Passive Detection Research Articles

User credibility evaluation for reputation measurement of online service

PurposeUsers often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.Design/methodology/approachIn this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.FindingsTheoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.Originality/valueThe proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.

Asymptomatic Plasmodium falciparum carriage at the end of the dry season is associated with subsequent infection and clinical malaria in Eastern Gambia.

Chronic carriage of asymptomatic low-density Plasmodium falciparum parasitaemia in the dry season may support maintenance of acquired immunity that protects against clinical malaria. However, the relationship between chronic low-density infections and subsequent risk of clinical malaria episodes remains unclear. In a 2-years study (December 2014 to December 2016) in eastern Gambia, nine cross-sectional surveys using molecular parasite detection were performed in the dry and wet season. During the 2016 malaria transmission season, passive case detection identified episodes of clinical malaria. Among the 5256 samples collected, 444 (8.4%) were positive for P. falciparum. A multivariate model identified village of residence, male sex, age ≥ 5 years old, anaemia, and fever as independent factors associated with P. falciparum parasite carriage. Infections did not cluster over time within the same households or recurred among neighbouring households. Asymptomatic parasite carriage at the end of dry season was associated with a higher risk of infection (Hazard Ratio, HR = 3.0, p < 0.0001) and clinical malaria (HR = 1.561, p = 0.057) during the following transmission season. Age and village of residence were additional predictors of infection and clinical malaria during the transmission season. Chronic parasite carriage during the dry season is associated with an increased risk of malaria infection and clinical malaria. It is unclear whether this is due to environmental exposure or to other factors.

Islanding detection of synchronous distributed generators

This paper analyses the performance of local passive islanding detection methods for synchronous distributed generators, under different grid and load scenarios. These methods monitor electrical parameters at the interconnection point of a distributed generator and detect island situation whenever these parameters change correspondingly. Lately, islanding detection research has been focused on inverter based systems. But synchronous generators still pose a challenge for study. With this aim, a low voltage distribution network with embedded synchronous generators has been modelled. The performance of frequency and rate-of-change-of-frequency relays have been evaluated, analysing the influence of power mismatch and generator characteristics on the islanding and also avoid false operation.

Retraction Note: Passive islanding detection in microgrids using artificial neural networks

Retraction Note: Passive islanding detection in microgrids using artificial neural networks

Ionizing Radiation Responsive Anomalous Photovoltage Drives Sensitive Self‐Powered X‐Ray Detection

AbstractThe anomalous photovoltaic (APV) effect in organic–inorganic hybrid perovskites (OIHPs) has attracted massive interest for developing high‐performance optoelectronic devices. However, exploring the ionizing radiation responsive APV effect remains blank, let alone its potential applications. Herein, the unprecedented APV behavior in a 1D lead‐free OIHP, (4‐AMP)BiI5 (ABI, 4‐AMP = 4‐(aminomethyl)pyridine) under X‐ray irradiation is reported, exhibiting a large above‐bandgap bulk photovoltage of ≈10 V. Such a strong APV effect is closely related to the intrinsic electric polarization in polar ABI, which acts as the driving force for X‐ray‐generated carriers’ separation and transport, thus allowing it to be self‐powered. As a result, sensitive self‐powered X‐ray detectors based on high‐quality ABI single crystals are successfully fabricated, possessing a high sensitivity of 66.84 µC Gy−1 cm−2, a low detection limit of 482 nGy s−1, and superior operational stability. This work first demonstrates the ionizing radiation‐responsive APV effect in OIHPs, which further enables passive radiation detection.

Dual-Feature-Based Bubble Sound Detection Method and Its Application in Passive Acoustical Detection of Underwater Gas Leakage

Dual-Feature-Based Bubble Sound Detection Method and Its Application in Passive Acoustical Detection of Underwater Gas Leakage

ОЦЕНКА СИСТЕМЫ ЭПИДЕМИОЛОГИЧЕСКОГО НАДЗОРА ЗА КОРЬЮ В Г. ДУШАНБЕ, 2023 Г.

