Trigger Module Research Articles

The design of self-healing memristive network circuit based on VTA DA neurons and its application

This paper proposes a self-healing memristive network circuit, which simulates the resilience mechanism of VTA DA neurons. The proposed memristive network circuit mainly consists of four modules: input (synapse) module, damage detection module, threshold trigger module and negative feedback module. The input module is composed of a memristive synaptic circuit, which can react to a harmful initial input rather than a normal initial input. Apart from reacting to initial input, the input module also can receive a feedback signal released by the negative feedback module, and the process of receiving feedback signal is the key of realizing the self-healing function. The damage detection module can output a low level pulse that acts as an input signal of the threshold trigger module when the harmful initial input exists. The threshold trigger module will activate the negative feedback module when the trigger point which corresponds to the positive threshold voltage of memristor is reached. As the last module of the self-healing function, the negative feedback module can transmit the feedback signal, also be called a repairing signal, to the damaged memristor of the input module. The PSPICE simulation results indicate that the proposed memristive network circuit can realize the self-healing function which corresponds to the resilience mechanism of the VTA DA neurons. Meanwhile, when the proposed memristive network circuit has been applied to the damaged electronic machines or robots, the self-healing function of it can make the machines be reusable.

Research on the Role of Artificial Intelligence in the Core of Intelligent Translation Systems

With the development of the world economy and the expansion of foreign trade, the status of English as a global language in English teaching is increasingly elevated, and language translation is an indispensable link. In the new intelligent translation and reading system based on language models, its translation part includes at least one dictionary used for translation. The system includes: reading and writing database, loading module, editing module, label module, trigger module, annotation module, and word addition module. Among them, the read-write database is used to store literature; The loading module is used to load article materials as reading documents. It adopts natural language processing technology to save system translation and reading time and improve system efficiency. In order to test the advantages of the system used in this article, 200 vocabulary words were input into the system and compared with the traditional system for translation accuracy. The translation accuracy of the system in this article was 94.64%, while the translation accuracy of the traditional system was 83.34%. The system in this article helps to improve translation efficiency and enhance reading experience.

Research on Data Acquisition and Regulation Methods of Basement Flashing Pressure Relief System Based on Digital Technology

Abstract This study utilizes digital technology to monitor water pressure changes within basement flashings, facilitating targeted drainage operations. By implementing an active water discharge method, drainage holes are strategically placed around or beneath basements to decompress and reduce water levels, thereby alleviating hydrostatic pressure on underground structures. This approach helps prevent basement uplift. The paper addresses challenges such as high energy consumption and ample data storage in long-term monitoring, introducing an acceleration trigger module and a data correction algorithm based on an enhanced BP neural network. A WOA-BP neural network model was developed using historical data to monitor water pressure efficiently. Our findings indicate that at 0.076MPa, flashing connections begin to fail, progressing to shear damage at 0.085MPa. Consequently, to preserve basement integrity, it is crucial to activate complete drainage when monitored pressure exceeds 0.045MPa to maintain pressures below the critical threshold of 0.076MPa.

MPC‐Bi‐LSTM based control strategy for connected and automated vehicles platoon oriented to cyberattacks

AbstractAny technological innovation will be accompanied by new challenges and risks, and the connected and automated vehicles (CAVs) are no exception. Among them, the argument that cooperating platoons may fall victim to cyberattacks through wireless communication has emerged as a significant issue. Therefore, this paper designs a communication topology anomaly response system (CTARS) to ensure platoon safety, which consists of a trigger module and a control module. The primary objective of the trigger module is to distinguish abnormal vehicle behavior based on time to collision (TTC) indicators, and the control module combines the model predictive control (MPC) and bidirectional long short‐term memory (Bi‐LSTM) to achieve accurate trajectory prediction of and optimal control, working in tandem with the trigger module. Subsequently, the real dataset HISTORIC is used to calibrate the multiple vehicle intelligent driver model (IDM) and train the trajectory prediction model. Furthermore, comparative simulations are conducted, encompassing various forms of cyberattacks, in order to examine the evolution characteristics of CAVs platoons (CAVP) and evaluate the performance of CTARS. The results demonstrate the remarkable effectiveness of CTARS in safeguarding the security of CAVP during cyberattacks, thus confirming its exceptional performance.

