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Although shared leadership is typically considered a beneficial leadership approach, findings reporting its effectiveness are mixed. By integrating implicit theory and the "Too-Much-of-a-Good-Thing" (TMGT) effect, this study hypothesizes that both too little and too much shared leadership restrict team creativity and employee creativity. We test such double threshold logic across three independent studies. Study 1 results reveal that shared leadership can promote team creativity, but only within a certain range. Results from Study 2 suggest that shared leadership is positively related to employee creativity, but again only within a certain range. Study 3 replicates the findings of Study 1 and Study 2, and reveals that shared leadership is unrelated to employee creativity when team collectivism is high. Together, these findings suggest that there is a double-threshold effect of shared leadership on employee creativity and team creativity, and that the double-threshold effect of shared leadership on employee creativity is moderated by team collectivism. [ABSTRACT FROM AUTHOR]

In this article, an optical majority/minority circuit has been designed using four electro‐optic Mach‐Zehnder interferometers. The binary decision diagram (BDD) is used to optimize the Boolean logical expression. In this design we get two outputs, one performs majority logic and the other performs minority logic simultaneously. Numerical simulation has been done with the obtained data from the beam propagation method. Pseudo‐eye diagram is also plotted to find amplitude modulation (AM) and extinction ratio (ER). AM and ER are found nearly 0.4 and 13 dB, respectively. A new parameter, the optical circuit complexity factor (OCC) factor has been calculated and from the result, it has been shown that the proposed design is more optimized than other majority/minority gate designs so far. [ABSTRACT FROM AUTHOR]

Environmental protection and energy conservation have become highly concerning themes. In the transportation field, green electric vehicles (EVs) are rapidly being promoted and applied, and power sources, as one of the core technologies, greatly affect the working performances of EVs. Currently, a single battery power supply is the mainstream configuration for EVs, but the instantaneous/short-term high-power output required by the battery for vehicle working conditions has a serious impact on the service life of the battery. As an effective solution, the battery/super-capacitor (SC) hybrid power source (HPS) has attracted increasing attention. This article proposes an improved semi-active battery/SC HPS, which can achieve multiple operating modes and fully utilize the advantages of the two power sources to effectively protect the battery. A fitness function is established with the optimization objective of minimizing the HPS cost and the number of cells in SC and battery as control variables. A genetic algorithm (GA) is adopted to optimize the HPS configuration based on the power required of the New European Driving Cycle (NEDC) working condition. The optimized number of battery cells is 777, much smaller than the 1191 calculated based on theoretical formulas. Additionally, a logic threshold strategy is introduced to flexibly control the collaborative work of the two power sources and achieve effective energy management. The availability of the presented control method of HPS in various working modes is verified through MATLAB/Simulink-based modeling and simulation. This work provides a theoretical reference for the application research of HPS in EVs. [ABSTRACT FROM AUTHOR]

Memorizing nanodrives are distinguished by a large variety of majority trigger structures, which are the basic fragments of the the nanocircuit of a high integration level. The paper describes the synthesis of reliable sequential nanodevices of single- electronics based on the technology of quantum cellular automata. When constructing majority nano-circuits with memory, the theory of finite automata is used. The order of computer design of different types of arithmetic and logic nanodevices is analyzed. High-speed parallel-acting and paraphase control nanoregisters control are created. [ABSTRACT FROM AUTHOR]

In this article, the authors proposed a family of recognition algorithms based on k-dimensional threshold rules and focused on the object recognition presented in the feature space of high dimension. These recognition algorithms are based on the concept of forming a set of k-dimensional preferred threshold rules that define an extremal algorithm within the proposed family of algorithms. A structural description of the developed family of recognition algorithms is given, presented as a sequence of computational procedures. The main ones are the procedures for determining a set of representative features; discriminant functions for each class; normalizing transformations; groups of highly correlated discriminant functions; basic discriminant functions; a set of preferred discriminant functions; a generalized recognition operator based on preferred discriminant functions. The results of experimental studies are presented; they showed that an increase in the accuracy of recognition results is provided (in comparison with known analogs) when using the indicated family of recognition algorithms. The main advantage of the proposed recognition algorithms is not only an increase in accuracy but also a significant reduction in arithmetic operations in object recognition. This property of the algorithms makes it possible to create various software recognition systems that operate in real time. [ABSTRACT FROM AUTHOR]

In this work, a complementary metal‐oxide‐semiconductor (CMOS) based leaky‐integrate and fire neuron has been proposed and investigated for neuromorphic applications. The neuron has been designed in Cadence Virtuoso and validated experimentally. It has been observed that the neuron consumes a maximum energy of 68.87 fJ/spike. The response of the neuron to excitatory as well as inhibitory inputs has been studied. To verify the applicability, the proposed neuron has been explored for reconfigurable threshold logic to implement various linearly separable Boolean functions including OR, AND, NOT, NOR, and NAND. Moreover, the threshold tunability of the neuron has also been verified and this property has been exploited to design threshold‐controlled logic gates. Instead of adjusting the weights of the applied inputs, the functionality of such gates can be controlled by changing the threshold of the neuron, simplifying the synaptic architecture of a neural network. Finally, a multilayer network has been designed and the recognition ability of the proposed network for MNIST handwritten digits has been verified with an accuracy of 96.93%. [ABSTRACT FROM AUTHOR]

