Negative-SET behavior is observed in various cation-based memories, which degrades the device reliability. Transmission electron microscopy results demonstrate caused by overgrowth of conductive filament (CF) into Pt electrode. The CF phenomenon suppressed and negative-SET eliminated inserting an impermeable graphene layer. graphene-based devices show high reliability satisfying performance. As a service to our authors readers, this journal provides supporting information supplied authors....

Temporal knowledge graph, serving as an effective way to store and model dynamic relations, shows promising prospects in event forecasting. However, most temporal graph reasoning methods are highly dependent on the recurrence or periodicity of events, which brings challenges inferring future events related entities that lack historical interaction. In fact, current moment is often combined effect a small part information those unobserved underlying factors. To this end, we propose new...

Abstract Large attention has recently been given to a novel technology named memristor, for having the potential of becoming new electronic device standard. Yet, its manifestation as fourth missing element is rather controversial among scientists. Here we demonstrate that TiO 2 -based metal-insulator-metal devices are more than just memory-resistor. They possess resistive, capacitive and inductive components can concurrently be programmed; essentially exhibiting convolution memristive,...

Conventional machine vision systems suffer from great data latency and energy consumption in cognitive tasks due to the separated sensors, memory units, processors. In‐sensor computing based on optoelectronic synapses allows efficient computation by directly sensing processing optical signals. Herein, an synapse Au/ZnO:N/IGZO/TiN structure is proposed. It shows uniform SET electrical RESET behaviors, with various light‐tunable plasticity. Furthermore, a 4‐bit reservoir experimentally...

Cloud resource scheduling is one of the most significant tasks in field big data, which a combinatorial optimization problem essence. Scheduling strategies based on meta-heuristic algorithms (MAs) are often chosen to deal with this topic. However, MAs prone falling into local optima leading decreasing quality allocation scheme. Algorithms good global search ability needed map available cloud resources requirements task. Honey Badger Algorithm (HBA) newly proposed algorithm strong ability. In...

Recently, 2-D cross-point array of resistive random access memory (RRAM) has been proposed for implementing the weighted sum and weight update operations to accelerate neuro-inspired learning algorithms on chip. This paper aims extend such 3-D vertical storing computing large-scale matrices in neural network. Considering fabrication integration analog synapses (i.e., multilevel RRAM devices) are premature at this stage, we propose using today's available digital or binary devices a ternary...

Grey Wolf Optimizer (GWO) is a new meta-heuristic optimization. It inspired by the unique predator strategy and organization system of grey wolves. Since GWO algorithm easy to fall into local optimum especially when it used in high-dimensional data, an improved combined with Cuckoo Search (CS) proposed this paper. By introducing global-search ability CS update its best three solutions that are alpha_wolf, beta_wolf delta_wolf, search strengthened, shortcoming offset. Preliminary experimental...

Due to their simple structures and high-density integration, Memristors are employed construct hardware spiking neurons. In this letter, we present a TiN/NbOx/Pt memristor with tunable threshold for constructing configurable By applying positive tuning voltages different compliance currents, the device exhibits multilevel negative voltages. Additionally, by changing amplitudes/widths of pulses, obtain quasi-linear modulation Based on such device, leaky integrate-and-fire neuron curves...

This paper presents a mathematical framework for the evaluation of performance proactive and reactive routing protocols in mobile ad hoc networks (MANETs). unified provides parametric view protocol performance, which turn deeper insight into operations reveals compounding interacting effects logic network parameters. The model comes from combinatorial model, where is synthesized along with characterization MAC performance. Each wireless node seen independently as two-customer queue without...

The electronic synapse, which can vividly emulate short-term and long-term plasticity, as well voltage sensitivity, in the bio-synapse, is vital device foundation for brain-inspired neuromorphic computing. In this letter, we propose a Ag/GeSe/TiN memristor an synapse applications. Due to electromigration diffusion of Ag cation, volatile non-volatile switching behaviours are coexistent device. Various synaptic functions, including pair-pulse facilitation, spike timing-dependent have been...

With the widespread use of Internet, network security issues have attracted more and attention, intrusion detection has become one main technologies. As for detection, original data source always a high dimension large amount data, which greatly influence efficiency accuracy. Thus, both feature selection classifier then play significant role in raising performance detection. This paper takes results classification optimization weighted K-nearest neighbor (KNN) with those algorithm into...

Feature selection is a very important direction for network intrusion detection. However, current feature technology of detection has the problems low rate and accuracy due to redundancy. An improved Butterfly Optimization Algorithm combined with Black Widow (BWO-BOA) proposed in this paper, which introduces dynamic adaptive search strategy global phase (BOA), uses movement process (BWO) algorithm as local search, at same time, order overcome butterfly optimization easily falling into...

<p>For the feature selection of network intrusion detection, issue numerous redundant features arises, posing challenges in enhancing detection accuracy and adversely affecting overall performance to some extent. Artificial rabbits optimization (ARO) is capable reducing can be applied for detection. The ARO exhibits a slow iteration speed exploration phase population prone an iterative stagnation condition exploitation phase, which hinders its ability deliver outstanding aforementioned...

Variable numerous types of equipment/subsystems may exist in complex systems, which makes it difficult to analyze and identify electromagnetic emission sources. A theory named "basic waveform theory" is presented this paper solve problem. This innovation characterizes with four basic waveforms, including square wave, sine damped oscillation, spike wave. Then, the effectiveness discussed both theoretical engineering ways. In particular, waveforms reflect physical characteristics equipment....

A noise source impedance extraction method for switched-mode power supply (SMPS) under operating condition is proposed and validated in this letter. First, a simplified precalibration using several known impedances introduced to eliminate the influence of measurement instruments other parasitic effects. Second, configuration presented calculation methods common-mode differential-mode microwave transmission analysis are described, respectively. The experimental results show that can extract...

Operando transmission FTIR spectroscopy of amine-functionalized polymer membranes reveals molecular level details CO 2 facilitated transport mechanisms, and the role water in mechanism.

<p>As an emerging network architecture, software-defined networking (SDN) has the core concept of separating control plane from hardware and unifying its management by a central controller. Since centralized SDN is such that attack on controller can lead to paralysis entire network, intrusion detection become particularly significant for SDN. Currently, more systems based machine learning deep are being applied SDN, but most have drawbacks as complex models low accuracy. This paper...

<p>As an emerging network architecture, software-defined networking (SDN) has the core concept of separating control plane from hardware and unifying its management by a central controller. Since centralized SDN is such that attack on controller can lead to paralysis entire network, intrusion detection become particularly significant for SDN. Currently, more systems based machine learning deep are being applied SDN, but most have drawbacks as complex models low accuracy. This paper...

Measuring event-related magnetic fields (ERFs) in magnetoencephalography (MEG) is crucial for investigating perceptual and cognitive information processing both neuroscience research clinical practice. However, the magnitude of ERF cortical sources comparable to noise a single trial. Consequently, numerous repetitive recordings are needed distinguish these from background noise, requiring lengthy time data acquisition. Herein, we introduce DeepReducer, linear transformer-based deep learning...

Purpose – The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability high, while absolute positioning accuracy and are low. Many factors affect accuracy, method an important factor. When traditional methods applied on robot, accumulative error will be involved according transformation between measurement coordinate base coordinate. Design/methodology/approach In manuscript, model proposed. First, simplified by...