An Efficient Approach for Uncertain Event Detection in RFID Complex Event Processing

The globalization of manufacturing has increased the risk of counterfeiting as the demand grows, the production flow increases, and the availability expands. The intensifying counterfeit issues causing a worriment to companies and putting lives at risk. Companies have ploughed a large amount of money into defensive measures, but their efforts have not slowed counterfeiters. In such complex manufacturing processes, decision-making and real-time reactions to uncertain situations throughout the production process are one way to exploit the challenges. Detecting uncertain conditions such as counterfeit and missing items in the manufacturing environment requires a specialized set of technologies to deal with a flow of continuously created data. In this paper, we propose an uncertain detection algorithm (UDA), an approach to detect uncertain events such as counterfeit and missing items in the RFID distributed system for a manufacturing environment. The proposed method is based on the hashing and thread pool technique to solve high memory consumption, long processing time and low event throughput in the current detection approaches. The experimental results show that the execution time of the proposed method is averagely reduced 22% in different tests, and our proposed method has better performance in processing time based on RFID event streams.

Intrinsic time decomposition based differential protection with adaptive threshold for UPFC compensated transmission line

In the presence of nonlinear response created by power electronics-based compensators, reliable fault detection and classification by distance protection relays is a major concern. The unified power flow controller (UPFC) has a dynamic characteristics that causes stability and protection issues. A intrinsic time decomposition (ITD) based strategy is proposed for addressing this issue. A differential energy based detection index computed using ITD and adaptive thresholding technique is employed such that unerring fault detection is achieved wherein faulty phases of a UPFC compensated transmission line are well pointed out. Various fault and non-fault cases considering critical power system conditions are analysed for power systems with varying configurations modelled using EMTDC/PSCAD. A comparison of the current detection method to recently proposed techniques reveals the benefits and feasibility of the presented detection strategy, which has been proved to be accurate and efficient.

A Precise Current Detection Method Using a Single Shunt and FET Rds(on) of a Low-Voltage Three-Phase Inverter

In this study, a low-voltage three-phase inverter was used alongside a shunt resistor to measure the current. However, it is known that this type of inverter and shunt resistor system has a region where the measurement of current is impossible due to structural limitations. As a result, many studies have focused on this region through the use of additional algorithms. Most studies measured current by forcibly adjusting the PWM duty in order to measure the current at the region where it could not be sensed. However, unfortunately, the total harmonic distortion (THD) increases in the current due to PWM adjustment. This causes an increase in torque ripple and inverter control instability. Therefore, in this paper, current was measured using the Rds(on) value between the drain source resistor when MOSFET was turned on and the Kalman filter in a low-voltage three-phase inverter with a single shunt. Additionally, the value was verified via comparison with the values achieved when a Hall-type current sensor and single shunt were used. As a result, this study confirmed that the inverter with a single shunt performs the same as a Hall-type sensor at the region where current cannot be detected.

Clinical Evaluation of a New Antigen-Based COVID-19 Rapid Diagnostic Test from Symptomatic Patients

Accurate diagnosis at the right moment is the prerequisite for treatment of any disease. Failure to correctly diagnose a disease can result in highly detrimental effects, unmistakably a crucial factor during the COVID-19 pandemic. RT-PCR is the gold standard for COVID-19 detection while there are other test procedures available, such as LAMP, X-Ray, and ELISA. However, these tests are expensive, require sophisticated equipment and a highly trained workforce, and multiple hours or even days are often required to obtain the test results. A rapid and cheap detection system can thus render a solution to the screening system on a larger scale and be added as an aid to the current detection processes. Recently, some rapid antigen-based COVID-19 tests devices have been developed and commercialized. In this study, we evaluated the clinical performance of a new rapid detection device (OnSite® COVID-19 Ag Rapid Test by CTK Biotech Inc., Poway, CA, USA) on COVID-19 symptomatic patients (n = 380). The overall sensitivity and specificity were 91.0% (95% CI: 84.8–95.3%) and 99.2% (95% CI: 97.1–99.9), against gold standard RT-PCR. The kit was capable of detecting patients even after 06 days of onset of symptoms and the sensitivity can be maximized to 98% in samples with an average RT-PCR Ct ≤ 26.48, demonstrating a high potential of the kit for clinical diagnosis of symptomatic patients in healthcare facilities.

High-Sensitivity Tunnel Magnetoresistance Sensors Based on Double Indirect and Direct Exchange Coupling Effect*

Detection of ultralow magnetic field requires magnetic sensors with high sensitivity and low noise level, especially for low operating frequency applications. We investigated the transport properties of tunnel magnetoresistance (TMR) sensors based on the double indirect exchange coupling effect. The TMR ratio of about 150% was obtained in the magnetic tunnel junctions and linear response to an in-plane magnetic field was successfully achieved. A high sensitivity of 1.85%/Oe was achieved due to a designed soft pinned sensing layer of CoFeB/NiFe/Ru/IrMn. Furthermore, the voltage output sensitivity and the noise level of 10.7 mV/V/Oe, 10 nT/Hz1/2 at 1 Hz and 3.3 nT/Hz1/2 at 10 Hz were achieved in Full Wheatstone Bridge configuration. This kind of magnetic sensors can be used in the field of smart grid for current detection and sensing.

Click Fraud in Digital Advertising: A Comprehensive Survey

Recent research has revealed an alarming prevalence of click fraud in online advertising systems. In this article, we present a comprehensive study on the usage and impact of bots in performing click fraud in the realm of digital advertising. Specifically, we first provide an in-depth investigation of different known categories of Web-bots along with their malicious activities and associated threats. We then ask a series of questions to distinguish between the important behavioral characteristics of bots versus humans in conducting click fraud within modern-day ad platforms. Subsequently, we provide an overview of the current detection and threat mitigation strategies pertaining to click fraud as discussed in the literature, and we categorize the surveyed techniques based on which specific actors within a digital advertising system are most likely to deploy them. We also offer insights into some of the best-known real-world click bots and their respective ad fraud campaigns observed to date. According to our knowledge, this paper is the most comprehensive research study of its kind, as it examines the problem of click fraud both from a theoretical as well as practical perspective.

Genome-Wide Scanning of Potential Hotspots for Adenosine Methylation: A Potential Path to Neuronal Development

Methylation of adenosines at N6 position (m6A) is the most frequent internal modification in mRNAs of the human genome and attributable to diverse roles in physiological development, and pathophysiological processes. However, studies on the role of m6A in neuronal development are sparse and not well-documented. The m6A detection remains challenging due to its inconsistent pattern and less sensitivity by the current detection techniques. Therefore, we applied a sliding window technique to identify the consensus site (5′-GGACT-3′) n ≥ 2 and annotated all m6A hotspots in the human genome. Over 6.78 × 107 hotspots were identified and 96.4% were found to be located in the non-coding regions, suggesting that methylation occurs before splicing. Several genes, RPS6K, NRP1, NRXN, EGFR, YTHDF2, have been involved in various stages of neuron development and their functioning. However, the contribution of m6A in these genes needs further validation in the experimental model. Thus, the present study elaborates the location of m6A in the human genome and its function in neuron physiology.