Reducing delay, power consumption, and chip area of a logic circuit are the main targets of a digital circuit designer. Most of the times, the designer sacrifices power consumption and chip area to decrease delay for a given technology node. To overcome this problem, we propose the ternary threshold logic gate. We have implemented the proposed gate by combining the threshold logic with the ternary logic. Then, we have constructed basic building blocks of a ternary ALU (as ternary logic gates, comparator, and arithmetic circuits) using the proposed ternary threshold logic gate. We have compared these building blocks and implemented with the proposed gate, with the ones implemented using different technologies. Via simulations, we have shown that the proposed gate may be utilized to decrease delay, power consumption, and chip area of ternary circuits. Thus, the proposed ternary threshold logic gate can be used to decrease delay, power consumption, and chip area of ternary circuits. [ABSTRACT FROM AUTHOR]

Utilizing magnetic tunnel junctions (MTJs) for write/read and fast spin-orbit-torque (SOT)-driven domain-wall (DW) motion for propagation, enables non-volatile logic and majority operations, representing a breakthrough in the implementation of nanoscale DW logic devices. Recently, current-driven DW logic gates have been demonstrated via magnetic imaging, where the Dzyaloshinskii-Moriya interaction (DMI) induces chiral coupling between perpendicular magnetic anisotropy (PMA) regions via an in-plane (IP) oriented region. However, full electrical operation of nanoscale DW logic requires electrical write/read operations and a method to pattern PMA and IP regions compatible with the fabrication of PMA MTJs. Here, we study the use of a Hybrid Free Layer (HFL) concept to combine an MTJ stack with DW motion materials, and He+ ion irradiation to convert the stack from PMA to IP. First, we investigate the free layer thickness dependence of 100-nm diameter HFL-MTJ devices and find an optimal CoFeB thickness, from 7 to 10 Å, providing high tunneling magnetoresistance (TMR) readout and efficient spin-transfer torque (STT) writing. We then show that high DMI materials, like Pt/Co, can be integrated into an MTJ stack via interlayer exchange coupling with the CoFeB free layer. In this design, DMI values suitable for SOT-driven DW motion are measured by asymmetric bubble expansion. Finally, we demonstrate that He+ irradiation reliably converts the coupled free layers from PMA to IP. These findings offer a path toward the integration of fully electrically controlled DW logic circuits. [ABSTRACT FROM AUTHOR]

For many years, chaotic maps have been widely used in the design of various algorithms in cryptographic systems. In this paper, a new model (compound chaotic system) of quantum random walks controlled by a hyper-chaotic map is constructed and a novel scheme for constructing a dynamic S-Box based on the new model is proposed. Through aperiodic evaluation and statistical complexity measurement, it is shown that the compound chaotic system has features such as complex structure and stronger randomness than classical chaotic systems. Based on the chaotic sequence generated by the composite system, we design a dynamic S-Box generation mechanism. The mechanism can quickly generate high-security S-Boxes. Then, an example of randomly generating S-Boxes is given alongside an analytical evaluation of S-Box standard performance criteria such as bijection, boomerang uniformity, bit independence, nonlinearity, linear approximate probability, strict avalanche effect, differential uniformity, the and generalized majority logic criterion. The evaluation results confirm that the performance of the S-Box is excellent. Thus, the proposed dynamic S-Box construction technique can be used to generate cryptographically strong substitution-boxes in practical information security systems. [ABSTRACT FROM AUTHOR]

A scientific and rational evaluation of teaching is essential for personalized learning. In the current teaching assessment model that solely relies on Grade Point Average (GPA), learners with different learning abilities may be classified as the same type of student. It is challenging to uncover the underlying logic behind different learning patterns when GPA scores are the same. To address the limitations of pure GPA evaluation, we propose a data-driven assessment strategy as a supplement to the current methodology. Firstly, we integrate self-paced learning and graph memory neural networks to develop a learning performance prediction model called the self-paced graph memory network. Secondly, inspired by outliers in linear regression, we use a t-test approach to identify those student samples whose loss values significantly differ from normal samples, indicating that these students have different inherent learning patterns/logic compared to the majority. We find that these learners' GPA levels are distributed across different levels. Through analyzing the learning process data of learners with the same GPA level, we find that our data-driven strategy effectively addresses the shortcomings of the GPA evaluation model. Furthermore, we validate the rationality of our method for student data modeling through protein classification experiments and student performance prediction experiments, it ensuring the rationality and effectiveness of our method. [ABSTRACT FROM AUTHOR]

This work aims to present a novel energy-efficient single transistor leaky integrate-and-fire neuron for future neuromorphic computing. It comprises of a SiGe-based MOSFET, having channel length of 400 nm. Using 2D simulation, it has been verified that the proposed SiGe-based single transistor neuron accurately mimics the spiking behavior of the biological neuron, while eliminating the need of external circuitry and exorbitant energy consumption. The neuron consumes energy of 3.8 pJ/spike, which is 11.8 times and 2.1 times lesser than the previously proposed Si-based and Ge-based single transistor neurons, respectively. It also shows improvement in terms of controllability, simplicity, integration density, and fabrication process. By designing threshold logic gates, the proposed neuron has been employed to implement universal digital logic functions, such as NAND and NOR. Finally, the recognition ability for MNIST handwritten digits has been verified. It has been confirmed that besides imitating the neuronal behavior accurately, the proposed neuron can also be used in practical spiking neural networks for image classification with an accuracy of 93.79%. [ABSTRACT FROM AUTHOR]