Objective: To thoroughly evaluate the current measles epidemiological surveillance (ES) system in Dushanbe, Republic of Tajikistan (RT), to uncover its strong points and areas for improvement. Methods: The ES system evaluation for measles was conducted from January to May 2023 using updated guidelines from the Centers for Disease Control (CDC), USA, for ES system evaluation. Results: Upon analysis, it was found that the ES system for measles in Dushanbe functions within an overcomplicated framework that does not have proper integration with medical data systems. The current system experiences delays in sharing data at all levels; it is based on passive case detection via patient self-referral. 32.2% of patients visit urban health centers (UHC), while 67.8% go to infectious diseases hospitals. Shortcomings have been found in disseminating knowledge and implementing approved methodological recommendations by the Ministry of Health and Social Protection of the Population of the Republic of Tajikistan (MHSPP RT) in the State Sanitary Epidemiological Surveillance Service (SSESS) centers. This deficiency is due to the absence of guidelines on the Ministry's official website, the lack of a centralized repository of guidelines, and the unavailability of training platforms for epidemiologists. Although about 80% of patients have access to measles laboratory diagnostics, the system's reliance on external funding raises issues regarding its effectiveness. Insufficient human and financial resources have been identified as barriers to timely decision-making, as illustrated by the delays in rolling out mass supplementary childhood vaccinations in September 2022 following a measles outbreak detected in January 2022. Conclusion: ing out mass supplementary childhood vaccinations in September 2022 following a measles outbreak detected in January 2022. Conclusion: To achieve the country's objective of eradicating measles, the measles ES system in Dushanbe requires additional funding for emergency outbreak response. Establishing a robust training and information-sharing platform is essential to address the existing deficiencies in disseminating and implementing guidelines Keywords: Measles, epidemiological surveillance system, assessment, Dushanbe

Passive Islanding Detection Method based on Resultant Sequence Impedance Component and Load Shedding in Islanded Area

Passive Islanding Detection Method based on Resultant Sequence Impedance Component and Load Shedding in Islanded Area

Passive Single-Photon Point Target Detection Based on First-Photon Time

Passive Single-Photon Point Target Detection Based on First-Photon Time

Multimodal evaluation of blood-brain barrier opening in mice in response to low-intensity ultrasound and a claudin-5 binder.

Background: The blood-brain barrier (BBB) is a major bottleneck in delivering therapeutics to the brain. Treatment strategies to transiently open this barrier include focused ultrasound combined with intravenously injected microbubbles (FUS+MB) and targeting of molecules that regulate BBB permeability. Methods: Here, we investigated BBB opening mediated by the claudin-5 binder cCPEm (a microorganismal toxin in a truncated form) and FUS+MB at a centre frequency of 1 MHz, assessing dextran uptake, broadband emission, and endogenous immunoglobulin G (IgG) extravasation. Results: FUS+MB-induced BBB opening was detectable at a pressure ≥0.35 MPa when assessed for leakage of 10 and 70 kDa dextran, and at ≥0.2 MPa for uptake of endogenous IgG. Treating mice with 20 mg/kg cCPEm failed to open the BBB, and pre-treatment with cCPEm followed by FUS+MB at 0.2 and 0.3 MPa did not overtly increase BBB opening compared to FUS+MB alone. Using passive cavitation detection (PCD), we found that broadband emission correlated with the peak negative pressure (PNP) and dextran leakage, indicating the possibility of using broadband emission for developing a feedback controller to monitor BBB opening. Conclusions: Together, our study highlights the challenges in developing combinatorial approaches to open the BBB and presents an additional IgG-based histological detection method for BBB opening.

