Differential Detection Method Research Articles

Multi-Step Attack Detection Based on Pre-Trained Hidden Markov Models.

Currently, hidden Markov-based multi-step attack detection models are mainly trained using the unsupervised Baum–Welch algorithm. The Baum–Welch algorithm is sensitive to the initial values of model parameters. However, its training uses random or average parameter initialization methods, which frequently results in the model training into a local optimum, thus, making the model unable to fit the alert logs well and thereby reducing the detection effectiveness of the model. To solve this issue, we propose a pre-training method for multi-step attack detection models based on the high semantic similarity of alerts in the same attack phase. The method first clusters the alerts based on their semantic information and pre-classifies the attack phase to which each alert belongs. Then, the distance of the alert vector to each attack stage is converted into the probability of generating alerts in each attack stage, replacing the initial value of Baum–Welch. The effectiveness of the proposed method is evaluated using the DARPA 2000 dataset, DEFCON21 CTF dataset, and ISCXIDS 2012 dataset. The experimental results show that the hidden Markov multi-step attack detection method based on pre-training of the proposed model parameters had higher detection accuracy than the Baum–Welch-based, K-means-based, and transfer learning differential evolution-based hidden Markov multi-step attack detection methods.

Research on infrared imaging detection and differential spectrum filtering detection methods for industrial gas leakage

Research on infrared imaging detection and differential spectrum filtering detection methods for industrial gas leakage

Two-stage digital differential atomic spin precession detection method

We propose and experimentally demonstrate a two-stage digital differential method for atomic spin precession detection. The first differential operation is carried out with a polarimeter module and subsequent digital differential. The second differential operation is achieved by orthogonally modulating the polarization direction of a linearly polarized probe light with a LiNbO3 electro-optic modulation module and by digitally demodulating the difference in the outputs corresponding to the positive and negative half periods of the modulation square-waves. This method is insensitive to the error of modulator and double sensitivity coefficient was obtained. The built detection system with the digital circuit was applied to a spin-exchange relaxation-free magnetometer, and the sensitivity coefficient, sensitivity, and bias instability were tested and compared with two other typical detection methods. The highest sensitivity and minimum bias instability and noise were achieved with the proposed method.

Comparison of forward and backward Lagrangian transport modelling to determine methane emissions from anaerobic digestion facilities

In biogas plants, where biological treatment of organic matter by anaerobic digestion (AD) is performed, as well as in plants for upgrading of biogas to biomethane, there might be emissions to air from different parts of the plants. Precise and comparable methods to quantify methane (CH 4 ) emissions from biogas plants are necessary to evaluate mitigation strategies and to generate more accurate emissions factors for national emission inventories in the context of the United Nations Framework Convention on Climate Change (UNFCCC) reporting. The main objective of this study was to provide recommendations for the measurement and modelling procedures of inverse dispersion modelling (IDM) to assure comparability of CH 4 emissions among diverse approaches and AD facilities. Two Lagrangian stochastic dispersion models were used operating in forward (LASAT) and backward (WindTrax) mode based on open-path concentration and meteorological data acquired by three international measurement teams at two biogas plants. The sensitivity analysis of the modelling systems regarding input parameters and setups (e.g. source configuration, terrain, sampling distance from the site, different combinations of wind data) showed that in WindTrax (backward mode) the measurement speed of meteorological parameters (via three-dimensional ultrasonic anemometer) had the largest influence on the calculated emission estimates, while in LASAT (forward mode) the assumption of the source configuration greatly affected the flux estimates. The used concentration data (e.g. location of observations, measurement mode of background concentration) was critically important to the success of IDM. The CH 4 emission rates from the AD facility in flat terrain (plant 1) calculated with both Lagrangian models by IDM showed good agreement with the DIAL (Differential Absorption Light Detection And Ranging) method and methane release tests (deviation in the range of 10–20%) when using best fit configurations (e.g. volume source in LASAT, area source in WindTrax, optimal measurement fetch). In moderately complex terrain (plant 2), the retrieval rates of controlled CH 4 releases, and thus the certainty of flux estimates of both dispersion models tended to decrease without the use of a terrain model. • First comparison of emission results inferred with LASAT and WindTrax. • Concentration and meteorological data obtained by three independent measurement teams. • Evaluation of sensitivity of the modelling system to input parameters and setups. • Recommendations for measurement and modelling procedure. • Uncertainty of ±10–20% for both models in flat terrains using best fit configurations.