3DEG: Data-Driven Descriptor Extraction for Global re-localization in subterranean environments

Localization algorithms that rely on 3D LiDAR scanners often encounter temporary failures due to various factors, such as sensor faults, dust particles, or drifting. These failures can result in a misalignment between the robot’s estimated pose and its actual position in the global map. To address this issue, the process of global re-localization becomes essential, as it involves accurately estimating the robot’s current pose within the given map. In this article, we propose a novel global re-localization framework that addresses the limitations of current algorithms heavily reliant on scan matching and direct point cloud feature extraction. Unlike most methods, our framework eliminates the need for an initial guess and provides multiple top-k candidates for selection, enhancing robustness and flexibility. Furthermore, we introduce an event-based re-localization trigger module, enabling autonomous robotic missions. Focusing on subterranean environments with low features, we leverage range image descriptors derived from 3D LiDAR scans to preserve depth information. Our approach enhances a state-of-the-art data-driven descriptor extraction framework for place recognition and orientation regression by incorporating a junction detection module that utilizes the descriptors for classification purposes. The effectiveness of the proposed approach was evaluated across three distinct real-life subterranean environments.

A Method of DDoS Attack Detection and Mitigation for the Comprehensive Coordinated Protection of SDN Controllers.

Software defined networking (SDN) improves the flexibility and programmability of the network by separating the control plane and the data plane and effectively realizes the global control of the network infrastructure. However, the centralized structure design of SDN exposes the controller to potential threats. Attackers have used the active flow table delivery mode to launch distributed denial of service (DDoS) attacks on the SDN controller, resulting in the controller failure and seriously affecting the network performance. To overcome this problem, this paper proposes a defense framework called CC-Guard. The framework consists of four modules: attack detection triggering, switch migration, anomaly detection, and mitigation. Among them, the attack detection trigger module improves the system's timely response to DDoS attacks. The switch migration module effectively unclogs the controller congestion problem and provides convenience for network flow transmission. The anomaly detection module uses a coarse-grained method for two-stage detection, which improves the detection accuracy. The mitigation module uses the idea of cross-domain cooperation of the controller to clear the abnormal flow in the blacklist. Experimental results show that our proposed CC-Guard has real-time DDoS attack defense capability and high detection accuracy, as well as efficient network resource utilization.

Susceptibility of Microseismic Triggering to Small Sinusoidal Stress Perturbations at the Laboratory Scale

AbstractSmall transient stress perturbations are prone to trigger (micro)seismicity. In the Earth's crust, these stress perturbations can be caused by various sources such as the passage of seismic waves, forcing by tides, or hydrological seasonal loads. A better understanding of the dynamic of earthquake triggering by stress perturbations is essential to improve our understanding of earthquake physics and our consideration of seismic hazard. Here, we study an experimental sandstone‐gouge‐filled fault system undergoing combined far field loading and periodic stress perturbations (of variable amplitude and frequency) at crustal pressure conditions. Microseismicity—in the form of acoustic emissions (AEs)—strains, and stresses, are continuously recorded in order to study the response of microseismicity as a function of loading rate, amplitude, and frequency of a periodic stress perturbation. The observed AE distributions do not follow the predictions of either a Coulomb failure model, taking into account both constant loading and oscillation‐induced strain rates, or a rate and state model. A susceptibility of the system's AE response to the amplitude of the confinement pressure perturbation is estimated, which highlights a linear relation between confinement pressure amplitude and the AE response amplitude, observations which agree with recent higher frequency experimental results on dynamic triggering. The magnitude‐frequency distribution of AEs is also computed. The Gutenberg‐Richter b‐value oscillates with stress oscillations. Our experiments may help complement our understanding of the influence of low inertia stress phenomena on the distribution of seismicity, such as observations of dynamic triggering and seismicity modulation by tides or hydrological loading.