In this study, an all-optical multiplexer (Mux) based on elliptical insulator-metal-insulator (IMI) plasmonic waveguides is designed. The area of the proposed structure is very small (400 nm × 400 nm) which operates at a wavelength of 1,550 nm. The developed device utilizes constructive and destructive interferences between the input signals and the selector signal. This structure is less complex and has lower loss compared to the previous works. Transmission (T), contrast ratio (CR), modulation depth (MD), insertion loss (IL), and contrast loss (CL) are the five parameters that describe the performance of the plasmonic Mux. The transmission threshold between logic 0 and logic 1 is 0.5. Moreover, the maximum transmission efficiency of the device is 163%. Moreover, based on the MD value of 95.09%, the dimensions of the proposed structure are excellent and optimal. The proposed plasmonic Mux structure contributes substantially to developing an all-optical arithmetic logic unit (ALU) and all-optical signal processing nanocircuits. The finite element method (FEM) simulates the proposed plasmonic multiplexer with COMSOL Multiphysics 5.4 software. [ABSTRACT FROM AUTHOR]

Superconducting electronics are among the most promising alternatives to conventional CMOS technology, thanks to the ultra-fast speed and ultra-high energy efficiency of the superconducting devices. Having a cryogenic control processor is also a crucial requirement for scaling the existing quantum computers up to thousands of qubits. Despite showing outstanding speed and energy efficiency, Josephson junction-based circuits suffer from several challenges such as flux trapping leading to limited scalability, difficulty in driving high impedances, and so on. Three-terminal cryotron devices have been proposed to solve these issues, which can drive high impedances (> 100 k Ω) and are free from any flux trapping issue. In this work, we develop a reconfigurable logic circuit using a heater cryotron (hTron). In conventional approaches, the number of devices to perform a logic operation typically increases with the number of inputs. However, here, we demonstrate a single hTron device-based logic circuit that can be reconfigured to perform 1-input copy and NOT, 2-input AND and OR, and 3-input majority logic operations by choosing suitable biasing conditions. Consequently, we can perform any processing task with a much smaller number of devices. Also, since we can perform different logic operations with the same circuit (same layout), we can develop a camouflaged system where all the logic gates will have the same layout. Therefore, this proposed circuit will ensure enhanced hardware security against reverse engineering attacks. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, three kinds of three-input logic gates are designed based on DNA strand displacement reaction, which are three-input OR logic gate, three-input AND logic gate, and three-input MAJORITY logic gate. The logic gates designed in this paper takes different DNA strands as input and fluorescence signals as output. The biochemical experimental results verify my designs. The results show that DNA strand displacement technology has important application value in DNA computing, especially in the construction of DNA molecular logic gates. [ABSTRACT FROM AUTHOR]

Discrete Hopfield Neural Network is widely used in solving various optimization problems and logic mining. Boolean algebras are used to govern the Discrete Hopfield Neural Network to produce final neuron states that possess a global minimum energy solution. Non-systematic satisfiability logic is popular due to the flexibility that it provides to the logical structure compared to systematic satisfiability. Hence, this study proposed a non-systematic majority logic named Major 3 Satisfiability logic that will be embedded in the Discrete Hopfield Neural Network. The model will be integrated with an evolutionary algorithm which is the multi-objective Election Algorithm in the training phase to increase the optimality of the learning process of the model. Higher content addressable memory is proposed rather than one to extend the measure of this work capability. The model will be compared with different order logical combinations 1= 3,2, 1= 3,2,1 and 1= 3,1. The performance of those logical combinations will be measured by Mean Absolute Error, Global Minimum Energy, Total Neuron Variation, Jaccard Similarity Index and Gower and Legendre Similarity Index. The results show that 1= 3,2 has the best overall performance due to its advantage of having the highest chances for the clauses to be satisfied and the absence of the first-order logic. Since it is also a non-systematic logical structure, it gains the highest diversity value during the learning phase. [ABSTRACT FROM AUTHOR]

The traditional traction control system (TCS) based on hydraulic braking only works when the wheels are slipping, which will cause the problem of slow response to extreme slip. In addition, the TCS of four‐wheel‐independent‐drive electric vehicle (4WIDEV) is often based on road adhesion characteristics identification or optimal slip ratio identification to implement active control, which is difficult to achieve in engineering. Aiming at this problem, a practical active TCS is proposed in this paper. Firstly, according to the wheel slip state of the front and rear axles, the dynamic transfer of torque between axles is realized to maintain the vehicle propulsion power. Second, the adhesion conditions between road and tire are classified, and two sets of target slip ratio thresholds are formulated for high and low adhesion pavement, respectively. Then the current road adhesion coefficient is estimated by using the advantage that the in‐wheel motor torque can be obtained in real‐time. Thirdly, the overall framework of the control strategy is established, the logic threshold control algorithm is adopted for tracking the wheel target slip ratio. Finally, the simulation results show that the proposed active TCS can improve the vehicle power and avoid excessive wheel slipping. [ABSTRACT FROM AUTHOR]

This work presents a study on the reliability of voters for approximate fault tolerant systems in the context of single event effects and electromagnetic interference. A first case study analyses different topologies of single-bit majority voters for logic circuits employing fault injection by simulation. In these simulations, an analysis is first performed to identify the critical diffusion areas of the physical implementation according to the voter input vector. Additionally, as a second case study, practical heavy ion experiments on different architectures of software-based approximate voters for mixed-signal applications are also presented, and the cross section of each voter is evaluated. The system comprising the voters was irradiated in two distinct experiments with an 16 O ion beam, producing an effective LET at the active region of 5.5 MeV/mg/cm 2 . As a complementary study, a conducted electromagnetic interference injection was also performed, considering two distinct voting schemes. Results of the case-studies allow identifying the most tolerant voter architectures (among the studied ones) for approximate computing applications under single event effects and electromagnetic interference. [ABSTRACT FROM AUTHOR]

