnet of CrTe2 as a prototype, the spin degrees of freedom in the thin films are directly probed using Mott polarimetry. The electronic band of 50 ML CrTe2 thin film, spanning the Brillouin zone, exhibits pronounced spin-splitting with polarization peaking at 7.9% along the out-of-plane direction. Surprisingly, atomic-layer-dependent spin-resolved measurements show a significantly enhanced spin polarization in a 3 ML CrTe2 film, achieving 23.4% polarization even in the absence of an external magnetic field. The demonstrated correlation between spin polarization and film thickness highlights the pivotal influence of perpendicular magnetic anisotropy, interlayer interactions, and itinerant behavior on these properties, as corroborated by theoretical analysis. This groundbreaking experimental verification of intrinsic effective spin polarization in CrTe2 ultrathin films marks a significant advance in establishing 2D ferromagnetic atomic layers as a promising platform for innovative vdW-based spintronic devices.

WS2 Nanotube Transistor for Photodetection and Optoelectronic Memory Applications.

Nanotube and nanowire transistors hold great promises for future electronic and optoelectronic devices owing to their downscaling possibilities. In this work, a single multi-walled tungsten disulfide (WS2) nanotube is utilized as the channel of a back-gated field-effect transistor. The device exhibits a p-type behavior in ambient conditions, with a hole mobility µp ≈ 1.4 cm2V-1s-1 and a subthreshold swing SS ≈ 10 V dec-1. Current-voltage characterization at different temperatures reveals that the device presents two slightly different asymmetric Schottky barriers at drain and source contacts. Self-powered photoconduction driven by the photovoltaic effect is demonstrated, and a photoresponsivity R ≈ 10 mAW-1 at 2V drain bias and room temperature. Moreover, the transistor is tested for data storage applications. A two-state memory is reported, where positive and negative gate pulses drive the switching between two different current states, separated by a window of 130%. Finally, gate and light pulses are combined to demonstrate an optoelectronic memory with four well-separated states. The results herein presented are promising for data storage, Boolean logic, and neural network applications.