Drain Extended MOS Body Region Engineering for Switching Reliability Under Unclamped Inductive Load Conditions

This work presents physical insights on drain extended NMOS (DeNMOS) transient switching reliability under unclamped inductive load (UIL) conditions. The dependence of UIL switching dynamics on the rate of carrier injection after parasitic bipolar junction transistor (P-BJT) triggering and subsequent space charge modulation (SCM) is demonstrated using a 2D TCAD simulation study. In DeNMOS, reduced body resistance suppresses the P-BJT while increasing the back gate bias delays the SCM. We show that the increased body contact length of the proposed DeNMOS offers the dual benefit of P-BJT mitigation and delayed SCM without degrading the DC electrical performance. Furthermore, it is shown that mitigation of P-BJT and delayed SCM enhance the turn-off reliability against thermal runaway when DeNMOS is subjected to transient switching conditions in the presence of UIL. Finally, we show that when external body resistance and bias are individually applied, they result in limited improvement in switching reliability, whereas body layout engineering could achieve optimum switching reliability. Subsequently, a comparative investigation of the body, drain and drift layout optimization techniques shows the highest enhancement in avalanche ruggedness and robustness against thermal runaway for body contact optimized DeNMOS.

Research on synchronous trigger module of laser-induced damage threshold measurement device

Research on synchronous trigger module of laser-induced damage threshold measurement device

Design of explosion-proof induction lamp temperature test system

Temperature test is an item to be tested in the type test of explosion-proof induction lamp. Temperature test is an item to be tested in the type test of explosion-proof induction lamp. A temperature test system based on single chip microcomputer integrated control and automatic trigger is proposed to improve the efficiency and stability of temperature test of explosion-proof induction lamp. Based on the analysis of the working principle of the explosion-proof induction lamp, the explosion-proof induction lamp temperature test system is designed, and the full-power trigger module of the explosion-proof induction lamp is designed in detail, so as to realize the automatic operation of the explosion-proof induction lamp temperature test.

Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection

In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0–6.3%, the respiration detection was 0–9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%.

Modularly Integrated System for Spatiotemporally Separated Solar Energy Storage and Release.

The sun is regarded as an endless source of clean energy. However, the intermittent supply and dynamically changeable demand of solar energy, as well as its uneven regional distribution, have been continually motivating the technological research of practical strategies to realize the spatiotemporally separated solar energy harvest and utilization. Accordingly, we here developed an integrated system for efficient solar energy capture, stable storage, and on-demand release, which corresponds to the intricate design of three distinct modules, namely, a photothermal conversion module, a latent heat storage module, and a mechanical trigger module. Moreover, efficient heat transfer and long-term supercooled stability necessitate interfacial passivation to coordinate the physical coupling of different modules. In addition to providing an integrated prototype that demonstrates a closed energy cycle in practice, this study may further inspire a new paradigm for advanced solar utilization in both theory and methodology.

High-precision and robust localization system for mobile robots in complex and large-scale indoor scenes

High-precision and robust localization is the key issue for long-term and autonomous navigation of mobile robots in industrial scenes. In this article, we propose a high-precision and robust localization system based on laser and artificial landmarks. The proposed localization system is mainly composed of three modules, namely scoring mechanism-based global localization module, laser and artificial landmark-based localization module, and relocalization trigger module. Global localization module processes the global map to obtain the map pyramid, thus improve the global localization speed and accuracy when robots are powered on or kidnapped. Laser and artificial landmark-based localization module is employed to achieve robust localization in highly dynamic scenes and high-precision localization in target areas. The relocalization trigger module is used to monitor the current localization quality in real time by matching the current laser scan with the global map and feeds it back to the global localization module to improve the robustness of the system. Experimental results show that our method can achieve robust robot localization and real-time detection of the current localization quality in indoor scenes and industrial environment. In the target area, the position error is less than 0.004 m and the angle error is less than 0.01 rad.

