Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Design, Analysis and Real-time Implementation of Networked Predictive Control Systems

这份报纸用预兆的控制策略涉及设计，分析和联网的控制系统的即时实现。联网的控制系统的特征的分析被详细说明，它证明一个联网的控制系统与常规控制系统不同。完成靠近环的联网的控制系统的需要的性能，联网的预兆的控制计划被介绍。设计，稳定性分析和联网的预兆的控制系统的即时实现被学习。它被联网的预兆的控制计划能补偿随机的网络通讯延期和数据退学学生的模拟和实际实验说明，完成需要的控制性能并且有好靠近环的稳定性。

Integrated Real-Time Big Data Stream Sentiment Analysis Service

Opinion (sentiment) analysis on big data streams from the constantly generated text streams on social media networks to hundreds of millions of online consumer reviews provides many organizations in every field with opportunities to discover valuable intelligence from the massive user generated text streams. However, the traditional content analysis frameworks are inefficient to handle the unprecedentedly big volume of unstructured text streams and the complexity of text analysis tasks for the real time opinion analysis on the big data streams. In this paper, we propose a parallel real time sentiment analysis system: Social Media Data Stream Sentiment Analysis Service (SMDSSAS) that performs multiple phases of sentiment analysis of social media text streams effectively in real time with two fully analytic opinion mining models to combat the scale of text data streams and the complexity of sentiment analysis processing on unstructured text streams. We propose two aspect based opinion mining models: Deterministic and Probabilistic sentiment models for a real time sentiment analysis on the user given topic related data streams. Experiments on the social media Twitter stream traffic captured during the pre-election weeks of the 2016 Presidential election for real-time analysis of public opinions toward two presidential candidates showed that the proposed system was able to predict correctly Donald Trump as the winner of the 2016 Presidential election. The cross validation results showed that the proposed sentiment models with the real-time streaming components in our proposed framework delivered effectively the analysis of the opinions on two presidential candidates with average 81% accuracy for the Deterministic model and 80% for the Probabilistic model, which are 1% - 22% improvements from the results of the existing literature.

Performance analysis model for real-time Ethernet-based computer numerical control system

In order to optimize the embedded system implementation for Ethernet-based computer numerical control (CNC) system,it is very necessary to establish the performance analysis model and further adopt the codesign method from the control,communication and computing perspectives.On the basis of analyzing real-time Ethernet,system architecture,time characteristic parameters of control-loop etc,a performance analysis model for real-time Ethernet-based CNC system was proposed,which is able to include the timing effects caused by the implementation platform in the simulation.The key for establishing the model is accomplished by designing the error analysis module and the controller nodes.Under the restraint of CPU resource and communication bandwidth,the experiment with a case study was conducted,and the results show that if the deadline miss ratio of data packets is 0.2%,then the percentage error is 1.105%.The proposed model can be used at several stages of CNC system development.

Diagnostic accuracy of real-time tissue elastography for breast cancer:a meta-analysis

Objective The present study aimed to determine the accuracy of real-time tissue elastography(RTE) for the diagnosis of breast cancer. Methods The search was conducted in the Pub Med, Web of Science, Cochrane Library, and China Biology Medicine databases from inception through December 31, 2014, without language restrictions. The meta-analysis was conducted using STATA version 12.0 and Meta-Disc version 1.4. We calculated the summary statistics for sensitivity(Sen), specificity(Spe), positive and negative likelihood ratio(LR+/LR–), diagnostic odds ratio(DOR), and summary receiver operating characteristic(SROC) curve. Results Ten studies that met all inclusion criteria were included in the meta-analysis. A total of 608 malignant breast lesions and 1292 benign breast tumors were assessed. All breast lesions were histologically confirmed after RTE. The pooled Sen was 0.83(95% CI = 0.79–0.86); the pooled Spe was 0.86(95% CI = 0.84–0.88). The pooled LR+ was 9.87(95% CI = 2.66–36.71); the pooled LR– was 0.20(95% CI = 0.17–0.23). The pooled DOR of RTE for the diagnosis of breast cancer was 62.21(95% CI = 33.88–114.24). The area under the SROC curve was 0.9334(standard error = 0.00125). We found no evidence of publication bias(t = –0.57, P = 0.582). Conclusion RTE may have high diagnostic accuracy for the differential diagnosis of benign and malignant breast tumors. RTE may be a good tool for breast cancer diagnosis.

Real-time lane departure warning system based on principal component analysis of grayscale distribution and risk evaluation model

A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.

