The Compound Prediction Analysis of Information Network Security Situation based on Support Vector Combined with BP Neural Network Learning Algorithm

In order to solve the problem of low security of data in network transmission and inaccurate prediction of future security situation, an improved neural network learning algorithm is proposed in this paper. The algorithm makes up for the shortcomings of the standard neural network learning algorithm, eliminates the redundant data by vector support, and realizes the effective clustering of information data. In addition, the improved neural network learning algorithm uses the order of data to optimize the "end" data in the standard neural network learning algorithm, so as to improve the accuracy and computational efficiency of network security situation prediction.MATLAB simulation results show that the data processing capacity of support vector combined BP neural network is consistent with the actual security situation data requirements, the consistency can reach 98%. the consistency of the security situation results can reach 99%, the composite prediction time of the whole security situation is less than 25s, the line segment slope change can reach 2.3% ,and the slope change range can reach 1.2%,, which is better than BP neural network algorithm.

The Appearance of a “Fresh” Surface on 596 Scheila as a Consequence of the 2010 Impact Event

Dust emission was detected on main-belt asteroid 596 Scheila in 2010 December and was attributed to the collision of a few-tens-of-meters projectile on the surface of the asteroid. In such an impact, the ejected material from the collided body is expected to mainly come from its fresh, unweathered subsurface. Therefore, it is expected that the surface of 596 was partially or entirely refreshed during the 2010 impact. By combining spectra of 596 from the literature and our own observations, we show that the 2010 impact event resulted in a significant slope change in the near-infrared (0.8–2.5 μm) spectrum of the asteroid, from moderately red (T type) before the impact to red (D type) after the impact. This provides evidence that red carbonaceous asteroids become less red with time due to space weathering, in agreement with predictions derived from laboratory experiments on the primitive Tagish Lake meteorite, which is spectrally similar to 596. This discovery provides the very first telescopic confirmation of the expected weathering trend of asteroids spectrally analog to Tagish Lake and/or anhydrous chondritic porous interplanetary dust particles. Our results also suggest that the population of implanted objects from the outer solar system is much larger than previously estimated in the main belt, but many of these objects are hidden below their space-weathered surfaces.

A Novel Adaptive Fuzzy MPPT Algorithm under Changing Atmospheric Conditions

The paper aims at the incompatibility between the speed and stability of the traditional MPPT algorithm and the imprecise search of the fuzzy control algorithm. An improved photovoltaic adaptive fuzzy control MPPT algorithm is proposed in this thesis. The solar irradiance changes dramatically and hence four kinds of fuzzy control algorithms with different input are modeled and simulated. The results indicate that the proposed fuzzy control algorithm using slope and slope change rate of P-U curve as input is the best. On this basis, dP/dU and duty cycle D(n-1) at n-1 moment are used as input to improve the tracking speed and optimal range. At the same time using shrinkage factor 1/I*|dP/dU| real-time adjustment of D(n-1) further shortens the optimal time of the algorithm. The algorithm is simulated and applied in a block. Simulation results show that the proposed algorithm is superior to the fuzzy control algorithm in steady-state oscillation rate, tracking speed and efficiency, and the algorithm is simple and easy to implement.

Abstract 11233: A Trigger and Response System for Preventing Cardiac Arrest in the Intensive Care Unit

Background: Although patients in the ICU are closely monitored, some ICU cardiac arrest events may be preventable. In this study we sought to reduce the rate of ICU cardiac arrests. Methods: This was a prospective study of a novel clinical trigger and response tool deployed in the ICUs of a single, tertiary academic medical center. An interrupted time series approach was used to assess the impact of the tool on ICU cardiac arrests. Results: Forty-three patients experienced an ICU cardiac arrest in the pre-intervention epoch (6.79 arrests per 1000 discharges) and 59 patients experienced an ICU cardiac arrest in the intervention epoch (7.91 arrests per 1000 discharges). In the intervention epoch, the clinical trigger and response tool was activated 106 times over a 1-year period, most commonly due to unexpected new or worsening hypotension. There was no step change in arrest-rate (2.24 arrests/1000 patients, 95%CI -1.82, 6.28, p=0.28) or slope change (-0.02 slope of arrest rate, 95%CI -0.14, 0.11, p=0.79) comparing the pre-intervention and intervention time epochs (see Figure). Cardiac arrests occurring in the pre-intervention epoch were more likely to be deemed ‘potentially preventable’ than those in the intervention epoch (25.6% prior to the intervention vs. 12.3% during the intervention, OR 0.58, 95%CI 0.20, 0.88, p<0.01). Conclusions: A trigger-and-response tool did not reduce the incidence of ICU cardiac arrest. Arrests occurring after introduction of the tool were less likely to be rated as ‘potentially preventable.’