Enhancing Industrial Security with IoT-based Passive Intrusion Detection and Segmentation

Enhancing Industrial Security with IoT-based Passive Intrusion Detection and Segmentation

Low-Complexity LRT-Based Passive Radar Target Detection Algorithm in Interfering Conditions

Low-Complexity LRT-Based Passive Radar Target Detection Algorithm in Interfering Conditions

Particle Filter-based Passive Islanding Detection Scheme for Renewable Energy Penetrated Distribution Systems

Particle Filter-based Passive Islanding Detection Scheme for Renewable Energy Penetrated Distribution Systems

Passive Islanding Detection Scheme Based on Instantaneous Voltage and Current for a Multi-DG Microgrid

Passive Islanding Detection Scheme Based on Instantaneous Voltage and Current for a Multi-DG Microgrid

A hybrid IDM using wavelet transform for a synchronous generator-based RES with zero non-detection zone

&lt;abstract&gt; &lt;p&gt;Increased use of renewable energy sources in distribution grids has led to the growing concern over unintentional islanding. Among the available islanding detection methods, the passive methods have larger non-detection zones and are susceptible to system faults. However, they have no effect on power quality like active methods. We present a hybrid method for the islanding detection of synchronous generator-based renewable energy sources. Here, the larger non-detection zone issue of the passive islanding detection method was reduced by combining it with a wavelet transform. The rate of change of a voltage unbalanced factor was computed from the sequence components of the renewable energy source terminal voltage. Then, the factor was analyzed using a wavelet transform, and a threshold for the factor was found. The robustness of the method was tested for several islanding as well as non-islanding situations. The efficacy of the method was also tested in multi-source test systems. From the analysis, it was observed that the proposed method was fast, reliable, and had a zero non-detection zone.&lt;/p&gt; &lt;/abstract&gt;

RIS-Aided Passive Detection for LSS Targets: A GNSS Multipath-Assisted Scheme

RIS-Aided Passive Detection for LSS Targets: A GNSS Multipath-Assisted Scheme

Mini/Micro UAV detection in the presence of ISM or spurious signals and an experimental application on an SDR

In recent years, Mini/Micro UAVs have started to become a major concern and threat to the public, which made the need of detection and classification of them inevitable. Among all known detection techniques, one of the best reassuring and promising approach is utilizing the passive RF detection method. One of the major problems in this technique is detecting the threats in the presence of the other wireless interference signals like ISM Band Based or Spurious Signals. Proposed study handles this task using hybrid discrimination techniques both utilizing Signal Analysis/Decoding and Overlapping Signal Removal methods. In the first part of the technique, the captured signals are decoded to detect and get RF parameters of Wi-Fi signals and therefore the detected ones are removed from the corresponding spectrums in the time domain which prevents the miscalculation of the center frequency and bandwidth caused by overlapping Wi-Fi signals. In the second part of the technique, developed pulse on pulse (PoP) algorithms are employed in order to calculate more precisely the center frequency and bandwidth of the threat. Both methods developed on an SDR are experimented on both laboratory and field. By means of PoP Algorithms, the calculated deviation center frequency of the one of the Mini/Micro UAVs’ signal is improved from 103 ppm to 61.2 ppm in the presence of wideband overlapping spurious signals. The bandwidth correction is also achieved and makes the bandwidth to be calculated precisely. When Wi-Fi signals are decoded corresponding technique is applied additionally, in frequency domain, the center frequency estimation improved from 61.2 ppm to 28.5 ppm. These results show that the proposed method outperforms the results given in laboratory and field tests.

