A Novel Method of Failure Sample Selection for Electrical Systems Using Ant Colony Optimization

The influence of failure propagation is ignored in failure sample selection based on traditional testability demonstration experiment method. Traditional failure sample selection generally causes the omission of some failures during the selection and this phenomenon could lead to some fearful risks of usage because these failures will lead to serious propagation failures. This paper proposes a new failure sample selection method to solve the problem. First, the method uses a directed graph and ant colony optimization (ACO) to obtain a subsequent failure propagation set (SFPS) based on failure propagation model and then we propose a new failure sample selection method on the basis of the number of SFPS. Compared with traditional sampling plan, this method is able to improve the coverage of testing failure samples, increase the capacity of diagnosis, and decrease the risk of using

Fault Modeling and Testing for Analog Circuits in Complex Space Based on Supply Current and Output Voltage

This paper deals with the modeling of fault for analog circuits. A two-dimensional (2D) fault model is first proposed based on collaborative analysis of supply current and output voltage. This model is a family of circle loci on the complex plane, and it simplifies greatly the algorithms for test point selection and potential fault simulations, which are primary difficulties in fault diagnosis of analog circuits. Furthermore, in order to reduce the difficulty of fault location, an improved fault model in three-dimensional (3D) complex space is proposed, which achieves a far better fault detection ratio (FDR) against measurement error and parametric tolerance. To address the problem of fault masking in both 2D and 3D fault models, this paper proposes an effective design for testability (DFT) method. By adding redundant bypassing-components in the circuit under test (CUT), this method achieves excellent fault isolation ratio (FIR) in ambiguity group isolation. The efficacy of the proposed model and testing method is validated through experimental results provided in this paper

A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits’ single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits’ single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments

Enhancing Low-Light Images Using Infrared-Encoded Images

Low-light image enhancement task is essential yet challenging as it is ill-posed intrinsically. Previous arts mainly focus on the low-light images captured in the visible spectrum using pixel-wise loss, which limits the capacity of recovering the brightness, contrast, and texture details due to the small number of income photons. In this work, we propose a novel approach to increase the visibility of images captured under low-light environments by removing the in-camera infrared (IR) cut-off filter, which allows for the capture of more photons and results in improved signal-to-noise ratio due to the inclusion of information from the IR spectrum. To verify the proposed strategy, we collect a paired dataset of low-light images captured without the IR cut-off filter, with corresponding long-exposure reference images with an external filter. The experimental results on the proposed dataset demonstrate the effectiveness of the proposed method, showing better performance quantitatively and qualitatively. The dataset and code are publicly available at https://wyf0912.github.io/ELIEI/Comment: The first two authors contribute equally. The work is accepted by ICIP 202

Reasoning over Hierarchical Question Decomposition Tree for Explainable Question Answering

Explainable question answering (XQA) aims to answer a given question and provide an explanation why the answer is selected. Existing XQA methods focus on reasoning on a single knowledge source, e.g., structured knowledge bases, unstructured corpora, etc. However, integrating information from heterogeneous knowledge sources is essential to answer complex questions. In this paper, we propose to leverage question decomposing for heterogeneous knowledge integration, by breaking down a complex question into simpler ones, and selecting the appropriate knowledge source for each sub-question. To facilitate reasoning, we propose a novel two-stage XQA framework, Reasoning over Hierarchical Question Decomposition Tree (RoHT). First, we build the Hierarchical Question Decomposition Tree (HQDT) to understand the semantics of a complex question; then, we conduct probabilistic reasoning over HQDT from root to leaves recursively, to aggregate heterogeneous knowledge at different tree levels and search for a best solution considering the decomposing and answering probabilities. The experiments on complex QA datasets KQA Pro and Musique show that our framework outperforms SOTA methods significantly, demonstrating the effectiveness of leveraging question decomposing for knowledge integration and our RoHT framework.Comment: has been accepted by ACL202

A Statistic-Based Calibration Method for TIADC System

Time-interleaved technique is widely used to increase the sampling rate of analog-to-digital converter (ADC). However, the channel mismatches degrade the performance of time-interleaved ADC (TIADC). Therefore, a statistic-based calibration method for TIADC is proposed in this paper. The average value of sampling points is utilized to calculate offset error, and the summation of sampling points is used to calculate gain error. After offset and gain error are obtained, they are calibrated by offset and gain adjustment elements in ADC. Timing skew is calibrated by an iterative method. The product of sampling points of two adjacent subchannels is used as a metric for calibration. The proposed method is employed to calibrate mismatches in a four-channel 5 GS/s TIADC system. Simulation results show that the proposed method can estimate mismatches accurately in a wide frequency range. It is also proved that an accurate estimation can be obtained even if the signal noise ratio (SNR) of input signal is 20 dB. Furthermore, the results obtained from a real four-channel 5 GS/s TIADC system demonstrate the effectiveness of the proposed method. We can see that the spectra spurs due to mismatches have been effectively eliminated after calibration

