False Triggering Research Articles

An Application of the Subwavelength Periodic Microstrip Guard Trace in High-Speed Circuits

This paper proposed a kind of guard traces based on a subwavelength periodic structure to reduce the far-end crosstalk (FEXT) of parallel microstrip lines in the PCB. This technology can be used to improve the false triggering and signal transmitting capacity of a multiconductor transmission line circuit system. In order to explore the present novel guard trace effect on isolating electromagnetic interference (EMI), the frequency response of the mutual capacitance and mutual inductance of the overall circuit system was provided and an equivalent circuit model was built. In comparison to the conventional microstrip line for isolating the EMI between parallel microstrip lines, the novel guard trace can efficiently reduce the mutual capacitance and mutual inductance of the overall circuit system. Thus, it is favorable for suppressing the crosstalk between microstrip lines. The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S$ </tex-math></inline-formula> -parameters calculation result showed that this kind of subwavelength periodic microstrip guard trace can isolate the EMI between two microstrip lines more effectively. Particularly, the conventional grounded guard trace needs a lot of dense grounded holes, which severely influences the wiring design of various layers of a multilayer circuit board. However, the proposed guard trace requires only one grounded hole, which has little influence on the circuit wiring of each layer of a multilayer printed circuit board. In our experiment, the step function signal of 30 ps rise time was imported into one microstrip line to measure the FEXT of the other microstrip line. It was demonstrated by the measurement result that the subwavelength periodic microstrip guard trace can reduce the FEXT to be below 5% of the transmission signal amplitude and is more flexible in practice. In compliance with the actual demand for a high-speed circuit, three isolation structures were proposed, and their isolation effects on the electromagnetic coupling between microstrip lines were verified individually.

Cognitive Failures: Relationship with Perceived Emotions, Stress, and Resting Vagally-Mediated Heart Rate Variability

Cognitive failures represent everyday task failures that individuals are normally capable of completing. While cognitive failures measured with the Cognitive Failures Questionnaire can be considered a trait, the psychophysiological states associated with cognitive failures are yet to be fully understood. The aim of this paper was to investigate the extent to which the perception of experiencing cognitive failures in daily life is associated with both psychological (i.e., perceived emotional valence, emotional intensity, and stress), as well as physiological (i.e., vagally-mediated heart rate variability, vmHRV) variables. A total of 69 participants were involved in this study (47 male, 22 female; Mage = 22.4 years). Participants underwent a 5-min heart rate variability measurement and filled out the self-report psychological variables, before completing the Cognitive Failures Questionnaire, providing scores for Distractibility, Forgetfulness, and False Triggering. When combining the predictors together into a hierarchical regression analysis, only the model related to the Distractibility subscale was found to be significant (unique significant negative predictor: resting vmHRV). Further research should investigate whether influencing resting vmHRV, with interventions such as slow-paced breathing, may decrease the perception of cognitive failures related to distractibility.

Анализ электромагнитной совместимости микропроцессорных устройств релейной защиты и автоматики

In the modern conditions of the development of the electric power complex, relay protection and automation devices play a special role related to protection against possible damage resulting from violations of normal operating modes, both of individual elements and the entire power system as a whole. This, in turn, directly affects the reliable and stable functioning of the main power elements and electrical equipment. Damage to the power part of the equipment of an electric grid complex can be caused by changes in the main parameters of the normal mode: a change (increase) in currents leads to overloads and, in the limit, to short circuits, a decrease in voltage leads to an avalanche of voltage and disruption of the operation of electric motors connected to the damaged section, and an increase in voltage leads to overvoltages in certain sections. In addition, violations associated with a decrease in the transmitted active power lead to a change in frequency, and a violation of the reactive power balance leads to a change in voltage in certain sections, which generally leads to noncompliance with the power balance and loss of stable operation of the power system. The main reasons for failures in operation, false and excessive triggering of microprocessor relay protection devices are considered. The main ways of solving the problem of electromagnetic compatibility in the electric power industry are identified. A solution is proposed to improve the reliability of the operation of microprocessor relay protection devices and the way of development of the problem of electromagnetic compatibility in the electric power industry is shown.

