A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the Internet.Regrettably,this development has expanded the potential targets that hackers might exploit.Without adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or alteration.The identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious attacks.This research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)units.The proposed model can identify various types of cyberattacks,including conventional and distinctive forms.Recurrent networks,a specific kind of feedforward neural networks,possess an intrinsic memory component.Recurrent Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended periods.Metrics such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual cyberattacks.RNNs are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection Model.This model utilises Recurrent Neural Networks,specifically exploiting LSTM techniques.The proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

大数据背景下两阶段Leverage重要性抽样方法研究

大数据背景下,需要对传统的抽样调查技术进行改进,以应对数据结构变化。以杠杆得分为入样概率的Leverage重要性抽样能够增加高杠杆值样本点被抽中的概率,但也增加了异常值选入抽样子集的风险,使得抽样估计偏离真实值。为降低大数据异常值影响,提高大数据抽样子集估计的稳健性,本文提出基于阈值自选择的两阶段Leverage重要性抽样方法。该方法第一阶段以样本距离的有序聚类识别稳健子集,使得用于二阶段抽样的样本更具代表性,第二阶段则是在稳健子集的基础上获得稳健抽样估计。模拟分析结果表明,本文所提方法能够提升线性回归系数估计的精度,在漂移型、波动型和混合型离群值中均适用。实证分析中本文所提方法在三个案例数据中拥有较小的预测值均方误差,有效降低了异常值的影响。

The Influence of Company Performance on Company Value(K-Pop Entertainment Company Registered on KOSPI.KRX South Korea 2018-2022)

A well-managed company is a company that maximizes the value of its company,which is aimed at achieving maximum profits for shareholders.This research aims to determine and analyze the influence of company size,profitability,and financial leverage on the value of companies listed on the South Korean Stock Exchange KOSPI 2018-2022.The population consists of 8 South Korean K-Pop entertainment companies registered on KOSPI 2018-2022.The sampling technique used was purposive sampling with a total sample of 8 companies and a 5-year observation period.So that 40 data were processed.The analysis technique is multiple linear regression.The results obtained show that partially company size has no significant effect on company value,profitability has a significant positive effect on company value,and financial leverage has a significant negative effect on company value.Meanwhile,simultaneously company size,profitability,and financial leverage influence company value.

leverage钛板在颈椎管单开门椎管扩大成形术中的应用

目的探讨leverage钛板固定行单开门椎管扩大成形术对多节段脊髓型颈椎病(cervical spondylotic myelopathy,CSM)患者颈椎曲度及轴性症状的影响。方法自2014-10-2016-10行单开门椎管扩大成形术治疗90例CSM患者,随机均分为观察组与对照组各45例,观察组术中行leverage钛板固定椎板,对照组采用丝线悬吊固定椎板。比较两组患者的相关疗效指标。结果观察组手术耗时显著低于对照组(P<0.05),术中出血、住院时间、引流量差异无统计学意义(P>0.05);两组术后疼痛VAS评分均显著降低,术后6、12、24个月观察组显著低于对照组(P<0.05),两组JOA评分差异无统计学意义(P>0.05);术后观察组颈椎曲度显著高于对照组,轴性症状发生率显著低于对照组(P<0.05)。结论 leverage钛板固定行单开门椎管扩大成形术治疗CSM,操作简便,术后远期疼痛更轻,有利于维持颈椎曲度。

基于Gibbs抽样的随机波动模型族的贝叶斯研究

文章运用Gibbs抽样的MCMC方法对上证综指建立SV-N、SV-MN、LeverageSV三类随机波动模型,并利用DIC准则进行优劣比较分析。实证结果表明,具有杠杆效应的随机波动模型,即LeverageSV模型较其他两类模型能更好地描述上海股市的波动性。

PageRank技术在智能系统中的应用

知识获取是智能系统发展的关键技术。本文分析了PageRank技术特点,采用PageRank技术解决智能系统中知识获取的效率问题,把改进了的PageRank技术应用于智能系统中,并构建一个简易的问答系统来验证PageRank技术的作用。

Analyses on the Microeconomic Leverage in IPOs＇ Trademark Disposition with Their Parent Companies

By applying the theory of the relationship between microeconomic leverages and corporate risks, this paper discusses methods that the IPOs should choose to dispose the trademark with their parent companies so as to go public with a high issue price. By analyzing their microeconomic leverage effects, this paper points out that each method has its specific effect on risks and the IPOs should choose the method according to its risk factors, existing assets and financial structure to gain risk income and decrease risk losses.