A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera.

Climate variables influence the occurrence, growth, and distribution of Vibrio cholerae in the aquatic environment. Together with socio-economic factors, these variables affect the incidence and intensity of cholera outbreaks. The current pandemic of cholera began in the 1960s, and millions of cholera cases are reported each year globally. Hence, cholera remains a significant health challenge, notably where human vulnerability intersects with changes in hydrological and environmental processes. Cholera outbreaks may be epidemic or endemic, the mode of which is governed by trigger and transmission components that control the outbreak and spread of the disease, respectively. Traditional cholera risk assessment models, namely compartmental susceptible-exposed-infected-recovered (SEIR) type models, have been used to determine the predictive spread of cholera through the fecal–oral route in human populations. However, these models often fail to capture modes of infection via indirect routes, such as pathogen movement in the environment and heterogeneities relevant to disease transmission. Conversely, other models that rely solely on variability of selected environmental factors (i.e., examine only triggers) have accomplished real-time outbreak prediction but fail to capture the transmission of cholera within impacted populations. Since the mode of cholera outbreaks can transition from epidemic to endemic, a comprehensive transmission model is needed to achieve timely and reliable prediction with respect to quantitative environmental risk. Here, we discuss progression of the trigger module associated with both epidemic and endemic cholera, in the context of the autochthonous aquatic nature of the causative agent of cholera, V. cholerae, as well as disease prediction.

Characterization of Event-Based Sampling Encoders for Industrial Internet of Things Using Input–Output Mutual Information

The emergence of Industry 4.0 has resulted in a rapid increase in the demand for bandwidth due to the proliferation of the industrial Internet of Things (IIoT). Increased utilization of the network also gives rise to undesirable consequences such as high latency and increased likelihood of data loss through packet drops. Encoding inputs using event-based sampling is a potential solution for decreasing network traffic generated when continuous input variables are sampled. The problem addressed by this article is the fact that currently there is no effective method for comparing different encoders. The resulting contribution is the use of mutual information to compare the input and encoded output in terms of accuracy for the currently most efficient encoders that use either memory based event triggering (MBET) or deadband error modulation (DEM). This allows a practitioner to select a suitable encoder for a given input specification.

Light and Heat Triggering Modulation of the Electronic Performance of a Graphdiyne-Based Thin Film Transistor.

Graphdiyne-based field effect thin film transistors (GTFTs) with a clean, efficient, nondestructive, continuous, and reversible modulation strategy have been developed for the first time. We have determined that efficient electronic modulation utilizing light and heat results in a significant improvement in GTFT performance. Heat can increase the switching ratio of the device to 103, while light regulation can induce a higher switching ratio of >104 by efficient charge injection with an improved conductivity of 1.5 × 104 S/m. Via the adjustment of the visible light wavelength and power density, tunable charge injection has been realized. These results not only highlight the excellent intrinsic properties and modulation method of GTFTs but also promote the application of such films composed of two-dimensional graphdiyne material in integrated devices, such as logic devices and flexible devices.

Cytosolic NQO1 Enzyme-Activated Near-Infrared Fluorescence Imaging and Photodynamic Therapy with Polymeric Vesicles

The utilization of enzymes as a triggering module could endow responsive polymeric nanostructures with selectivity in a site-specific manner. On the basis of the fact that endogenous NAD(P)H:quinone oxidoreductase isozyme 1 (NQO1) is overexpressed in many types of tumors, we report on the fabrication of photosensitizer-conjugated polymeric vesicles, exhibiting synergistic NQO1-triggered turn-on of both near-infrared (NIR) fluorescence emission and a photodynamic therapy (PDT) module. For vesicles self-assembled from amphiphilic block copolymers containing quinone trimethyl lock-capped self-immolative side linkages and quinone-bridged photosensitizers (coumarin and Nile blue) in the hydrophobic block, both fluorescence emission and PDT potency are initially in the "off" state due to "double quenching" effects, that is, dye-aggregation-caused quenching and quinone-rendered PET (photoinduced electron transfer) quenching. After internalization into NQO1-positive vesicles, the cytosolic NQO1 enzyme triggers self-immolative cleavage of quinone linkages and fluorogenic release of conjugated photosensitizers, leading to NIR fluorescence emission turn-on and activated PDT. This process is accompanied by the transformation of vesicles into cross-linked micelles with hydrophilic cores and smaller sizes and triggered dual drug release, which could be directly monitored by enhanced magnetic resonance (MR) imaging for vesicles conjugated with a DOTA(Gd) complex in the hydrophobic bilayer. We further demonstrate that the above strategy could be successfully applied for activated NIR fluorescence imaging and tissue-specific PDT under both cellular and in vivo conditions.