In recent years, with the increasing severity of energy and environmental issues, countries have vigorously developed the new energy automotive industry. To reduce the difficulty of driver operation and increase endurance mileage, this article proposes a regenerative braking control strategy for a single-pedal pure electric commercial vehicle. Firstly, the single-pedal control system's hierarchical approach was designed to contain the driver's intention analysis and torque calculation layers. After identifying the driver's intention, a logic threshold method was used to determine the braking pattern. Then, a fuzzy theory was used, with road gradient, braking strength, and speed as input parameters, and the ratio coefficient of braking force as the output parameter. A hybrid regenerative braking strategy was formulated based on the ideal distribution curve. Finally, the proposed strategy was verified through simulation and a constant-speed car-following experiment. The constant-speed car-following experiment results show that the maximum optimization rate of energy consumption provided by the proposed single-pedal regenerative braking control strategy is 5.81%, and the average optimization rate is 4.33%. This strategy can effectively reduce energy consumption and improve the economic performance of single-pedal pure electric commercial vehicles. [ABSTRACT FROM AUTHOR]

The work considers controversial problems with the introduction of specialized and at the same time universal large integrated circuits, which are clarified at the initial stages of automated hierarchical design. Universal micro- and nanocircuits with configurable logic are created in the article to increase the efficiency of automated design systems. The article provides effective methods of programming multiplexer micro- and nanocircuits with configured logic for implementing Boolean and majority logic functions. The obtained results are used to configure the multiplexer functional blocks. With the help of modern automated design systems, comparative modeling of logic micro- and nanocircuits with configured logic was performed, which proved the adequacy of their functioning, the advantages of frequency and disadvantages of temperature characteristics of nanomultiplexer circuits. [ABSTRACT FROM AUTHOR]

The total ionizing dose (TID) effect significantly impacts the electrical parameters of fully depleted silicon on insulator (FDSOI) devices and even invalidates the on–off function of devices. At present, most of the irradiation research on the circuit level is focused on the single event effect, and there is very little research on the total ionizing dose effect. Therefore, this study mainly analyzes the influence of TID effects on a CMOS inverter circuit based on 22 nm FDSOI transistors. First, we constructed and calibrated an N-type FDSOI metal-oxide semiconductor (NMOS) structure and P-type FDSOI metal-oxide semiconductor (PMOS) structure. The transfer characteristics and trapped charge distribution of these devices were studied under different irradiation doses. Next, we studied the TID effect on an inverter circuit composed of these two MOS transistors. The simulation results show that when the radiation dose was 400 krad (Si), the logic threshold drift of the inverter was approximately 0.052 V. These results help further investigate the impact on integrated circuits in an irradiation environment. [ABSTRACT FROM AUTHOR]

Over the past two decades, voluntary sustainability standards (VSS) have emerged as instruments to improve social and environmental practices and to communicate sustainability standards in trade and business. However, debates about the correct assessment methodology for VSS risk causing duplication, overlaps, and fragmentation, undermining the value of VSS in sustainability transition. In this paper I propose materiality, theory of change and reflexive governance as the three building blocks of an appropriate framework for VSS and other sustainability assessment schemes in the food and agricultural sectors. Materiality is the specific criteria for defining and assessing factors that matter for sustainability, such as indicators, metrics, and rankings. Materiality is a process of social construction that enables stakeholder engagement and integrated knowledge production, going beyond just benchmarking entities against their competitors using standardized measures. Theory of change is a method that explains how interventions lead to desired outcomes and changes but is much more than a linear logic model of inputs and outputs. It sheds light on underlying assumptions, embedded contexts and long- and short-term dynamics. Reflexive evaluation consists of a single-loop process that follows a problemdetection-correction course and double- and triple-loop learning that allows assumptions and learned propositions to be challenged. It highlights unintended outcomes and offers alternatives to conducting interventions, which is different from conventional monitoring and evaluation methods, which focus on measuring the attainment of intended outcomes only. The study concludes that the semantic meaning of "standards" and "assessment" in agricultural VSS abstract the complex nature of sustainability because of overly linear meaning. In the complex construct of sustainability assessment, the role of VSS is not to conclude a success or a failure but to encourage knowledge-based learning and accountable governance because social change is an open-ended validation and adaption process. The framework proposed by this paper offers a solution by calling for integrated knowledge production resulting from interdisciplinary assessments and learning-oriented actions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The safety, comfort, and energy feedback of active suspension in a single control mode is mutually restricted. To meet the needs of drivers and passengers for vehicle driving performance under different road conditions, this paper proposes a multi-mode switching control strategy of an intelligent suspension system, aiming at improving the stability and comfort of vehicles under different road conditions. In this paper, the adaptive Kalman filter algorithm with a forgetting factor is used to estimate the road input. The accuracy of the algorithm in estimating the road input is verified by simulation and experiment. The single-double threshold logic judgment method is used to formulate the switching rules between each working mode. In the controller, the PID control of the BP neural network and the LQR control optimized by GA are used to optimize and adjust the vehicle driving performance indexes in different modes, which effectively solves the problem of limited adaptability of suspension control optimization objectives under different road driving conditions. Based on the data from the vehicle acceleration sensor and road condition sensor, the modeling and simulation of the switching control system are carried out. The simulation results show that the designed control system can effectively improve the comprehensive performance of the vehicle under different road driving conditions. Compared with the traditional active suspension, the body acceleration is increased by 26% on the B-grade road surface, which effectively improves the user's ride comfort. Compared with the traditional active suspension, the tire dynamic displacement is increased by 24% on the D-grade road, which can significantly improve the overall performance of the vehicle and meet the design requirements of the system. [ABSTRACT FROM AUTHOR]