Defect Automatic Identification of Eddy Current Pulsed Thermography

Eddy current pulsed thermography (ECPT) is an effective nondestructive testing and evaluation (NDT&E) technique, and has been applied for a wide range of conductive materials. Manual selected frames have been used for defects detection and quantification. Defects are indicated by high/low temperature in the frames. However, the variation of surface emissivity sometimes introduces illusory temperature inhomogeneity and results in false alarm. To improve the probability of detection, this paper proposes a two-heat balance states-based method which can restrain the influence of the emissivity. In addition, the independent component analysis (ICA) is also applied to automatically identify defect patterns and quantify the defects. An experiment was carried out to validate the proposed methods

Evolutionary conservation of nested MIR159 structural microRNA genes and their promoter characterization in Arabidopsis thaliana

MicroRNAs (miRNAs) are endogenous small RNAs, that are vital for gene expression regulation in eukaryotes. Whenever a pri-miRNA precursor includes another miRNA precursor, and both of these precursors may generate independent, non-overlapping mature miRNAs, we named them nested miRNAs. However, the extent of nested miR159 structural evolutionary conservation and its promoter characterization remains unknown. In this study, the sequence alignment and phylogenetic analysis reveal that the MIR159 family is ancient, and its nested miR159 structures are evolutionary conserved in different plant species. The overexpression of ath-MIR159a, including the 1.2 kb downstream region, has no effect on rescuing the mir159ab phenotype. The promoter truncation results revealed that the 1.0 kb promoter of ath-MIR159a is sufficient for rescuing the mir159ab phenotype. The cis-regulatory elements in the ath-miR159a promoters indicated functions related to different phytohormones, abiotic stresses, and transcriptional activation. While the MybSt1 motif-containing region is not responsible for activating the regulation of the miR159a promoter. The qRT-PCR results showed that overexpression of ath-MIR159a led to high expression levels of miR159a.1–5 and miR159a.1–3 and complemented the growth defect of mir159ab via downregulation of MYB33 and MYB65. Furthermore, continuously higher expression of the miR159a.2 duplex in transgenic lines with the curly leaf phenotype indicates that miR159a.2 is functional in Arabidopsis and suggests that it is possible for a miRNA precursor to encode several regulatory small RNAs in plants. Taken together, our study demonstrates that the nested miR159 structure is evolutionary conserved and miRNA-mediated gene regulation is more complex than previously thought

Performance characteristics of 18F–fluorodeoxyglucose in non-infected hip replacement

PurposeThe aim of this study was to retrospectively analyze 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/ computed tomography (CT) images of non-infected hip arthroplasty patients and summarize findings that may be useful for clinical practice.Methods18F-FDG PET/CT images of non-infected hip arthroplasty patients were collected from September 2009 to August 2021. The region of interest was independently delineated by two physicians and maximum standardized uptake values (SUVmax) were recorded and compared. Serologic data were also collected and the correlation between SUVmax and serologic parameters was analyzed, while the images were classified based on the 18F-FDG uptake pattern in the images using the diagnostic criteria proposed by Reinartz et al. (9). The interval between hip replacement and PET/CT was classified by year and the characteristics of the two groups were compared. The images of patients who underwent PET/CT multiple times were analyzed dynamically.ResultsA total of 121 examinations were included; six patients underwent PET/CT twice and two patients had three scans. There were no significant correlations between SUVmax and serologic results. The interobserver agreement between the two physicians in the classification according to the criteria of Reinartz et al. (9) was 0.957 (P < 0.005). Although there was non-specific uptake in cases with an arthroplasty-to-PET/CT interval this was non-significant. Additionally, 18F-FDG showed potential utility for dynamic observation of the condition of the hip.ConclusionSUVmax provided information independent of serologic results, meanwhile 18F-FDG showed potential applicability to the dynamic monitoring of hip arthroplasty-related diseases. However, the presence of blood vessels and muscles affected image interpretation and the specificity of 18F-FDG was not optimal. A more specific radionuclide is needed to maximize the benefits of using PET/CT for the assessment of periprosthetic joint infection (PJI)