Decentralised event‐based synchronisation and control of spacecraft

In this study a decentralised event-based scheme is proposed to synchronise the spacecraft's attitudes during their convergence toward the desired attitude, in the presence of disturbance. To achieve this goal, decentralised integral-based triggering mechanisms are introduced which not only reduce the data transmission among the spacecraft efficiently but also guarantee a minimum inter-event time for each triggering module. Moreover, a design procedure is given to find the control gains and triggering conditions parameters properly. Finally, simulation results are provided to show the effectiveness of the system.

A micro-tattooing device for capsule endoscope using a Wood's metal triggering mechanism

The endoscopic tattooing procedure is essential before surgery in the gastroenterology practice. Because conventional tattooing is conducted by injecting biocompatible ink from outside the human body, a conventional tattooing device is not appropriate for use in the Capsule Endoscope (CE). A compact micro-tattooing device with an optimal triggering mechanism which can be enclosed in the CE is required. Therefore, A micro-tattooing device operated by two conical springs with a Wood's metal-based triggering module is proposed. Needle insertion and ink injection to the submucosal layer of the colon is actuated by triggering mechanism #1. When triggering mechanism #2 is activated, the needle is withdrawn to avoid scratching the internal lumen. Each triggering module is activated by the Joule heating of a Ni-Cr wire with low power consumption to accommodate the CE battery's small capacity. The in-vitro and ex-vivo tests were conducted to confirm the feasibility of the tattooing module. In the in-vitro test, the needle displacement was confirmed to be 3.3 mm. Using extracted porcine colon, the total tattooing procedure was conducted, and the injected ink in the submucosal layer was observed by hemisecting the specimen. Conclusively, the device achieved competitive results, both in terms of power consumption and space constraints.

Electronics of Time-of-Flight Measurement for Back-n at CSNS

Back-n is a white neutron experimental facility at China Spallation Neutron Source (CSNS). The time structure of the primary proton beam make it fully applicable to use TOF (time-of-flight) method for neutron energy measuring. We implement the electronics of TOF measurement on the general-purpose readout electronics designed for all of the seven detectors in Back-n. The electronics is based on PXIe (Peripheral Component Interconnect Express eXtensions for Instrumentation) platform, which is composed of FDM (Field Digitizer Modules), TCM (Trigger and Clock Module), and SCM (Signal Conditioning Module). T0 signal synchronous to the CSNS accelerator represents the neutron emission from the target. It is the start of time stamp. The trigger and clock module (TCM) receives, synchronizes and distributes the T0 signal to each FDM based on the PXIe backplane bus. Meantime, detector signals after being conditioned are fed into FDMs for waveform digitizing. First sample point of the signal is the stop of time stamp. According to the start, stop time stamp and the time of signal over threshold, the total TOF can be obtained. FPGA-based (Field Programmable Gate Array) TDC is implemented on TCM to accurately acquire the time interval between the asynchronous T0 signal and the global synchronous clock phase. There is also an FPGA-based TDC on FDM to accurately acquire the time interval between T0 arriving at FDM and the first sample point of the detector signal, the over threshold time of signal is obtained offline. This method for TOF measurement is efficient and not needed for additional modules. Test result shows the accuracy of TOF is sub-nanosecond and can meet the requirement for Back-n at CSNS.