The relationship between the subjective experience of real-world cognitive failures and objective target-detection performance in visual search

Visual search is a common occurrence in everyday life, such as searching for the location of keys, identifying a friend in a crowd, or scanning an upcoming intersection for hazards while driving. Visual search is also used in professional contexts, such as medical diagnostic imaging and airport baggage screening. These contexts are often characterised by low-prevalence or rare targets. Here we tested whether individual differences in the detection of targets in visual search could be predicted from variables derived from the rich informational source of participants' subjective experience of their cognitive and attentional function in everyday life. We tested this in both low-prevalence (Experiment 1) and high-prevalence (Experiment 2) visual search conditions. In both experiments, participants completed a visual search with arrays containing multiple photorealistic objects, and their task was to detect the presence of a gun. Following this, they completed the Cognitive Failures Questionnaire (CFQ) and the Attentional Control Scale (ACS). In Experiment 1, the target was present on 2% of trials, while in Experiment 2, it was present on 50%. In both experiments, participants' scores on the False Triggering component of the CFQ were negatively associated with accuracy on target-present trials, while participants' scores on the Forgetfulness component of the CFQ were positively associated with target-present accuracy. These results show that objective performance in visual search can be predicted from subjective experiences of cognitive function. They also highlight that the CFQ is not monolithic. Instead, the CFQ subfactors can have qualitatively different relationships with performance. Theoretical and practical implications are discussed.

Search for gamma-ray bursts and gravitational wave electromagnetic counterparts with High Energy X-ray Telescope of Insight-HXMT

ABSTRACT The High Energy (HE) X-ray telescope on board the Hard X-ray Modulation Telescope (Insight-HXMT) can serve as a wide field of view (FOV) gamma-ray monitor with high time resolution (μs) and large effective area (up to thousands cm2). We developed a pipeline to search for gamma-ray bursts (GRBs), using the traditional signal-to-noise ratio (SNR) method for blind search and the coherent search method for targeted search. By taking into account the location and spectrum of the burst and the detector response, the targeted coherent search is more powerful to unveil weak and sub-threshold bursts, especially those in temporal coincidence with gravitational wave (GW) events. Based on the original method in literature, we further improved the coherent search to filter out false triggers caused by spikes in light curves, which are commonly seen in gamma-ray instruments (e.g. Fermi/GBM, POLAR). We show that our improved targeted coherent search method could eliminate almost all false triggers caused by spikes. Based on the first two years of Insight-HXMT/HE data, our targeted search recovered 40 GRBs, which were detected by either Swift/BAT or Fermi/GBM but too weak to be found in our blind search. With this coherent search pipeline, the GRB detection sensitivity of Insight-HXMT/HE is increased to about 1.5E-08 erg cm−2 (200 keV–3 MeV). We also used this targeted coherent method to search Insight-HXMT/HE data for electromagnetic counterparts of LIGO-Virgo GW events (including O2 and O3a runs). However, we did not find any significant burst associated with GW events.

Performance Analysis of Novel Bidirectional DC-DC Converter With L-D Based Modified GaN-FET Driver

Gallium nitride (GaN)-FET devices are capable to provide high efficiency operation of dc-dc converter at higher frequency. The major problem of using GaN-FET in dc-dc converter lies in driver stage, which creates switch voltage ringing and high dv/dt during switching event. This creates false triggering of GaN-FET due its inherent low turn on threshold voltage. In this article, a novel nonisolated coupled inductor based bidirectional dc-dc (CIBDC) converter is proposed and tested with a modified inductor diode (L-D) based GaN-FET driver to verify higher efficiency operation as well as low switch voltage ringing and low dv/dt. The proposed converter is capable to provide higher voltage conversion ratios in both buck and boost mode. Due to parallel path structure the input current ripple is also less in the proposed CIBDC. The steady state performance like switch voltage ringing, dv/dt immunity, voltage stress, current stress, efficiency, etc. of this topology is tested on a 250 W prototype using L-D based driver.