大规模数据下基于充分降维的Leverage重要性抽样方法

随着信息技术的飞速发展,大规模数据在短时间内搜集并储存下来,为分析决策提供了巨大的信息量,也给统计建模带来了一定难度。对于样本容量大、变量个数少的数据,Leverage重要性抽样是一个简便可行的方法。本文发现,该方法中度量样本重要性的Leverage分数与因变量无关,而且在维度较大的情形下对样本没有区分程度,使得估计结果较差。为了同时考虑因变量和维度的影响,本文提出了基于充分降维的Leverage重要性抽样方法。该方法以不损失信息为前提,在充分降维的空间内重新计算Leverage分数,使得抽样更具有代表性。模拟数据分析显示,在样本容量较大的复杂数据中,相比于原始的Leverage重要性抽样方法,本文提出的方法可以降低估计的均方误差。三个实际数据也证实了该方法的可行性和有效性。

Development of a least squares support vector machine model for prediction of natural gas hydrate formation temperature

Hydrates always are considered as a threat to petroleum industry due to the operational problems it can cause.These problems could result in reducing production performance or even production stoppage for a long time.In this paper, we were intended to develop a LSSVM algorithm for prognosticating hydrate formation temperature(HFT) in a wide range of natural gas mixtures. A total number of 279 experimental data points were extracted from open literature to develop the LSSVM. The input parameters were chosen based on the hydrate structure that each gas species form. The modeling resulted in a robust algorithm with the squared correlation coefficients(R^2) of 0.9918. Aside from the excellent statistical parameters of the model, comparing proposed LSSVM with some of conventional correlations showed its supremacy, particularly in the case of sour gases with high H_2S concentrations, where the model surpasses all correlations and existing thermodynamic models. For detection of the probable doubtful experimental data, and applicability of the model, the Leverage statistical approach was performed on the data sets. This algorithm showed that the proposed LSSVM model is statistically valid for HFT prediction and almost all the data points are in the applicability domain of the model.

Deleveraging:Data, Risks and Countermeasures

Based on the latest macro financial data, this paper estimates China＇ s overall leverage ratio and sector-specific leverage ratios for households, non-financial enterprises, government and financial institutions. It is noted with particular emphasis that the tendency of non-financial enterprises to increase leverage has further intensified instead of abated, which warrants our great attention. Considering that increasing leverage of government sector represents a basic international trend since the eruption of global financial crisis, we simulate the paths of dynamic evolution of China＇s debt-to-GDP ratio on the basis of different scenarios of the difference between real economic growth rate and real interest rate, together with the NPL ratio of banks. Result indicates that in the coming two decades, the leverage ratio of China＇s government sector will continue to rise and will not converge. Hiking leverage ratio, growing debt burden and rising non-performing assets present major financial risks facing China for a certain period of time in the future. Under the premise of supply-side structural reforms and in tandem with the efforts of the real economy to reduce overcapacity, inventory and eliminate zombie firms, we suggest that China focus on disposing of non-performing assets and steadily deleverage through the implementation of integrated strategies to prevent debt problems from triggering systemic financial crisis.

Volatility forecasting in Chinese nonferrous metals futures market

This paper seeks to model and forecast the Chinese nonferrous metals futures market volatility and allows new insights into the time-varying volatility of realized volatility and leverage effects using high-frequency data.The LHAR-CJ model is extended and the empirical research on copper and aluminum futures in Shanghai Futures Exchange suggests the dynamic dependencies and time-varying volatility of realized volatility,which are captured by long memory HAR-GARCH model.Besides,the findings also show the significant weekly leverage effects in Chinese nonferrous metals futures market volatility.Finally,in-sample and out-of-sample forecasts are investigated,and the results show that the LHAR-CJ-G model,considering time-varyingvolatility of realized volatility and leverage effects,effectively improves the explanatory power as well as out-of sample predictive performance.