A Mathematical Model of Real-Time Simulation and the Convergence Analysis on Real-Time Runge-Kutta Algorithms

In this paper, a mathematical model of real-time simulation is given, and the problem of convergence on real-time Runge-Kutta algorithms is analysed. At last a theorem on the relation between the order of compensation and the convergent order of real-time algorithm is proved.

Real-Time Computer Analytical Application in Pressure Transient Analysis of Petroleum Reservoirs

Today with certainty, the petroleum industry is fostering sanguinely the fields’ development programs for the optimization of reservoir characterization through worth-full appliances of computer analysis techniques. The time element is of prime importance for optimistic petroleum development projects. Therefore, the frontline of “Real-time Analysis” is added into the applications of computer solving techniques for achieving and sketching up the real-time cost effectiveness in analyzing field development programs. It focuses on the phases of real-time well test data acquisition system, real-time secure access to the well test data either on field or in office and real-time data interpretation unit. This interface will yield the productive results for the field of reservoir’s pressure transient analysis and wells’ systems analysis by following the up-to-date preferred, accurate and effective well test analytical principles with modern real-time computer applications and techniques. It also lays emphasis for the comfort and reliability of data in creating best interpersonal working modes within a reputable and esteemed petroleum development organization.

Electricity Price Influence Factors Analysis Using Stochastic Matrix for Real-Time Electricity Price Forecasting

Real-time electricity price( RTEP) influence factor extraction is essential to forecasting accurate power system electricity prices. At present,new electricity price forecasting models have been studied to improve predictive accuracy,ignoring the extraction and analysis of RTEP influence factors. In this study,a correlation analysis method is proposed based on stochastic matrix theory.Firstly, an augmented matrix is formulated, including RTEP influence factor data and RTEP state data. Secondly, data correlation analysis results are obtained given the statistical characteristics of source data based on stochastic matrix theory.Mean spectral radius( MSR) is used as the measure of correlativity.Finally,the proposed method is evaluated in New England electricity markets and compared with the BP neural network forecasting method. Experimental results show that the extracted index system comprehensively generalizes RTEP influence factors,which play a significant role in improving RTEP forecasting accuracy.

Real-Time Grouting Monitoring and Visualization Analysis System for Dam Foundation Curtain Grouting

A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model of the system is established. The real-time collection and transmission technology of the grouting data provides a data foundation for the system. The real-time grouting monitoring and dynamic alarming method helps the system control the grouting quality during the grouting process, thus, the abnormalities of grouting, such as jacking and hydraulic uplift, can be effectively controlled. In addition, the 3D grouting visualization analysis technology is proposed to establish the grouting information model(GIM). The GIM provides a platform to visualize and analyze the grouting process and results. The system has been applied to a hydraulic project of China as a case study, and the application results indicate that the real-time grouting monitoring and 3D visualization analysis for the grouting process can help engineers control the grouting quality more efficiently.

A novel stochastic modeling framework for coal production and logistics through options pricing analysis

We propose a novel stochastic modeling framework for coal production and logistics using option pricing theory.The problem of valuing the inherent real optionality a coal producer has when mining and processing thermal coal is modelled as pricing spread options of three assets under the stochastic volatility model.We derive a three-dimensional Fast Fourier Transform(“FFT”)lower bound approximation to value the inherent real optionality and for robustness check,we compare the semi-analytical pricing accuracy with the Monte Carlo simulation.Model parameters are estimated from the historical monthly data,and stochastic volatility parameters are obtained by matching the Kurtosis of the low-ash diff data to the Kurtosis of the stochastic volatility process which is assumed to follow Cox–Ingersoll–Ross(“CIR”)model.

Intravitreal triamcinolone acetonide： a ＂real world＂ analysis of visual acuity, pressure and outcomes

Dear Sir,Triamcinolone acetonide（TA）is worldwide available therapeutic agent that is commonly used throughout medicine.TA remains a safe and important ophthalmic therapeutic agent even after the advent of angiogenesis inhibitors[1-2].

Research on the Effect of Artificial Intelligence Real Estate Forecasting Using Multiple Regression Analysis and Artificial Neural Network: A Case Study of Ghana

To transition from conventional to intelligent real estate, the real estate industry must enhance its embrace of disruptive technology. Even though the real estate auction market has grown in importance in the financial, economic, and investment sectors, few artificial intelligence-based research has tried to predict the auction values of real estate in the past. According to the objectives of this research, artificial intelligence and statistical methods will be used to create forecasting models for real estate auction prices. A multiple regression model and an artificial neural network are used in conjunction with one another to build the forecasting models. For the empirical study, the study utilizes data from Ghana apartment auctions from 2016 to 2020 to anticipate auction prices and evaluate the forecasting accuracy of the various models available at the time. Compared to the conventional Multiple Regression Analysis, using artificial intelligence systems for real estate appraisal is becoming a more viable option (MRA). The Artificial Neural network model exhibits the most outstanding performance, and efficient zonal segmentation based on the auction evaluation price enhances the model’s prediction accuracy even more. There is a statistically significant difference between the two models when it comes to forecasting the values of real estate auctions.