Dynamic abuse testing of airbag system for passenger car under vehicle-road conditions and identification method for high-risk triggering items

Determination of the triggering conditions for automobile airbags is a complex problem because vehicles often run under transient conditions due to the dynamic influence from varying road conditions. The research into malfunctions of automobile airbags is an important and challenging topic. In this work, the peak acceleration and moving window integration algorithms were used to obtain the high-risk abuse items from a test matrix that consisted of 111 items which were under multiple road environment excitation, including condition categories for typical roads, curb striking, potholes and drains, and roadblocks. A novel multi-channel data reduction method and improved clustering method based on abuse probability sorting were proposed, and based on the specific characteristic constraints for the automobile airbag malfunction test results, by construction of a false triggering probability model and discussion of the weight factors of the two algorithms, importance rankings for the high-risk false action items were realized based on the relative probability. Finally, 53 high-risk abuse items were identified from a large set of 111 test items through 10-channel acceleration sensors. After analysis and comparison of the test condition details, conclusions of high-risk items are drawn with regard to the vehicle-road excitation that affects airbag abuse. The consistency of the identification results with the Chinese national standard verifies the accuracy and effectiveness of the proposed method.

An approach to rapid processing of camera trap images with minimal human input.

Camera traps have become an extensively utilized tool in ecological research, but the manual processing of images created by a network of camera traps rapidly becomes an overwhelming task, even for small camera trap studies.We used transfer learning to create convolutional neural network (CNN) models for identification and classification. By utilizing a small dataset with an average of 275 labeled images per species class, the model was able to distinguish between species and remove false triggers.We trained the model to detect 17 object classes with individual species identification, reaching an accuracy up to 92% and an average F1 score of 85%. Previous studies have suggested the need for thousands of images of each object class to reach results comparable to those achieved by human observers; however, we show that such accuracy can be achieved with fewer images.With transfer learning and an ongoing camera trap study, a deep learning model can be successfully created by a small camera trap study. A generalizable model produced from an unbalanced class set can be utilized to extract trap events that can later be confirmed by human processors.

Memory-based event-triggered secure state estimation of cyber-physical systems

This paper studies the secure state estimation issue of time-varying nonlinear cyber-physical systems under false data injection attacks and a memory event-triggered mechanism. Compared to the conventional event-triggered mechanism based on current system information, a memory-based event-triggered mechanism involving the past measurement output is proposed. Under this scheme, the false triggering induced by abrupt variations of system output can be reduced effectively, and the waste of network resources is mitigated. A Bernoulli variable is utilized to describe the stochastic process of the false data injection attacks. By constructing a novel Lyapunov-Krasovskii functional related to Legendre polynomials and applying Bessel-Legendre inequality technique, sufficient conditions for guaranteeing the asymptotic stability and designing a state estimator of the estimation error system are obtained. Finally, numerical simulations are carried out to illustrate the validity of the presented approach.