Real-time stabilization of the alkali-metal transverse axis orientation in nuclear spin comagnetometer by biaxial differential detection

Axis orientation stability has a great effect on the long-term drift performance of nuclear spin comagnetometers that utilize alkali atoms to detect the magnetic moment of nuclear spin ensembles. Previous studies have analyzed the sensitivity influence of the misalignment angle and demonstrated a post-processing calibration method in the transverse polarized comagnetometer, but there is no study on the traditional longitudinally polarized setup. We propose an innovative biaxial differential detection method to monitor the misalignment angle in the longitudinally polarized comagnetometer and then eliminate it on-line. By monitoring the amplitude difference of a reference magnetic field’s projections in a rotated measurement frame, an error signal with good linearity is obtained. Experiments showed that any misalignment angle within (−π/4, π/4) can be successfully compensated to near 0 within about 1.5 s, which is fast enough compared to the drift rate of a practical device. The new detection method is robust and insensitive to many factors, such as direct component drift and scale factor inequality, so the method can be widely used in similar devices that acquire high accurate alignment of the axis orientation, such as the spin exchange relaxation-free magnetometer.

A new Duffing detection method for underwater weak target signal

On the basis of the double coupled Duffing oscillator, a differential double coupled Duffing oscillator method, called the proposed method 1, is proposed. The large scale state is judged by the differential timing sequence diagram, and its detection result is more intuitive. To overcome the frequency limitation of differential double coupled Duffing oscillator in detecting unknown frequency periodic signal, according to the proposed method 1, based on the intermittent chaos phenomenon, the differential double coupled Duffing oscillator variable step size detection method, called the proposed method 2, is proposed. This method can be used to detect Gaussian noise background periodic signal and K-distributed noise background periodic signal. Compared with the double Duffing method and the double coupled Duffing method, its average signal-to-noise ratio (SNR) threshold is reduced by 4.94 dB and 1.68 dB respectively, and the detection result is more intuitive to judge through the differential timing sequence diagram. The accuracy and universality of the proposed method 2 are proved by the detection of three measured underwater weak target signals. Experiments show that it has some characteristics such as intuitive detection result, high sensitivity, low SNR threshold, few oscillators, low system complexity and so on.

Low-noise optical measurement of sound using midfringe locked interferometer with differential detection.

A midfringe locked interferometer with differential detection is proposed for non-contact optical sound measurement, and the equivalent noise level of approximately 0 dB SPL/Hz is achieved. The noise level of the proposed method is 30 dB lower than that of a very recent laser Doppler vibrometer and close to that of a quarter-inch measurement microphone. The midfringe locking stabilizes the optical interferometer against slow environmental fluctuations and enables detection of the acoustic signal directly from optical intensity. The differential detection method eliminates laser intensity noise, which is a dominant noise source in optical interferometers. The noise level of the constructed system was approximately 10 dB above the optical shot-noise (the classical detection limit attributed to the quantum nature of light) at frequencies higher than 2 kHz. Further noise reduction by several available methods could lead to optical measurements that are more sensitive than measurements by microphones. In addition, the constructed interferometer is used to reconstruct sound fields generated by a half-inch laboratory standard microphone used as a transmitter. The proposed method will be a powerful tool for measuring small-amplitude sound fields where it has been challenging to use existing methods.