Magnetic skyrmions are topologically protected spin textures and they are suitable for future logic-in-memory applications for energy-efficient, high-speed information processing and computing technologies. In this work, we have demonstrated skyrmion-based 3 bit majority logic gate using micromagnetic simulations. The skyrmion motion is controlled by introducing a gate that works on voltage controlled magnetic anisotropy. Here, the inhomogeneous magnetic anisotropy behaves as a tunable potential barrier/well that modulates the skyrmion trajectory in the structure for the successful implementation of the majority logic gate. In addition, several other effects such as skyrmion–skyrmion topological repulsion, skyrmion-edge repulsion, spin–orbit torque and skyrmion Hall effect have been shown to govern the logic functionalities. We have systematically presented the robust logic operations by varying the current density, magnetic anisotropy, voltage-controlled gate dimension and geometrical parameters of the logic device. The skyrmion Hall angle is monitored to understand the trajectory and stability of the skyrmion as a function of time in the logic device. The results demonstrate a novel method to achieve majority logic by using voltage controlled magnetic anisotropy which further opens up a new route for skyrmion-based low-power and high-speed computing devices. [ABSTRACT FROM AUTHOR]

Vortex beams with optical orbital angular momentum have broad prospects in future high-speed and large-capacity optical communication. In this investigation of materials science, we found that low-dimensional materials have feasibility and reliability in the development of optical logic gates in all-optical signal processing and computing technology. We found that spatial self-phase modulation patterns through the MoS2 dispersions can be modulated by the initial intensity, phase, and topological charge of a Gauss vortex superposition interference beam. We utilized these three degrees of freedom as the input signals of the optical logic gate, and the intensity of a selected checkpoint on spatial self-phase modulation patterns as the output signal. By setting appropriate thresholds as logic codes 0 and 1, two sets of novel optical logic gates, including AND, OR, and NOT gates, were implemented. These optical logic gates are expected to have great potential in optical logic operations, all-optical networks, and all-optical signal processing. [ABSTRACT FROM AUTHOR]

In the context of computing in resistive memories (ReRAM), the implementation of threshold logic gates (TLGs) with memristors has been especially investigated for programable in-memory logic implementations. In this work we focus on two circuit design concepts for threshold logic with memristors: the voltage divider and the voltage adder. We provide an analytical exploration of the impact of the HRS-to-LRS ratio of memristors on the performance of every circuit and highlight the advantages of the voltage adder approach. Through experimental results from a proof-of-concept circuit, implemented using self-directed channel (SDC) memristors by Knowm Inc., we validated the conclusions derived from the theoretical analysis for computational memory structures supporting threshold logic gates. Moreover, we present the design and simulation of a bitline driver and sensing circuitry for a 1T1R array, where the proposed threshold logic scheme can seamlessly fit, thus providing solutions towards the development of robust and reliable computational ReRAM modules. [ABSTRACT FROM AUTHOR]

This paper considers the structure consisting of the set of all words over a given alphabet together with the subword relation, regular predicates, and constants for every word. We are interested in the counting extension of first-order logic by threshold counting quantifiers. The main result shows that the two-variable fragment of this logic can be decided in twofold exponential alternating time with linearly many alternations (and therefore in particular in twofold exponential space as announced in the conference version (Kuske and Schwarz, in: MFCS'20, Leibniz International Proceedings in Informatics (LIPIcs) vol. 170, pp 56:1–56:13. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020) of this paper) provided the regular predicates are restricted to piecewise testable ones. This result improves prior insights by Karandikar and Schnoebelen by extending the logic and saving one exponent in the space bound. Its proof consists of two main parts: First, we provide a quantifier elimination procedure that results in a formula with constants of bounded length (this generalises the procedure by Karandikar and Schnoebelen for first-order logic). From this, it follows that quantification in formulas can be restricted to words of bounded length, i.e., the second part of the proof is an adaptation of the method by Ferrante and Rackoff to counting logic and deviates significantly from the path of reasoning by Karandikar and Schnoebelen. [ABSTRACT FROM AUTHOR]

Ternary logic is a promising alternative to classical binary logic as it offers the benefits of reduced interconnect, higher operating speed and smaller chip area. In this paper, a new approach is proposed to implement the 3–2 compressor and 4–2 compressor circuits using the futuristic carbon nanotube field-effect transistors (CNTFET). A CNTFET unique feature of geometry dependent threshold variation is utilized in threshold detector circuits which have been used to perform ternary to binary conversion. The high power consumption of capacitive based designs is reduced by minimizing the occurrence of voltage division by performing intermediate processing on binary literals rather than performing the computation directly on ternary signals. It exploits the combination of ternary logic and binary logic design technique to achieve enhanced performance. The proposed compressor designs are examined exhaustively using the Synopsys HSPICE simulator with 32 nm Stanford CNTFET model under various test conditions such as different supply voltages, temperatures, load capacitors, and operational frequencies. The simulation results indicate the superiority of the proposed design in terms of power and power delay product as compared to earlier reported designs. [ABSTRACT FROM AUTHOR]