Improved assessment sensitivity of time-varying cavitation events based on wavelet analysis

Ultrasonic cavitation, characterized by the oscillation or abrupt collapse of cavitation nuclei in response to ultrasound stimulation, plays a significant role in various applications within both industrial and biomedical sectors. In particular, inertial cavitation (IC) has garnered considerable attention due to the resulting mechanical, chemical, and thermal effects. Passive cavitation detection (PCD) has emerged as a valuable technique for monitoring this procedure. While the fast Fourier transform (FFT) is a widely used algorithm to analyze IC-induced broadband noise detected by PCD system, it may not adequately capture the time-varying instability of cavitation due to potential nuclei collapse during ultrasound irradiation. In contrast, the continuous wavelet transform offers a more flexible approach, enabling more sensitive analysis of signals with varying frequencies over time. In this study, nanodiamond (ND) and its derivative, nitro-doped nanodiamond (N-AND), known to possess cavitation potential from previous research, were chosen as the source of cavitation nuclei. The cavitation signals detected by PCD were subjected to both FFT and wavelet analyses, with their results comprehensively compared. This research showcased the feasibility of employing wavelet analysis for effective inertial cavitation evaluation. It provided the advantage of monitoring the temporal evolution of cavitation events in real-time, enhancing sensitivity to weak and unstable cavitation signals, especially those in higher order components (3rd and 4th order). Additionally, it yielded a higher level of precision in determining IC thresholds and doses. Furthermore, the inclusion of time information through wavelet analysis offered insights into the limitations of low-cycle ultrasound in inducing IC. This study introduces a novel perspective for more sensitive and precise cavitation assessment, leveraging time and frequency data from wavelet analysis, and holds promise for effective utilization of cavitation effects while minimizing losses and damages resulting from unintended cavitation events.

A survey on passive digital video forgery detection techniques

Digital media devices such as smartphones, cameras, and notebooks are becoming increasingly popular. Through digital platforms such as Facebook, WhatsApp, Twitter, and others, people share digital images, videos, and audio in large quantities. Especially in a crime scene investigation, digital evidence plays a crucial role in a courtroom. Manipulating video content with high-quality software tools is easier, which helps fabricate video content more efficiently. It is therefore necessary to develop an authenticating method for detecting and verifying manipulated videos. The objective of this paper is to provide a comprehensive review of the passive methods for detecting video forgeries. This survey has the primary goal of studying and analyzing the existing passive techniques for detecting video forgeries. First, an overview of the basic information needed to understand video forgery detection is presented. Later, it provides an in-depth understanding of the techniques used in the spatial, temporal, and spatio-temporal domain analysis of videos, datasets used, and their limitations are reviewed. In the following sections, standard benchmark video forgery datasets and the generalized architecture for passive video forgery detection techniques are discussed in more depth. Finally, identifying loopholes in existing surveys so detecting forged videos much more effectively in the future are discussed.

Comparative Study of Histotripsy Pulse Parameters Used to Inactivate Escherichia coli in Suspension.

Bacterial loads can be effectively reduced using cavitation-mediated focused ultrasound, or histotripsy. In this study, gram-negative bacteria (Escherichia coli) in suspension were used as model bacteria to evaluate the effectiveness of two regimens of histotripsy treatments: cavitation histotripsy (CH) and boiling histotripsy (BH). Ten-milliliter volumes of Escherichia coli were treated at different negative focal pressure amplitudes and over time periods up to 40 min. Cavitation activity was characterized with coaxial passive cavitation detection (PCD) and synchronized plane wave B-mode imaging. CH treatments exhibited a threshold behavior that was consistent with PCD metrics of cavitation. Above the threshold, bacterial inactivation followed a monotonically increasing log-linear relationship that indicated an exponential inactivation rate. BH exhibited no threshold, but instead followed a different monotonically increasing inactivation rate. Inactivation rates were larger for BH at or below the CH threshold, and larger for CH substantially above the threshold. CH studies performed at different pulse lengths at the same duty cycle had similar inactivation rates, suggesting that at any given pressure amplitude, the "on time" was the most important variable for inactivating E. coli. The maximum inactivation was produced by CH at the highest pressure amplitudes used, leading to a log reduction >4.2 for a 40 min treatment. The results of this study suggest that both CH and BH can be used to inactivate E. coli in suspension, with the optimal regimen depending on the attainable peak negative focal pressure at the target.