A Research of Pulse Source for EFT Test of Electrical Vehicle Piles

A type of high-voltage pulse source technology generating double-exponential waveform pulse group was introduced. In this approach, the pulse interval could be adjusted with the step length of 100 μs, and the amplitude would reach up to 35 kV. This pulse source could be used to test the sensitivity of electric vehicle (EV) piles under electrical fast transient (EFT) interference. The theory of obtaining double-exponential wave and its generating circuit was analyzed, and then the influencing factors of the rising edge were expounded. A method of pulse insertion was adopted to generate a fast transient pulse group due to the limitation of the repeated operating frequency of switching devices. This method could be summarized as a common load fed by several parallel pulse sources, which were controlled and triggered in time sequence. Thus, a set of timing pulse could be obtained from the load ending. The feasibility of this method was also demonstrated. The electromagnetic interference cannot be avoidable because the load was fed by different timing sources. The high-voltage pulse generated initially causes the latter sources to be false-triggered with serious influence to the entire system. The interference generated by the couple circuit composed by distributed parameters, such as distributed capacitance and inductance, was also analyzed. A coupled model was established, analyzed, and simulated to prove the existence of the conducted interference and false triggering for other sources. The measure of conducted interference suppression was also presented. A set of experiments was carried out to show that different numbers of double-exponential pulse groups with different time intervals could be obtained.

A Variational Method for Filling in Missing Data in Doppler Velocity Fields

AbstractSingle-Doppler radar data are often missing in important regions of a severe storm due to low return power, low signal-to-noise ratio, ground clutter associated with normal and anomalous propagation, and missing radials associated with partial or total beam blockage. Missing data impact the ability of WSR-88D algorithms to detect severe weather. To aid the algorithms, we develop a variational technique that fills in Doppler velocity data voids smoothly by minimizing Doppler velocity gradients while not modifying good data. This method provides estimates of the analysed variable in data voids without creating extrema.Actual single-Doppler radar data of four tornadoes are used to demonstrate the variational algorithm. In two cases, data are missing in the original data, and in the other two, data are voided artificially. The filled-in data match the voided data well in smoothly varying Doppler velocity fields. Near singularities such as tornadic vortex signatures, the match is poor as anticipated. The algorithm does not create any velocity peaks in the former data voids, thus preventing false triggering of tornado warnings. Doppler circulation is used herein as a far-field tornado detection and advance-warning parameter. In almost all cases, the measured circulation is quite insensitive to the data that have been voided and then filled. The tornado threat is still apparent.

Characterisation of the Junction Temperature of Gallium-Nitride Power Devices via Quasi-Threshold Voltage as Temperature Sensitive Electrical Parameter

This paper presents a robust and easy-to-implement approach to measure the junction temperature of SiC power devices using quasi-threshold voltage as temperature sensitive electrical parameter with adjustable temperature sensitivity. The voltage drop across the parasitic inductance between Kelvin and power source is used to trigger the data acquisition circuit. The novelty of the proposed method lies in the concept of variable temperature sensitivity where the robustness decreases with the increase in the sensitivity. This concept proposes a trade-off between temperature sensitivity and robustness. A D flip-flop is used to make the acquisition circuit more robust to prevent false triggering while keeping fast switching speed and low noise susceptibility. Basic simulations, static and dynamic measurements are performed successfully on a commercially available 1.2 kV/120 A power module in a buck converter topology. The effect of DC-link voltage and load current invariance is also verified in this paper.

Investigation of transients in a submersible electric motor with a downhole compensator

Currently, the energy efficiency improving into the oil production is an important task. The main electricity consumer in the electrical complex structure of the electric centrifugal pumps’ installation is a submersible asynchronous electric motor. The power factor of these electric motors varies from 0.75 to 0.85. It leads to the losses’ increasing in the conductive elements of the complex. The use of downhole reactive power compensators is the most potential way to increase the power factor into the submersible asynchronous electric motors. In the course of pilot tests there are some cases of the protection devices for downhole compensators’ false triggering. It is recorded when the control station is switched off. It leads to the energy efficiency decreasing into the oil production. The purpose of this study is to research the transients in a submerged asynchronous electric motor equipped by the downhole compensator when the power supply is switched off. The task of the study is to determine the transient process’ parameters, in order to prevent false triggering of the downhole compensator protection devices. Simulation modeling of a submerged electric motor with a downhole compensator is performed in the Matlab Simulink. A simulation model of a submerged electric motor with a downhole compensator is developed to study transients when the power supply is switched off. The characteristics for the transient process of the voltage and current into the downhole compensator are obtained during the simulation modeling. The current surge for the capacitors’ discharge of the downhole compensator is 260.7% relative to the rated current at the time of the power supply disconnection. Prevention measures off false triggering for automatic shutdown devices of the downhole compensator are proposed.