Debt choice, growth opportunities and corporate investment: evidence from China

The study aims to investigate how relying on short-term debt may help Chinese listed firms to make efficient investment decisions and reduce overinvestment problem for low-growth firms.The study uses a large set of panel data of nonfinancial Chinese listed firms over the period 2007–2017 and,using the robust twostage generalized method of moments,which is robust to unobserved heterogeneity of individual firms and addresses endogeneity issues.Findings show a positive relationship between growth and investment;this association is enhanced by leverage,especially for high-growth firms.This supports the view that short-term debt helps Chinese firms to make optimal use of leverage and therefore make better investment decisions.Furthermore,the results reveal that leverage plays a disciplining and monitoring role to reduce overinvestment incentive for low-growth firms.Overall,the study suggests that shareholders should consider short-term debt to mitigate the debt overhang problem and restrict the opportunistic behavior of managers,which can lead to efficient investment decisions.It also provides foreign investors insights about capital structure in China,and how it can help them make better investment decisions.

The Role of R&D Leverage as a Dynamic Capability in Performance Creation:Evidence from SMEs in Taiwan

This study addresses the role of R&D leverage in SMEs’performance creation.The authors do so by considering SMEs’high resource dependence due to isomorphism.We propose that R&D leverage,with a presence of dynamic capabilities,plays a moderating role in the relation between resource investments and performance.This study,which focused on Taiwan’s SMEs,conducts a questionnaire survey using the hierarchical sampling technique,across various industries and geographic areas in Taiwan.The empirical findings reveal that R&D leverage as an essential leveler in resource management enhances resource advantages.

Determinants of Capital Structure in the Nigerian Listed Insurance Firms

The paper investigates the determinants of capital structure in Nigerian listed insurance firms using data obtained from annual report of the sampled firms for the period of 2001-2010. It used five explanatory variables to measure their effects on debt ratio. Multiple regression is employed as a tool of analysis. The result reveals that all the explanatory variables have statistically and significantly influenced the explained variable. The results approve the prediction of pecking order theory in the case of profitability and trade-off theory in case of tangibility variables. The growth variable supports the agency theory hypothesis whereas size variable confirms to the asymmetry of information theory. It is therefore recommended that the management of listed insurance firms in Nigeria should always consider their positions using these capital structure determinants as important inputs before embarking on debt financing decision.

Factors Affecting Financial Performance of Tourism Destination Firms Listed on Stock Exchanges in China

Purpose:the aim of this research is to test the effect of financial ratio on the financial performance of tourism destination firms listed on stock exchange in China.The research selected ratios:current ratio(CR)as a dimension of liquidity,total asset turnover ratio(TATR)as a dimension of asset utilization,debt ratio(DE)as a dimension of leverage,natural logarithm of total asset(LNTA)as a dimension of firm size,GDP growth rate as a dimension of economic prosperity,and effective tax rate as a dimension of effective tax.This research will use return on asset(ROA),return on sales(ROS),return on equity(ROE)and sales growth(SG)to determine the financial performance.Since stock exchange founded in China,tourism destination firm developed very fast.However tourism destination listed firms have weakness financial performance.Design/methodology/approach:the research data collected from quarterly financial report,from 2012 Q1 to 2018 Q4.The secondary data has been analyzed by multiple regression.Finding:the result indicate that CR,TATR,GDP growth rate have positive impact on financial performance.While DE has negative impact on financial performance.And LNTA has a mix result with financial performance.Originality/value:This study led to the effect of financial ratios on tourism's financial performance since past researches with this aim were difficult to identify and certain references were not specifically linked to the topic.

中央空调系统运行的数据分析与优化策略研究

文章选取热带地区某城市的一套中央空调系统数据,通过对中央空调系统各指标之间的关系进行分析,借助SAS、SPSS和MATLAB软件,采用概率抽样的方法,构建基于加权偏最小二乘法的中央空调系统变量关系模型,计算模型最优解,给出中央空调系统的最优控制策略,实现中央空调系统的智能控制与节能的目的。