Development of a monoclonal antibody against PRRSV glycoprotein 3 using an immuodominant peptide as immunogen

Glycoprotein 3 (GP3), a highly glycosylated membrane protein, is a protective antigen and minor structural protein of porcine reproductive and respiratory syndrome virus (PRRSV), and plays a crucial role in virus assembly and infection. In the present study, we synthesized 23 overlapping peptides span GP3 protein sequence and used pig anti-PRRSV serums to identify immunodominant peptides by indirect ELISA. Five immunodominant peptides GP3-P3, P4, P5, P6 and P7 were identified and GP3-P4 (P55LCPTRQAAAEILEPGKS72) was conjugated to carrier protein BSA. One mAb 1E5 against GP3 was generated from BALB/c mice immunized with the conjugates BSA-P4. The Characterization of mAb was identified by Western blot, Dot-ELISA, IPMA and IFA. We found that mAb 1E5 can specifically react with HP-PRRSV strains but not C-PRRSV or NADC30-like PRRSV strains tested in this study. Site-directed alanine substitution analysis revealed that 8 amino acid residues were involved in antibody binding, among them E65, L67 and P69 were critical residue recognized by mAb 1E5. Taken together, this study provided a novel strategy for generating specific mAbs against virus proteins by using immunodominant peptides as targets, and the mAb 1E5 may be useful for development of rapid differential detection method differentiating HP-PRRSV from C-PRRSV and NADC30-like PRRSV.

Differential ATAC-seq and ChIP-seq peak detection using ROTS.

Changes in cellular chromatin states fine-tune transcriptional output and ultimately lead to phenotypic changes. Here we propose a novel application of our reproducibility-optimized test statistics (ROTS) to detect differential chromatin states (ATAC-seq) or differential chromatin modification states (ChIP-seq) between conditions. We compare the performance of ROTS to existing and widely used methods for ATAC-seq and ChIP-seq data using both synthetic and real datasets. Our results show that ROTS outperformed other commonly used methods when analyzing ATAC-seq data. ROTS also displayed the most accurate detection of small differences when modeling with synthetic data. We observed that two-step methods that require the use of a separate peak caller often more accurately called enrichment borders, whereas one-step methods without a separate peak calling step were more versatile in calling sub-peaks. The top ranked differential regions detected by the methods had marked correlation with transcriptional differences of the closest genes. Overall, our study provides evidence that ROTS is a useful addition to the available differential peak detection methods to study chromatin and performs especially well when applied to study differential chromatin states in ATAC-seq data.

Detection method of nonlinear magnetized harmonic signal of medical magnetic nanoparticles

Medical magnetic nanoparticles are nano-medical materials with superparamagnetism, which can be collected in the tumor tissue through blood circulation, and magnetic particle imaging technology can be used to visualize the concentration of magnetic nanoparticles in the living body to achieve the purpose of tumor imaging. Based on the nonlinear magnetization characteristics of magnetic particles and the frequency characteristics of their magnetization, a differential detection method for the third harmonic of magnetic particle detection signals is proposed. It was modeled and analyzed, to study the nonlinear magnetization response characteristics of magnetic particles under alternating field, and the spectral characteristics of magnetic particle signals. At the same time, the relationship between each harmonic and the amount of medical magnetic nanoparticle samples was studied. On this basis, a signal detection experimental system was built to analyze the spectral characteristics and power spectral density of the detected signal, and to study the relationship between the signal and the excitation frequency. The signal detection experiment was carried out by the above method. The experimental results showed that under the alternating excitation field, the medical magnetic nanoparticles would generate a spike signal higher than the background sensing signal, and the magnetic particle signal existed in the odd harmonics of the detected signal spectrum. And the spectral energy was concentrated at the third harmonic, that is, the third harmonic magnetic particle signal detection that meets the medical detection requirement could be realized. In addition, the relationship between each harmonic and the particle sample volume had a positive growth relationship, and the detected medical magnetic nanoparticle sample volume could be determined according to the relationship. At the same time, the selection of the excitation frequency was limited by the sensitivity of the system, and the detection peak of the third harmonic of the detection signal was reached at the excitation frequency of 1 kHz. It provides theoretical and technical support for the detection of medical magnetic nanoparticle imaging signals in magnetic particle imaging research.

Demonstration of a Label-Free and Low-Cost Optical Cavity-Based Biosensor Using Streptavidin and C-Reactive Protein.

