Using Linear Regression Analysis and Defense in Depth to Protect Networks during the Global Corona Pandemic

The purpose of this research was to determine whether the Linear Regression Analysis can be effectively applied to the prioritization of defense-in-depth security tools and procedures to reduce cyber threats during the Global Corona Virus Pandemic. The way this was determined or methods used in this study consisted of scanning 20 peer reviewed Cybersecurity Articles from prominent Cybersecurity Journals for a list of defense in depth measures (tools and procedures) and the threats that those measures were designed to reduce. The methods further involved using the Likert Scale Model to create an ordinal ranking of the measures and threats. The defense in depth tools and procedures were then compared to see whether the Likert scale and Linear Regression Analysis could be effectively applied to prioritize and combine the measures to reduce pandemic related cyber threats. The results of this research reject the H0 null hypothesis that Linear Regression Analysis does not affect the relationship between the prioritization and combining of defense in depth tools and procedures (independent variables) and pandemic related cyber threats (dependent variables).

A Vehicle Traveling Time Prediction Method Based on Grey Theory and Linear Regression Analysis

Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider both aspects of time and space. In this paper, a vehicle traveling time prediction method based on grey theory （GT） and linear regression analysis （LRA） is presented. In aspects of time, we use the history data sequence of bus speed on a certain road to predict the future bus speed on that road by GT. And in aspects of space, we calculate the traffic affecting factors between various roads by LRA. Using these factors we can predict the vehicle＇s speed at the lower road if the vehicle＇s speed at the current road is known. Finally we use time factor and space factor as the weighting factors of the two results predicted by GT and LRA respectively to find the final result, thus calculating the vehicle＇s traveling time. The method also considers such factors as dwell time, thus making the prediction more accurate.

Predicting urbanization level by main element analysis and multiple linear regression---taking Xiantao district in Hubei Province as an example

In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and lastly predict its urbanization level

CFD Analysis and Optimization of Automobile Radiator based on STAR-CCM+

This research talks about the radiator cooling system of the automobile engine,the radiator’ s fluidstructure interaction dynamics based on computational fluid dynamics( CFD) STAR-CCM+ software. The linear regression model of coolant determined by MATLAB software was imported into the user-defined field function of the software,using the standard K-Epsilon turbulence model to analyze temperature,pressure and velocity changes of the coolant in the radiator channel. In order to improve the efficiency of the radiator,it is necessary to analyze the structure of two kinds of heat sinks,and get better heat transfer effect.

Education Investment Fixed Asset Investment and Regional Economic Development Differences--Empirical analysis based on Chinese

In this article,it discusses the di£ferences in economic development between urban and rural areas and regions in our country from the perspective of education investment and fixed asset investment.Based on the provincial data of 31 provinces from 1999 to 2017 released by National Bureau of Statistics,it expends the Cobb-Douglas model and Lucas model,and analyses the data with multiple linear regression models.From the study,it finds that compared with investment in fixed assets,investment in education has a larger role in promoting economic development,which is more obvious in the underdeveloped central and western regions and rural areas.However,at the same time it needs to note that the positive effects of education investment will be restricted by the economic structure and policy environment,and education expenditure policies should also be implemented in accordance with time and local conditions.

Analysis of Alkaline Foam to Water Temperature Model

Factors affecting bath water temperature model include the shape and size of a bath, people’s gesture, volume, individual temperature adaptation as well as body movement in the bath. In addition, the bathroom space, ambient temperature and bath materials will also affect changes of the water temperature to a certain extent. In this paper, the cooling function and linear regression method are used and the MATLAB software is also used to simulate the model of water temperature, alkaline bath foams that obtained can accelerate changes in water temperature.

中国8省市50岁及以上人群卫生保健服务满意度与生活质量的关联研究

目的探讨50岁及以上人群卫生保健服务满意度和生活质量之间的关系。方法利用世界卫生组织(World Health Organization,WHO)全球老龄化与成人健康研究中国项目基线调查资料,选取我国8个省/直辖市15050名50岁及以上的中老年人,使用全球老龄化与成人健康研究问卷和WHO生活质量量表8项简化版评估卫生保健服务满意度和生活质量,并获取社会人口学及慢性病患病情况等信息,使用多元线性回归模型分析两者之间的关系并按居住地、性别和年龄组进行分层分析。结果研究共纳入研究对象13408人,平均年龄为(63.86±10.24)岁,对本市(区)提供的卫生保健服务感到非常满意的占4.16%,感到满意的占58.90%,感到一般的占30.81%,感到不满意的占5.69%,感到非常不满意的占0.44%。研究对象生活质量得分为(40.25±15.56)分,多元线性回归分析显示研究对象的卫生保健服务满意度越高,生活质量越好(P<0.001)。在分层分析中,该关联在不同居住地区、不同性别以及不同年龄组中均有统计学意义(P<0.001)。结论50岁及以上的人群中,较高的卫生保健服务满意度和较高的生活质量相关。

Biomass estimation of Shorea robusta with principal component analysis of satellite data

Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.