Hangar fire detection alarm with algorithm for extinguisher

A fire alarm is a high-performance system that detects smoke, heat or flames and actuates fire suppression system, for the protection of lives and property. It is employed in aircraft hangars for the protection of aircraft, personnel as well as the hangar structure. The need for a fire alarm in a hangar with algorithm for extinguishers cannot be overemphasized. The structure of the hangar building, type of aircraft housed in the hangar and activities carried out at the hangar such as inspections, overhauls and modifications of aircraft, determine the type of fire alarm to be used, whether it should be automatic or manual [2]. The detection employed, be it smoke detection, heat sensing or both and the process of extinguishing in the face of a fire threat or hazard is equally important. The effectiveness of the alarm is dependent on genuine alerts and not false alarm triggers, hence in this research paper, the employment of intelligent detection using comparators in programmed IC, the Micro-controller, was interfaced with a 555 Timer, a multi-vibrator for generating aural sound for alarm, LCD Display for indicated readings as well as algorithm for extinguishing using water or foam via sprinklers. The basic work started with a block diagram representation, thereafter, individual subsystems, which form the building blocks were analyzed and the components parts identified. A circuit diagram for the project was analyzed and built using Proteus. This was simulated and found to be achievable, hence a program was written in C++ for the micro-controller using Arduino Language known as the source code. The results show hangar fire detection alarm with algorithm for extinguishing and was investigated as an effective means of suppressing fire threat in the hangar [4].

A BMI Based on Motor Imagery and Attention for Commanding a Lower-Limb Robotic Exoskeleton: A Case Study

Lower-limb robotic exoskeletons are wearable devices that can be beneficial for people with lower-extremity motor impairment because they can be valuable in rehabilitation or assistance. These devices can be controlled mentally by means of brain–machine interfaces (BMI). The aim of the present study was the design of a BMI based on motor imagery (MI) to control the gait of a lower-limb exoskeleton. The evaluation is carried out with able-bodied subjects as a preliminary study since potential users are people with motor limitations. The proposed control works as a state machine, i.e., the decoding algorithm is different to start (standing still) and to stop (walking). The BMI combines two different paradigms for reducing the false triggering rate (when the BMI identifies irrelevant brain tasks as MI), one based on motor imagery and another one based on the attention to the gait of the user. Research was divided into two parts. First, during the training phase, results showed an average accuracy of 68.44 ± 8.46% for the MI paradigm and 65.45 ± 5.53% for the attention paradigm. Then, during the test phase, the exoskeleton was controlled by the BMI and the average performance was 64.50 ± 10.66%, with very few false positives. Participants completed various sessions and there was a significant improvement over time. These results indicate that, after several sessions, the developed system may be employed for controlling a lower-limb exoskeleton, which could benefit people with motor impairment as an assistance device and/or as a therapeutic approach with very limited false activations.

Machine Learning based Autonomous Fire Combat Turret

The time lag between the identification and the initiation of the actuation protocol is more in conventional fire combat system. This in turn increases the response time resulting in financial loss as well as injuries to human beings. In this paper an efficient method of fire combat is proposed to eliminate resource loss. This system extinguishes fire before it reaches its destructive level. It eliminates all the flaws of the conventional fire extinguishers and improves the damage limitation by raising an alarm. Further by applying HAAR cascade classifier machine learning algorithm, accuracy of 70-75 % is achieved to detect fire. It also provides minimum latency and optimal response in detecting fires and differentiating them from false triggers. It is observed that the response time of proposed fire combat system is 2-4 seconds. The automatic mode is reliable in the presence of multiple units that are deployed in the same area of interest. The system is able to cover the entire hemispheric 3D volume of the room as per the industrial and domestic safety standards.&#x0D;

Reducing False Triggering Caused by Irrelevant Mental Activities in Brain-Computer Interface Based on Motor Imagery.