An optical cavity-based biosensor (OCB) has been developed for point-of-care (POC) applications. This label-free biosensor employs low-cost components and simple fabrication processes to lower the overall cost while achieving high sensitivity using a differential detection method. To experimentally demonstrate its limit of detection (LOD), we conducted biosensing experiments with streptavidin and C-reactive protein (CRP). The optical cavity structure was optimized further for better sensitivity and easier fluid control. We utilized the polymer swelling property to fine-tune the optical cavity width, which significantly improved the success rate to produce measurable samples. Four different concentrations of streptavidin were tested in triplicate, and the LOD of the OCB was determined to be 1.35 nM. The OCB also successfully detected three different concentrations of human CRP using biotinylated CRP antibody. The LOD for CRP detection was 377 pM. All measurements were done using a small sample volume of 15 µL within 30 min. By reducing the sensing area, improving the functionalization and passivation processes, and increasing the sample volume, the LOD of the OCB are estimated to be reduced further to the femto-molar range. Overall, the demonstrated capability of the OCB in the present work shows great potential to be used as a promising POC biosensor.

Liquid photoacoustic sensing with high sensitivity by temperature compensated differential detection method

In this letter, a temperature compensated differential (TCD) photoacoustic (PA) method is proposed to simultaneously suppress the side-effect of multiple interferences, significantly improving the accuracy and sensitivity of liquid PA detection. We firstly established a theoretical model to prove the validity of this method. Then a differential PA detection system was set up to detect glucose concentration, a typical weak absorbing substance in the near-infrared range. The experimental results demonstrate that a trace-level detection limit of () for glucose solution was obtained. The TCD-PA method provides a feasible way for on-line high-precision detection of liquid substances.

FreeHi-C spike-in simulations for benchmarking differential chromatin interaction detection.

High-throughput genome-wide chromatin conformation capture assay (Hi-C) is routinely used to profile long-range genomic interactions and three-dimensional organization of genomes. A key application of Hi-C is the comparative analysis of genomic interactions across different time points, cellular conditions, or multiple stimuli. While operating characteristics of methods for Hi-C data processing such as normalization, pairwise interaction and higher-order organization detection have been relatively well studied, properties of methods for differential chromatin interaction detection are less investigated. We have recently developed FreeHi-C to enable data-driven non-parametric simulations from Hi-C experiments. Here, we extend FreeHi-C with a user/data-driven spike-in module to facilitate comparisons of differential chromatin interaction detection methods where the ground truth differential chromatin interactions are known under a wide variety of settings. We use FreeHi-C to benchmark four differential chromatin interaction detection methods, namely HiCcompare, multiHiCcompare, diffHic, and Selfish, using three comparative analysis settings with different sequencing depths and spike-in proportions. This comparison reveals distinguished performances in terms of the standard metrics such as the false discovery rate control, detection power, significance order, precision-recall curve, and receiver operating characteristic curve as well as overall genomic properties of the types of differential chromatin interactions detectable by each method. Furthermore, it highlights the lack of power for all methods in small replication settings.

Quantitative characterization of physical structure on carbon fiber surface based on image technique

In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness.

Optimized Sampling Rate for Voltammetry-Based Electrochemical Sensing in Wearable and IoT Applications

The recent advancements in electrochemical measurements are guiding the development of new platforms for in situ point-of-care monitoring of human-metabolite, markers, and drugs. Despite this, the application of voltammetry-based sensing (VBS) techniques is still limited in wearable, portable, or Internet-of-Things (IoT) systems. In order to use VBS approaches to measure analytes in small and low-power electronic platforms for diagnostics, several improvements are required. For example, the definition of a method to achieve the right tradeoff between sample rate and sensing performance is still missing. To develop a method to define the best sampling rate, we present here an extensive analysis of experimental data to prove that it is feasible to detect drugs such as paracetamol by using staircase cyclic voltammetry or differential pulse voltammetry direct detection methods, with low sampling frequency. Our results prove that the proposed method helps the development of systems capable of discriminating the minimum pharmacology concentration of the metabolite under analysis with a massive reduction of the sampling frequency.

A Differential Detection Method Based on a Linear Weak Measurement System.