Effectiveness of legislative actions against tobacco smoking regarding the reduction of in-hospital morbidity of angina pectoris and myocardial infarction in Russia as a whole and 10 Russian constituent entities

Russian anti-tobacco policy is aimed at reducing long-term morbidity and mortality from smoking-related diseases.Aim. To assess the associations of tobacco control (TC) legislative measures with hospitalization rate for myocardial infarction (MI) and angina in Russia as a whole and in 10 Russian constituent entities, as well as to compare the effectiveness of anti-smoking measures in regions.Material and methods. We analyzed data on hospitalizations of patients with angina (I20) and acute (I21) and subsequent (I22) MI, as well as chronic rheumatic heart diseases (I05-I09), for 2005-2019 in Russia as a whole and in 10 Russian constituent entities. We analyzed hospital admission rates for angina and MI to compare the periods before and after introduction of Federal TC law in 2013, adjusting for possible confounders and long-term trends. We used interrupted time-series design and Poisson regression model with calculation of rate ratio (RR) and 95% CI. Regions were compared by means of original TC law implementation scale (TCIS) developed based on the results of Russian TC policy evaluation survey in 10 Russian regions (n=11625). We analyzed the relationship between the TC law measures implementation scores and RR of hospital admissions reductions for angina and MI after the TC law by means of Spearman’s rank correlation (coefficient with 95% CI) and linear regression models. Statistical package STATA 11.2 was used.Results. The actual trend of hospital admission rates for angina after TC law introduction demonstrates the greatest slope change from the predicted trend (without the law) (p=0,004); less, but still significant slope change for MI (p=0,049), and no slope change for chronic rheumatic heart disease (p=0,332). Results showed a 16,6% decrease in hospital admission rates for angina (RR, 0,83; 95% CI, 074-0,93) and 3,5% — for MI (RR, 0,96; 95% CI, 0,96-0,97) after the TC law introduction in RF and effects of various magnitude in the regions. Regions with higher TCIS scores, i.e. better enforcement of full TC package had greater reduction in hospital admission rates for angina (rsp=-0,627; 95% CI, -1,05−-0,199; p=0,004); with better enforcement of smoke-free policies — grater reduction in hospitalization rates for MI (rsp= -0,793 95%CI, -1,08−-0,506, p<0,001). Reduction of hospital admission rates for angina and MI correlated with the higher scores for help to quit tobacco use (rsp=-0,555; 95% CI, -1,098−-0,01, p=0,045), (rsp= -0,736; 95% CI, -1,12−-0,357, p=0,027). Also, hospital admission rates for angina and MI were associated with the changes in smoking cessation prevalence in 2013-2018 in the regions (β=-0,345; 95% CI, -0,67−-0,02 p=0,041) and smoking prevalence in 2019 (β=2,964; 95% CI, 1,28-5,92, p=0,049), respectively.Conclusion. TC legislation can lead not only to immediate reductions in hospital admission rates for angina and MI, but also to longer-term results. These effects may be due not only to the introduction of TC law, as such, but also to the enforcement of the law, as well as the direct results of TC measures — the decrease in smoking prevalence in the population.

Driving Assistance System with Lane Change Detection

In this study, a simple technology for a self-driving system called “driver assistance system” is developed based on embedded image identification. The system consists of a camera, a Raspberry Pi board, and OpenCV. The camera is used to capture lane images, and the image noise is overcome through color space conversion, grayscale, Otsu thresholding, binarization, erosion, and dilation. Subsequently, two horizontal lines parallel to the X-axis with a fixed range and interval are used to detect left and right lane lines. The intersection points between the left and right lane lines and the two horizontal lines can be obtained, and can be used to calculate the slopes of the left and right lanes. Finally, the slope change of the left and right lanes and the offset of the lane intersection are determined to detect the deviation. When the angle of lanes changes drastically, the driver receives a deviation warning. The results of this study suggest that the proposed algorithm is 1.96 times faster than the conventional algorithm.

Underground space optimization of smart city based on information processing technology

This study explores the underground space optimization method of smart city based on information processing technology to save space optimization operation time. Taking coordinate of intersection point, radius of intersection point, mileage of vertical slope change point and elevation of slope change point as design variables, taking total cost of underground space construction of smart city as objective function and taking plane, vertical section, horizontal and vertical combination and environmental impact as constraint conditions, a multi-objective optimization mathematical model of underground space of smart city was constructed. Parete genetic algorithm in information processing technology was used to solve the multi-objective optimization mathematical model of the underground space of smart city, realize the automatic search for the optimal scheme of the underground space of smart city, and complete the intelligent optimization process of the underground space construction scheme of smart city. The results show that the method obtained from this study can effectively optimize the underground space of smart city and obtain the optimal subway laying line, save space and optimize operation time and improve the convergence of the method.

A Hierarchical Clustering Method to Repair Gaps in Point Clouds of Powerline Corridor for Powerline Extraction

Powerline detection is becoming a significant issue for powerline monitoring and maintenance, which further ensures transmission security. As an efficient method, laser scanning has attracted considerable attention in powerline detection for its high precision and robustness during the night period. However, due to occlusion and varying point density, gaps will appear in scans and greatly influence powerline detection by over–clustering, insufficient extraction, or misclassification in existing methods. Moreover, this situation will be worse in terrestrial laser scanning (TLS), because TLS suffers more from gaps due to its unique ground–based scanning mode compared to other laser scanning systems. Thereby, this paper explores a robust method to repair gaps for extracting powerlines from TLS data. Firstly, a hierarchical clustering method is used to extract the powerlines. During the clustering, gaps are repaired based on neighborhood relations of powerline candidates, and repaired gaps can create continuous neighborhood relations that ensure the execution of the clustering method in return. Test results show that the hierarchical clustering method is robust in powerline extraction with repaired gaps. Secondly, reconstruction is performed for further detection. Pylon–powerline connections are found by the slope change method, and powerlines with multi–span are successfully fitted using these connections. Experiment shows that it is feasible to find connections for multi–span reconstruction.