Computing systems are becoming more and more power-constrained due to unconventional computing requirements like computing on the edge, in-sensor, or simply an insufficient battery. Emerging Non-Volatile Memories are explored to build low-power computing circuits, and adders are one among them. In this work, we propose a low-power adder using a Ferroelectric Tunnel Junction (FTJ). FTJs are two-terminal devices where the data is stored in the polarization state of the device. An FTJ-based majority gate is proposed, which uses a current-mode sensing technique to evaluate the majority of the inputs. By conditionally selecting between the majority and its complement, an XOR operation is implemented, thereby achieving full-adder functionality. Since FTJ-based majority operation is slow, a ternary adder architecture is used to compensate for the speed loss. The ternary adder proposed by us has two stages of full adder and requires O(1) time for n-bit addition. The proposed adder is verified using a simulation in CMOS 130 nm technology. A 32-bit addition can be achieved in 100 μs and consumes 0.78 pJ, which is very power efficient (7.8 nW). The proposed adder can be used in applications where power consumption is crucial, and speed is not a strict requirement. [ABSTRACT FROM AUTHOR]

Drowsiness on the road is a widespread problem with fatal consequences; thus, a multitude of systems and techniques have been proposed. Among existing methods, Ghoddoosian et al. utilized temporal blinking patterns to detect early signs of drowsiness, but their algorithm was tested only on a powerful desktop computer, which is not practical to apply in a moving vehicle setting. In this paper, we propose an efficient platform to run Ghoddoosian's algorithm, detail the performance tests we ran to determine this platform, and explain our threshold optimization logic. After considering the Jetson Nano and Beelink (Mini PC), we concluded that the Mini PC is most efficient and practical to run our embedded system in a vehicle. To determine this, we ran communication speed tests and evaluated total processing times for inference operations. Based on our experiments, the average total processing time to run the drowsiness detection model was 94.27 ms for the Jetson Nano and 22.73 ms for the Beelink (Mini PC). Considering the portability and power efficiency of each device, along with the processing time results, the Beelink (Mini PC) was determined to be most suitable. Additionally, we propose a threshold optimization algorithm, which determines whether the driver is drowsy, or alert based on the trade-off between the sensitivity and specificity of the drowsiness detection model. Our study will serve as a crucial next step for drowsiness detection research and its application in vehicles. Through our experiments, we have determined a favorable platform that can run drowsiness detection algorithms in real-time and can be used as a foundation to further advance drowsiness detection research. In doing so, we have bridged the gap between an existing embedded system and its actual implementation in vehicles to bring drowsiness technology a step closer to prevalent real-life implementation. [ABSTRACT FROM AUTHOR]

The FitzHugh-Nagumo (FHN) spiking model has rich dynamics behaviors and can imitate the firing process of a neuron. The memristor is a nonvolatile and resistance tunable device, which gradually becomes a potential candidate for performing dynamic behaviors and implementing neuromorphic computation in the nervous system. In this paper, the memristive FitzHugh-Nagumo (MFHN) spiking model is presented. Firstly, we introduce a memristor to the FHN spiking model to build the MFHN spiking model and analyze the phase plane trajectory of the MFHN model. Secondly, we couple two MFHN models with a memristor and experimentally simulate the dynamic behaviors of two coupled neurons. The synchronous and asynchronous phenomena of two coupled neurons are discussed. Thirdly, the feasibility of the MFHN spiking model is demonstrated by the realization of binary logical operations and the implementation of binary adders. The comparison between the MFHN binary adder and the FHN binary adder is conducted. The simulation results illustrate that the proposed model efficiently performs rich, dynamic behaviors and higher firing frequency. The coupled MFHN models show the effectiveness of a memristor acting as an electric coupling synapse. The threshold logic computation can be completed efficiently by the MFHN spiking model. The MFHN binary adders reproduce the computing functions and behaviors of the biological neuron. [ABSTRACT FROM AUTHOR]

In the emerging nanotechnology, a finest potential alternative to transistor-based technology is Quantum-dot cellular automata (QCA). It promises higher device density and lower power consumption. The predominant application of QCA is the realization of configurable blocks in the digital systems. This paper presents a new serial scan register and a boundary scan cell, essential components used for chip-level and system-level testing. The proposed majority logic gate-based 1-bit clocked D-flip-flop (DFF) and the rotating multiplexer is used in these techniques. In the first attempt, the clocked DFF is further extended to implement the 2-bit, 4-bit, serial shift register and scan flip-flop. The detailed structural and performance analysis in different aspects proves that the proposed circuits offer elevated performance in contrast to earlier reported works. The various circuit comparison factors that are to be considered in QCA are the circuit complexity, area, delay in terms of the number of clocks, and energy dissipation. Significant improvements have been enhanced in the proposed layouts as compared to traditional approaches. In addition, power dissipation analysis of the stated DFF would be carried out at 2 K Temperature using different tunnelling energy levels (0.5, 1.0, and 1.5 Ek). All the simulations are performed using QCA Designer Ver. 2.0.3 and the power analysis is performed by QCA Pro tool Ver. 1.0. [ABSTRACT FROM AUTHOR]