Population Ageing,Financial Leverage and Systemic Risk

Population ageing and high financial leverage are two common problems .faced by the worM＇s major economies. The recent financial crisis proved that the two issues could lead to systemic risk if not handled properly. Based on dynamic panel data from 1980 to 2012 in 119 countries, this paper examines the impact of population ageing on financial leverage J？om an empirical point of view and finds that there is a signOqcant inverted U-shape relationship between the two. In addition, empirical studies show that after passing the ＂turning point＂ of ageing, there will be a marked increase in the probability of financial crisis during the ＂deleveraging＂ process. It can be projected from the empirical conclusions of this paper that China will likely enter the range of a turning point between 2019 and 2028. After that, population ageing, deleveraging and asset price collapse may have a ＂resonance＂ effect to severely impact the stability of the financial system. Therefore, China should shift to more proactive macro financial regulations as quickly as possible, as dynamic and robust management of financial leverage and forward-looking control of bubbles could ensure that the financial system remain flexible enough to avoid systemic risk to the greatest extent.

China＇s Sovereign Balance Sheet and Its Risk Assessment

Using available data and necessary estimations, this paper provides a tentative picture of the balance sheet of China＇s sovereign account between 2000 and 2010. The main findings indicate that the net worth of China＇s sovereign assets had been positive and increasing during the period under review. This implies that the Chinese government has sufficient sovereign assets to cover its sovereign liabilities, therefore the likelihood of a sovereign debt crisis in China is extremely low in the near term. Moreover, although China＇s leverage ratio （total liabilities/GDP） is far lower compared to advanced economies, it seems higher than that of other major emerging economies such as Brazil, Russia, and India （BRIC）. In fact, the leverage ratio has been increasing rapidly over recent years and requires special attention. In particular, according to sector-specific analysis, high corporate liability ratios （percentage to GDP） constitute a major concern of China＇s national balance sheet. In 2010, this liability ratio exceeded l OO percent, which exceeds the 90 percent level observed in OECD countries. Lastly, this paper concludes that a sustainable economic growth and structural transformation of growth model are the fundamental means to taming China＇s balance sheet risks.

A statistical method for assessment of the existing correlations of hydrate forming conditions

Hydrate formation in the oil and gas industries has been a serious problem for a long time. It may cause many difficulties for instance in gas pipelines blockages. In order to determine the hydrate forming condition, gas gravity method has been used. Several correlations have been proposed based on gas gravity method. Checking the accuracy of the applied correlations is important. In this paper, the leverage approach is used for this purpose. Leverage approach is a statistical method for detection outliers which identifies the applicability domain （AD） of hydrate data predicting correlations and the quality of the existing data. Moreover, the Williams plot is sketched, which is a graphical depiction for determination of the doubtful points. The obtained results showed the existing correlations are all statistically correct and valid to predict hydrate formation temperature, just one data point is out of the applicability domains, and none of the experimental data can be chosen as outliers.

The Effects of Gross vs.Net Asset Value-Based Managers’Compensation on REIT Capital Structure and Performance:Evidence From the Italian REIT Market

Investors should always argue about management fees because of their impact on net performance that can be substantial.This especially for investments,like real estate,which require intensive management.However,different from traditional mutual funds that are usually related to the gross value of the assets under management,but similar to other financial industry sectors(e.g.hedge funds and private equity funds),REIT managers’compensation structure typically provides a basically fixed payment based alternatively on gross asset value(GAV)or net asset value(NAV).In addition,managers usually also gain a performance fee.The paper analyses how the two alternative compensation schemes influence REITs’investment decisions and capital structure and,consequently,REITs’share value and performance.The final issue addressed is whether—and under which conditions—one compensation scheme is superior to the other.Due to the(usual)market price discount on NAVs,both fee structures incentivise managers to leverage—even in a tax-free environment—in order to maximize the management fees.However,the leverage motivation is stronger for GAV-based than for NAV-based REITs,which are also expected to be more selective in investment decisions.Overall,considering initial fee percentage,GAV-based REITs are expected to execute higher management fees than NAV-based REITs due to the relevant leverage effect.Moreover,debt recourse produces different effects on share value if measured upon market price or net asset value.The empirical analysis focuses on public Italian REITs(2002-2012).The results seem to support the theoretical expectations.GAV-based REITs experience higher debt trends and levels than NAV-based REITs.At the same time,GAV-based REITs register lower real estate asset returns gross and net of management fees for both current and growth yields.Differences in the returns lead to permanent higher performances over total return indexes of NAV-based REITs compared to GAV-based REITs.