Analysis of the Real-world Efficacy of Lianhua Qingwen Capsule(莲花清瘟胶囊)in the Treatment of Upper Respiratory Tract Infection

Objective:To explore the efficacy of Lianhua Qingwen Capsule(莲花清瘟胶囊)on upper respiratory tract infection,to understand the impact of Lianhua Qingwen Capsule(莲花清瘟胶囊)on the treatment outcome of upper respiratory tract infection,and provide reference for rational clinical drug use.Methods:The HIS database based on 18 large third-grade class-A hospitals was selected to match 1:1 for upper respiratory tract infection patients using and without Lianhua Qingwen Capsule(莲花清瘟胶囊)according to certain standards.The recombination of treatment outcome as"recovery"and"improvement"in the database was defined as effective treatment,"ineffectiveness","death"and"other"as ineffectivetreatment populations,and the effectiveness of treatment outcomes in the remerged 2 groups was compared by propensity score method.Results:After matching,454 cases were in both the patients treated by(experimental group)and without(control group)Lianhua Qingwen Capsule(莲花清瘟胶囊).Analysis was performed by three Logistic regression methods,all showing regression coefficients greater than 0 and statistically significant differences(P<0.05).Conclusion:Patients with upper respiratory tract infection treated by Lianhua Qingwen Capsule(莲花清瘟胶囊)are more effective than that without Lianhua Qingwen Capsule(莲花清瘟胶囊),it can improve the clinical efficacy of patients with upper respiratory tract infection。

A Multimodal Discourse Analysis of Meaning Construction of Real Estate Posters

Posters have been one of the main research subjects in the Systemic-Functional Linguistics. Nowadays, posters are full of various types of semiotic modes with their wide applications of multimodality. This phenomenon is reflected in real estate posters as well, therefore, this thesis hopes to explore their essence of using multimodality and discussing meaning construction of the real estate posters.

The comparison and analysis of real estate operation in China

This paper raises the comparison method of operational stages of the real estate market. In order to select similar operational stages, we established an analysis model by applying fuzzy grade-of-membership clustering in this paper. Firstly, we select the materials information of the real estate market in America, Germany and Japan. Secondly, the real estate markets of America, Germany and Japan are divided into several different stages. Lastly, we apply the method of fuzzy grade-of-membership clustering to select comparable stages. The result of analysis indicates that the real estate market of Japan and Germany (1960-1980) are similar to the market in China.

Analysis of Solvency of A-Share Listed Companies in China’s Real Estate Industry

The real estate industry is a capital-intensive industry and capital has become a particular concern for real estate enterprises.For a long time,China’s real estate enterprises rely on high-leverage development and carry out high-debt and high-risk operations.The solvency of real estate enterprises has been the focus of stakeholders’attention.In August 2020,China’s regulatory authorities introduced new financing regulations for real estate enterprises.They set up“three red lines,”which brought real estate enterprises’solvency into focus once again.This article takes A-share listed companies in China’s real estate industry as an example,analyzes and evaluates its debt solvency,and gives suggestions based on new policies and regulations,hoping to provide specific references to the enterpriser’s manager and external decision-makers.

基因Ⅰ型草鱼呼肠孤病毒TaqMan Real-Time PCR检测方法的建立及应用

为了建立和应用可检测基因I型草鱼呼肠孤病毒（GCRV）的荧光定量检测方法，实验根据基因I型GCRV的s6保守序列，分别设计扩增目的条带661bp普通引物（P1、P2）、扩增目的条带159bp荧光定量引物（F1、F2）和一条探针；同时构建含有目的片段的PVAX1-S6作为标准质粒，10倍梯度稀释构建质粒拷贝数与Ct值的标准曲线（Y=-3．389X＋38．076）。结果表明，此方法在3．9×10^7～3．9×10^1拷贝／uL之间相关性较好，R2为0．992，最小检测量为4拷贝／uL；且与基因Ⅱ型、Ⅲ型GCRV以及其他病原核酸无交叉反应。运用该方法检测16份草鱼出血病疑似样品，阳性结果为4份；而普通PCR检测仅2份显示阳性。本研究建立了针对基因I型GCRV的荧光定量检测方法，具有高效、特异、灵敏、可重复性强的优点，适合于目前基因I型GCRV的临床快速检测和病毒定量分析。