Try with Simpler -- An Evaluation of Improved Principal Component Analysis in Log-based Anomaly Detection

The rapid growth of deep learning (DL) has spurred interest in enhancing log-based anomaly detection. This approach aims to extract meaning from log events (log message templates) and develop advanced DL models for anomaly detection. However, these DL methods face challenges like heavy reliance on training data, labels, and computational resources due to model complexity. In contrast, traditional machine learning and data mining techniques are less data-dependent and more efficient but less effective than DL. To make log-based anomaly detection more practical, the goal is to enhance traditional techniques to match DL's effectiveness. Previous research in a different domain (linking questions on Stack Overflow) suggests that optimized traditional techniques can rival state-of-the-art DL methods. Drawing inspiration from this concept, we conducted an empirical study. We optimized the unsupervised PCA (Principal Component Analysis), a traditional technique, by incorporating lightweight semantic-based log representation. This addresses the issue of unseen log events in training data, enhancing log representation. Our study compared seven log-based anomaly detection methods, including four DL-based, two traditional, and the optimized PCA technique, using public and industrial datasets. Results indicate that the optimized unsupervised PCA technique achieves similar effectiveness to advanced supervised/semi-supervised DL methods while being more stable with limited training data and resource-efficient. This demonstrates the adaptability and strength of traditional techniques through small yet impactful adaptations

Signal Timing Optimization Based on Fuzzy Compromise Programming for Isolated Signalized Intersection

In order to optimize the signal timing for isolated intersection, a new method based on fuzzy programming approach is proposed in this paper. Considering the whole operation efficiency of the intersection comprehensively, traffic capacity, vehicle cycle delay, cycle stops, and exhaust emission are chosen as optimization goals to establish a multiobjective function first. Then fuzzy compromise programming approach is employed to give different weight coefficients to various optimization objectives for different traffic flow ratios states. And then the multiobjective function is converted to a single objective function. By using genetic algorithm, the optimized signal cycle and effective green time can be obtained. Finally, the performance of the traditional method and new method proposed in this paper is compared and analyzed through VISSIM software. It can be concluded that the signal timing optimized in this paper can effectively reduce vehicle delays and stops, which can improve traffic capacity of the intersection as well

Compound-specific stable carbon isotope analysis of hexabromocyclododecane diastereoisomers using gas chromatography/isotope ratio mass spectrometry

Rationale Compound-specific stable isotope analysis (CSIA) is a powerful tool for the source apportionment and characterization of environmental transformation processes, especially for new emerging contaminants. In this study, we have developed an effective method for determination of the stable carbon isotope ratios of hexabromocyclododecane diastereoisomers. Methods Three diastereoisomers of hexabromocyclododecane (HBCD), alpha-, beta-, and gamma-HBCD, were separated on a preparative high-performance liquid chromatography (HPLC) system. Their carbon isotope ratios were determined using gas chromatography/isotope ratio mass spectrometry (GC/IRMS), and compared with data obtained by elemental analyzer/isotope ratio mass spectrometry (EA/IRMS). Results alpha-, beta-, and gamma-HBCD were well separated by the preparative HPLC system. Method validation results indicated excellent precision and reproducibility. For a series of injection volumes (0.5 to 3 mu L), the average carbon isotope ratios for alpha-HBCD, beta-HBCD, and gamma-HBCD were -26.42 parts per thousand, -26.88 parts per thousand, and -26.43 parts per thousand, respectively, and their deviations from those of the HBCD standard (-26.52 parts per thousand) were all lower than the analytical uncertainty of 0.5 parts per thousand. Relative standard deviations of intra-day and inter-day injections of HBCD were in the ranges 0.35-0.64% and 0.37-0.76%, respectively. Comparison with EA/IRMS further verified the accuracy of the HBCD stable carbon isotope ratio measured by GC/IRMS. Conclusions This work offers a novel approach to separate and concentrate the three major isomers of HBCD and to determine their stable carbon isotope ratios. This permits analysis of their carbon isotope ratios in environmental samples in order to elucidate the sources and abiotic or biological transformation processes of HBCD in the environment

Enantiomeric analysis of polycyclic musks AHTN and HHCB and HHCB-lactone in sewage sludge by gas chromatography/tandem mass spectrometry

Rationale Enantioselective analysis of chiral compounds is an interesting and challenging technique used to elucidate the degradation/transformation mechanisms of these compounds or understand their environmental processes. In this study, we have developed an effective separation and detection approach for the enantiomeric analysis of AHTN and HHCB, as well as a transformation product of HHCB (HHCB-lactone), in sludge samples. Methods The analytical method was developed using a cyclodextrin-based enantioselective gas chromatography column combined with tandem mass spectrometry (GC/MS/MS). The GC oven temperature gradients, the linear velocity of the helium carrier gas, as well as the MS/MS parameters, including quantitative and qualitative ion pairs, dwell times, and collision energies, were optimized to achieve good separation and high sensitivity for all target enantiomers. Results Baseline separations of all target enantiomers were observed. Limits of quantification (LOQs) for all enantiomers ranged from 0.010 to 0.045 mu g/L, and calibration linearity for all single enantiomers was higher than 0.99. The intra-day and inter-day precisions for all single enantiomers of AHTN, HHCB, and HHCB-lactone ranged from 0.8 to 3.8% and from 4.2 to 8.3%, respectively. Conclusions The developed method was fully validated through enantioselective analyses of AHTN, HHCB, and HHCB-lactone in sludge samples collected from 17 WWTPs. The enantiomeric fractions (EFs) of HHCB and HHCB-lactone in sludge samples distinctly deviated from 0.50, indicating a significant enantioselective transformation of HHCB with preferential degradation of the 4S enantiomers. Significant positive correlations were found between the EF values of cis-HHCB enantiomers and cis-HHCB-lactone enantiomers in the sludge samples, implying that further efforts are still needed to clarify the degradation/transformation mechanism from HHCB to HHCB-lactone

Removal of Methylene Blue from Aqueous Solution Using Agricultural Residue Walnut Shell: Equilibrium, Kinetic, and Thermodynamic Studies

Walnut shell (WS), as an economic and environmental-friendly adsorbent, was utilized to remove methylene blue (MB) from aqueous solutions. The effects of WS particle size, solution pH, adsorbent dosage and contact time, and concentration of NaCl on MB removal were systematically investigated. Under the optimized conditions (i.e., contact time ~ 2 h, pH ~ 6, particle size ~ 80 mesh, dye concentration 20 mg/L, and 1.25 g/L adsorbent), the removal percentages can achieve ~97.1%, indicating WS was a promising absorbent to remove MB. Other supplementary experiments, such as Fourier transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), and Brunauer-Emmett-Teller (BET) method, were also employed to understand the adsorption mechanisms. FTIR confirmed that the successful adsorption of MB on WS particles was through functional groups of WS. Using DLS method, the interactions between WS particles and dyes under various pH were investigated, which can be ascribed to the electrostatic forces. Kinetic data can be well fitted by the pseudo-second-order model, indicating a chemical adsorption. The adsorption isotherms were well described by both Langmuir and Freundlich models. Dubinin-Radushkevich model also showed that the adsorption process was a chemical adsorption. Thermodynamic data indicated that the adsorption was spontaneous, exothermic, and favorable at room temperature