In this paper, we have investigated the performance of underwater vertical wireless optical communication (UVWOC) link employing on–off key modulation in the presence of underwater turbulence, pointing errors and attenuation losses. The turbulence of the medium (assumed to be weak turbulence) has been modeled by employing the hyperbolic tangent log normal (HTLN) distribution. Temperature, pressure and salinity are parameters which can bring about variation of optical transmission characteristics with respect to depth of the ocean/sea. An in-depth study of optical transmission through vertical oceanic links requires the the underwater medium to be modeled as comprising of non-identical turbulent layers. Each of these independent and non-identical turbulence layers are modeled using the HTLN distribution function. The pointing error due to misalignment between source and detector is modeled using Rayleigh displacement pointing error. A novel closed-form expression to quantify the average bit error rate (BER) has been derived for single input single output (SISO) communication link. This expression has then been further generalized to make it applicable to the case of receive diversity schemes such as selection combining, majority logic combining and maximum ratio combining. The expression for the average BER associated with the UVWOC link for different pointing errors, different data rates and different types of ocean water has been determined. Novel closed-form expressions quantifying the outage probability and ergodic channel capacity have been derived for SISO and SC receive diversity schemes. The accuracy of all of the closed-form expressions derived in this paper have been validated using Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, we study the effect of delayed feedback on the dynamics of a three-dimensional chaotic dynamical system and stabilize its chaotic behavior and control the respective unstable steady state. We derive an explicit formula in which a Hopf bifurcation occurs under some analytical conditions. Then the existence and stability of the Hopf bifurcation are analyzed by considering the time delay τ as a bifurcation parameter. Furthermore, by numerical calculation and appropriate ascertaining of both the feedback strength K and time delay τ, we find certain threshold values of time delay at which an unstable equilibrium of the considered system is successfully controlled. Finally, we use numerical simulations to examine the derived analytical results and reveal more dynamical behaviors of the system. [ABSTRACT FROM AUTHOR]

The present article focuses on Mike Flanagan’s The Haunting of Hill House, a ten-episode series released on Netflix in 2019 and which the writers claimed was partly inspired by Shirley Jackson’s acclaimed novel of the same name. Both narratives are articulated around the towering and bleak presence of Hill House and its crippling influence on a variety of characters. However, questions pertaining to the notion of adaptation or faithfulness will not be tackled here. Instead, we wish to examine the concept of adolescence through the study of boundaries, thresholds and, more generally, liminality. Our discussion will be informed by concepts aligning space and body with a view to shedding new light on the gothic paraphernalia of the show. It will first deal with the bleak and labyrinthine setting of Hill House as a porous and crumbling structure whose cinematic transcription challenges the traditional understanding of space. This contribution will then study the different members of the Crain family and how their characterisation borrows from gothic readings of the ailing and failing body. Finally, we wish to go beyond familiar (albeit fascinating) analyses of liminality (with, for instance, the heterotopic space and the liminal neophyte, our focal points in parts one and two respectively) and apprehend formal and stylistic playfulness through the study of thresholds and transitions in the very fabric of the television narrative. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is considered to be one of the most frequent neurogenerative dementia in the elderly population. In order to improve the quality of life span, early detection of AD has drawn significant attention to the researchers throughout the globe. To this aim, this paper makes a novel attempt to classify the brain MRI images into three classes viz. Alzheimer's disease (AD), mild cognitive impairment (MCI) and healthy control (HC) using the volumetric information of white matter (WM), grey matter (GM) and cerebro spinal fluid (CSF). This classification has been accomplished with the help of fuzzy logic based approach followed by a majority voter classifier. Our proposition is finally tested over several brain MRI images collected from ADNI dataset. Supremacy of our proposition has strongly been established by measuring its performance parameters such as accuracy, sensitivity and specificity and subsequently been compared with many of the state-of-the-art methods. Simulation results have shown an average improvement of approximately 6.5%, 6.9% and 4% over a number of existing works in terms of accuracy, sensitivity and specificity respectively. [ABSTRACT FROM AUTHOR]

Elliptic curves (ECs) are deemed one of the most solid structures against modern computational attacks because of their small key size and high security. In many well-known cryptosystems, the substitution box (Sbox) is used as the only nonlinear portion of a security system. Recently, it has been shown that using dynamic S-boxes rather than static S-boxes increases the security of a cryptosystem. The conferred study also extends the practical application of ECs in designing the nonlinear components of block ciphers in symmetric key cryptography. In this study, instead of the Mordell elliptic curve (MEC) over the prime field, the Galois field has been engaged in constructing the S-boxes, the main nonlinear component of the block ciphers. Also, the proposed scheme uses the coordinates of MEC and the operation of the Galois field to generate a higher number of S-boxes with optimal nonlinearity, which increases the security of cryptosystems. The proposed S-boxes resilience against prominent algebraic and statistical attacks is evaluated to determine its potential to induce confusion and produce acceptable results compared to other schemes. Also, the majority logic criteria (MLC) are used to assess the new S-boxes usage in the image encryption application, and the outcomes indicate that they have significant cryptographic strength. [ABSTRACT FROM AUTHOR]

To program intercellular communication for biomedicine, it is crucial to regulate the secretion and surface display of signaling proteins. If such regulations are at the protein level, there are additional advantages, including compact delivery and direct interactions with endogenous signaling pathways. Here we create a modular, generalizable design called Retained Endoplasmic Cleavable Secretion (RELEASE), with engineered proteins retained in the endoplasmic reticulum and displayed/secreted in response to specific proteases. The design allows functional regulation of multiple synthetic and natural proteins by synthetic protease circuits to realize diverse signal processing capabilities, including logic operation and threshold tuning. By linking RELEASE to additional sensing and processing circuits, we can achieve elevated protein secretion in response to "undruggable" oncogene KRAS mutants. RELEASE should enable the local, programmable delivery of intercellular cues for a broad variety of fields such as neurobiology, cancer immunotherapy and cell transplantation. To program intercellular communication for biomedicine, it is crucial to regulate the secretion and surface display of signaling proteins. Here the authors develop RELEASE, a modular approach to control intercellular signals using protein-based circuits. [ABSTRACT FROM AUTHOR]