Self-reference detection is necessary and important to a biosensor. The linear weak measurement system based on total internal reflection has attracted widespread attention due to its high stability, label-free detection, and easy integration. In this paper, we propose a differential detection method based on the linear total internal reflection weak measurement system. We introduce the half-wave plate (HWP) to convert the H light and the V light to each other, thereby obtaining the difference in phase change of the optical path before and after the HWP. Experiments show that the system can not only achieve differential detection, but also has high stability. The linear differential weak measurement system proposed in this paper not only provides a new differential measurement method for real-time biosensors, but also enriches the types of weak measurement sensors.

Demonstration of a Low-Cost and Portable Optical Cavity-Based Sensor through Refractive Index Measurements.

An optical cavity-based sensor using a differential detection method has been proposed for point-of-care diagnostics. We developed a low-cost and portable optical cavity-based sensor system using a 3D printer and off-the-shelf optical components. In this paper, we demonstrate the sensing capability of the portable system through refractive index measurements. Fabricated optical cavity samples were tested using the portable system and compared to simulation results. A referencing technique and digital low pass filtering were applied to reduce the noise of the portable system. The measurement results match the simulation results well and show the improved linearity and sensitivity by employing the differential detection method. The limit of detection achieved was 1.73 × 10−5 Refractive Index Unit (RIU), which is comparable to other methods for refractive index sensing.

Research on Coal-Rock Fracture Image Edge Detection Based on Tikhonov Regularization and Fractional Order Differential Operator

Aiming at the conventional image edge detection algorithm, the first-order differential edge detection method is easy to lose the image details and the second-order differential edge detection method is more sensitive to noise. To deal with the problem, the Tikhonov regularization method is adopted to reconstruct the input coal-rock infrared images, so as to reduce the noise interference, and then, the reconstructed image is transformed by gray level. Finally, we consider the frequency characteristics and long memory properties of fractional differential, the classical first-order Sobel and second-order Laplacian edge detection algorithms are extended to fractional order pattern, and a new pattern of fractional order differential image edge detection is constructed to realize the coal-rock fracture edge features identification. The results show that, compared with integer order differential, the error rate and omission rate of fractional order differential algorithm are smaller, the quality factor is larger, and the execution time and memory footprint are smaller. From the point of view of location criteria and location accuracy, the fractional order differential algorithm is better than the integer order. In addition, the proposed method is compared with Canny algorithm, B-spline wavelet transform, and multidirection fuzzy morphological edge detection method, can detect more coal-rock fracture infrared image edge details, and is more robust to noise.

A high-throughput system for automated bottle mouth defects inspection

Bottle mouth defects inspection is very important for the production line of beverage and medicine. In this paper, an intelligent inspection system for bottle mouth defects is presented. The linear convection mechanical structure and electrical control system based on industrial personal computer (IPC), motion card and data I/O card are firstly illustrated in detail. Thereafter, a method using the high-speed camera is applied to obtain the bottle mouth image. To find the centre of bottle mouth, a novel multi-search-orientation algorithm is proposed, and then the differential detection method based on ring scanning tangent is used to identify the cracks of the bottle mouth. The experimental results show that the detection algorithm is effective and the system is reliable.

DFseq: Distribution-Free Method to Detect Differential Gene Expression for RNA-Sequencing Data.

Many current RNA-sequencing data analysis methods compare expressions one gene at a time, taking little consideration of the correlations among genes. In this study, we propose a method to convert such an one-dimensional comparison approach into a two-dimensional evaluation of the ratio of standard deviations (SD) of two constructed random variables. This method allows the identification of differentially expressed genes while controlling a preset significance level conditional on the read count mean-variance relationship. Meanwhile, correlations among genes are naturally accommodated due to the clustering of genes with similar distribution in the proposed σ-σ plot. The proposed distribution-free method is designated as DFseq, because it does not depend on a parametric distribution to fit read count. As a result, compared with parametric methods, DFseq can effectively handle genes with a bimodal-like distribution and/or genes with excessive 0 read counts, as well as genes with outlying observations. Besides, DFseq is an ideal platform for comparing performance of different differential gene expression detection methods.