In recent years, the brain-computer interface (BCI) based on motor imagery (MI) has been considered as a potential post-stroke rehabilitation technology. However, the recognition of MI relies on the event-related desynchronization (ERD) feature, which has poor task specificity. Further, there is the problem of false triggering (irrelevant mental activities recognized as the MI of the target limb). In this paper, we discuss the feasibility of reducing the false triggering rate using a novel paradigm, in which the steady-state somatosensory evoked potential (SSSEP) is combined with the MI (MI-SSSEP). Data from the target (right hand MI) and nontarget task (rest) were used to establish the recognition model, and three kinds of interference tasks were used to test the false triggering performance. In the MI-SSSEP paradigm, ERD and SSSEP features modulated by MI could be used for recognition, while in the MI paradigm, only ERD features could be used. The results showed that the false triggering rate of interference tasks with SSSEP features was reduced to 29.3%, which was far lower than the 55.5% seen under the MI paradigm with ERD features. Moreover, in the MI-SSSEP paradigm, the recognition rate of the target and nontarget task was also significantly improved. Further analysis showed that the specificity of SSSEP was significantly higher than that of ERD (p < 0.05), but the sensitivity was not significantly different. These results indicated that SSSEP modulated by MI could more specifically decode the target task MI, and thereby may have potential in achieving more accurate rehabilitation training.

Perceived cognitive failures and quality of life for older adults with bipolar disorder

BackgroundOlder adults with bipolar disorder (BD) commonly present with cognitive deficits (e.g., attention, memory, verbal fluency). Concomitantly, older adults with BD commonly report subjective or perceived cognitive failures. For this study, we confirmed a 3-factor model of cognitive failures first validated with older adults free of mental illness (i.e., forgetfulness, distractibility, false triggering). We then computed a structural equation model (SEM) demonstrating the construct validity of perceived cognitive errors in relation to quality of life with BD. Use of SEM enabled us to measure quality of life broadly and germane to BD (i.e., well-being, life satisfaction, alcohol misuse, sleep quality). MethodsWe obtained responses from an international sample of 350 older adults with BD (M = 61.26 years of age, range 50–87), recruited via micro-targeted social media advertising. Most lived in Canada, the U.S., U.K., Ireland, Australia and South Africa. ResultsAs hypothesized, perceived cognitive failures were predicted by BD symptoms (depression and hypo/mania). And cognitive failures directly and indirectly predicted quality of life. LimitationsFuture research is needed to replicate this QoL model over time with younger patients and those recruited using more traditional methods. ConclusionsPerceived cognitive failures may not be strongly correlated with objective indices of cognitive deficits; nonetheless perceived cognitive failures are significantly associated with quality of life for older adults with BD. For both cognitive errors and BD symptoms, their indirect effect on quality of life (via suicide ideation) is greater than the direct effect.

Study on the Reduced Reliability of A Certain Amplifier Caused by Electrostatic Discharge (ESD)

This paper introduces and analyzes the single-channel tripping accident of a reactor as a result of false triggering of a certain amplifier caused by electrostatic discharge (ESD). In response to this problem, a simulated operational amplifier circuit platform is built in practice to verify the analysis results, and a solution is proposed at last. In addition, further analysis is made to the existing preventive maintenance plans, and cable shielding is found to be problematic; therefore, the principle and analysis of cable shielding are given here.

Mesures for eradication of signaling subsystem false triggering in the AMT telemechanics system within the range of Chita power supply distance of Zabaykalskaya railroad, the subdepartment of Russian Railways

Mesures for eradication of signaling subsystem false triggering in the AMT telemechanics system within the range of Chita power supply distance of Zabaykalskaya railroad, the subdepartment of Russian Railways