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The Republic of Indonesia‟s Law no. 7 of 2017 requires presidential and vice-presidential candidates to be proposed by political parties that meet the requirements, namely obtaining at least 20% of the total Legislative House seats or nationally obtaining 25% of valid votes in the previous Legislative House election. This is not recognized in Article 6A paragraph (2) of the 1945 Constitution, the constitutional basis for nominating a president. This paper aims to provide a philosophical analysis on the presidential and vice-presidential electoral threshold. Results show that from a philosophical perspective, this threshold provisions eliminate the constitutional rights of the people and minor political parties to nominate presidential and vice-presidential candidates. There can only be a maximum of three political parties and the oligarch and large political parties will make sure that the candidates will only come from their parties. This threshold undermines the logic of the presidential system. In conclusion, philosophically the threshold limits the freedom of alternative candidates to nominate themselves in the presidential election. It will only give an opportunity for candidates from major political parties. Thus, the government and various parties must reconsider this law to protect the rights of the people as mandated by the constitution. [ABSTRACT FROM AUTHOR]

This paper presents two new inexact sum-based 1-bit approximate full adders (AFAs). The proposed 1-bit approximate adders (PAAs), namely PAA1 and PAA2, are derived based on the majority logic. The layouts of PAAs are designed in quantum cellular automata (QCA) technology using the QCADesigner tool. To assess the performance of PAAs, we compare them against the reported AFAs in terms of various design metrics, such as the total area, delay, and performance. The comparison results show that the PAA1 and PAA2, having an area of 0.02 μ m 2 and 0.04 μ m 2 , provide area savings of 60% and 20%, respectively, compared with the lowest-area AFA reported in the literature. Also, the PAA1 and PAA2 have an equal delay of 0.5 clock cycles, that is, 33.33% less as compared to the AFA with the lowest delay. The designs are analyzed in terms of image quality metrics for image processing applications. Besides area efficiency and delay performance, on average, PAA1 provides the worst PSNR/SNR, while PAA2 provides the best PSNR/SNR compared to the other state-of-the-art approximate adders. [ABSTRACT FROM AUTHOR]

A tractor is a typical representative of power machinery in agricultural production. Two working conditions of tractors include road transportation and field operation. These working conditions can also be subdivided into plowing, rotary tillage, and fertilization, according to the carried agricultural implements. However, there are high oil consumption and low energy-saving in tractors, where the external load fluctuates frequently, as the working environment changes. Furthermore, a large number of gears have been equipped and frequently shifted to fully meet the needs of different working conditions in the traditional tractors, leading to the difficulty of tractor operation. In this study, a hybrid-mechanical-hydraulic power system was designed for a tractor using continuously variable transmission and hybrid power technology. The driving and transmission modes of the system were realized to obtain the speed regulation curve of the continuously variable transmission. The mounted hydro-mechanical continuously variable transmission (HMCVT) was also optimized for the best performance of the power system. Taking the engine economy curve as the target, the economic speed ratio map of HMCVT was drawn by the MATLAB platform. The target speed ratio was then obtained, according to the vehicle speed and throttle opening. As such, a speed ratio control strategy was formulated using the engine economy curve. Moreover, an energy management strategy was constructed using the minimum equivalent fuel consumption. The equivalent factor was integrated into the working division using the logic threshold. The penalty function was then introduced to maintain the battery State of Charge (SOC) stability. A strategy was designed for the rule-based mode division and the minimum fuel consumption power allocation using the adaptive equivalent factor. Specifically, the vehicle speed, demand torque, battery SOC, and speed ratio were firstly used as the logic threshold for the mode division, and then the minimum instantaneous equivalent fuel consumption was used as the objective function. Finally, the corresponding constraint conditions were introduced to calculate the minimum fuel for the engine and motor at any moment. The dynamic model of the tractor system was established in the SimulationX software. A test bench was also built using a dynamometer. The simulation and experimental analysis of the tractor were performed on the three typical working conditions of plowing, harvesting, and transportation. The results showed that the error between the simulation and test value was less than 5%, indicating a reliable model. The HMCVT efficiency was above 0.80 under the three working conditions, whereas, the efficiency of the whole power system was around 0.4. The SOC values were achieved at +1.96, -0.37, and -0.19 at the end of the plowing, harvesting, and transportation, respectively, indicating near the target value. The fuel consumption values were 2.72, 6.80, and 1.77 L in the plowing, harvesting, and transportation, respectively. Therefore, the 18% and 15% oil consumption was saved under the power output condition, compared with the power shift tractor, and the continuously variable transmission tract published by the German Agricultural Association, respectively. By contrast, 15% and 19% of the oil were saved under the transportation condition, compared with the power shift tractor, and the continuously variable transmission tractor, respectively. The 9%-20% fuel was also saved under three working conditions, indicating the feasible power system and the control strategy. The finding can provide a better solution to reduce the tractor energy consumption under multi-working conditions. [ABSTRACT FROM AUTHOR]

We present a neuro-symbolic visual question answering (VQA) pipeline for CLEVR, which is a well-known dataset that consists of pictures showing scenes with objects and questions related to them. Our pipeline covers (i) training neural networks for object classification and bounding-box prediction of the CLEVR scenes, (ii) statistical analysis on the distribution of prediction values of the neural networks to determine a threshold for high-confidence predictions, and (iii) a translation of CLEVR questions and network predictions that pass confidence thresholds into logic programmes so that we can compute the answers using an answer-set programming solver. By exploiting choice rules, we consider deterministic and non-deterministic scene encodings. Our experiments show that the non-deterministic scene encoding achieves good results even if the neural networks are trained rather poorly in comparison with the deterministic approach. This is important for building robust VQA systems if network predictions are less-than perfect. Furthermore, we show that restricting non-determinism to reasonable choices allows for more efficient implementations in comparison with related neuro-symbolic approaches without losing much accuracy. [ABSTRACT FROM AUTHOR]