Experimental Study on Anchoring Physical Properties of Different Anchoring Lengths Coupled with Temperature and Pressure

Aiming at deep roadway anchorage solids, laboratory similar model tests were used to reveal the mechanical properties of anchorage solids with different anchorage lengths under the coupling effect of temperature and pressure, and SPSS statistical analysis software was used to conduct linear regression analysis of the ultimate anchorage force obtained from the tests. The results show that: through multiple linear regression analysis, the influence degree of temperature and pressure coupling on the ultimate anchorage force is arranged in order of anchoring length > surrounding rock strength > temperature > side pressure coefficient, and the linear regression equation of the model is obtained. Compared with the linear regression equation of simulation results, the model has a high explanatory ability.

GROUNDWATER QUALITY AND CONTAMINATION INDEX MAPPING IN CHANGCHUN CITY,CHINA

Groundwater in Changchun City, Jilin Province of China tends to be influenced by human activities. Chemical types of groundwater were detected in both shallow and deep groundwater were: HCO3--Ca2+ and HCO3--Ca2+·Mg2+ or HCO3--Mg2+·Ca2+; SO42--Ca2+ and SO42--Ca2+·Mg2+; Cl--Ca2+; and CO32--Na+. The deteriorations of groundwater quality due to the increase of TDS, NO3-+ NO2-(as Nitrogen) and TH contents have been observed from 1991 to 1998. Scatter analyses showed strong positive correlations between Ca2+, Cl-and NO3-ions and weak negative correlations between the depth of water table and Ca2+, SO42-, Cl-and NO3-ions. A mapping of contaminant index based on Chinese standard of groundwater showed that a large proportion of the groundwater in 1998 was deteriorated by human process. Despite their low values of sodium adsorption ratio (SAR), the most of the sampled wells were not suitable for drinking and agriculture purposes due to higher contents of NO3-, NO2-and Mn2+ ions.

A Thermal Event in the Ordos Basin:Insights from Illite ^40Ar-^39Ar Dating with Regression Analysis

Four samples from a Permian reservoir in the Ordos Basin of North China were separated into twelve fractions in grain sizes of 〈0.5, 0.5-1 and 1-2 μm. Using the ^40Ar-^39Ar step-heating method, all of the fractions essentially yielded plateau ages ranging from 172.5 to 217.1 Ma. These scattered plateau ages might not have been obtained from pure diagenetic illites but from mixed clay minerals, although the samples were disaggregated using a gentle freeze-thaw cycle to free them of non-clay minerals. A regional thermal event, as suggested by several proxies, led to intensive iHitization as a distinct diagenetic process when the Yanshanian Movement triggered magmatism around the entire North China Block during the Jurassic to Cretaceous. Thermal illites formed during a short time period, whereas detrital illites came from various sources. The scattered plateau ages could have resulted from mixed degassing of thermal and detrital illites. Within one sample, the plateau ages decrease with the diminution of grain sizes, but it is difficult to extrapolate to the detrital-illite-free ages. Because the plateau age is a mixture of ages for thermal and detrital illites, this regression analysis studies the dependence of the plateau ages on the synthetic values of contents and ages of detrital illites instead of on the grain sizes. Comparing the samples to one another, the plateau ages show the same trend among the different grain sizes. Weighted by the contents and ages of detrital illites, linear regression analysis revealed the relationship between the plateau ages and the relative weight proportions. Based on iterated calculations, a thermal event age and a set of weight proportions were derived. The regressed thermal event age is 163.3±1.6 Ma, which coincides with regional thermal activities and links to gas accumulation.

Effects of Tidal Channels and Roads on Landscape Dynamic Distribution in the Yellow River Delta, China

Landscape characters in estuarine regions generally controlled by tidal regimes and human activities like road construction.In this work,tidal channels and road construction in the Yellow River Delta(YRD)were extracted by visual interpretation methods so as to decipher impacts of tidal channel development and road construction on landscape patch change during 1989–2016.Spatial distribution history of three wetlands,which covered by Phragmites australis(freshwater marsh,FM),Suaeda salsa(salt marsh,SM),and mudflats(MD)were also established.Results indicated that tidal channel,number,frequency,and fractal dimension were all the maximum in 2003,and the minimum in 1998,respectively.Road length,number,and density showed increasing trend during 1989–2016.MD were the predominant landscape type,followed by FM and SM during 1989-2016.Principal component analysis implied two extracted factors,F1 and F2,which could represent 91.93% of the total variations.F1 mainly proxied tidal channel development,while F2 represented road construction.A multiple linear regression analysis showed positive effects of both F1 and F2 on FM patch numbers and negative impacts on SM patch areaes with R^2 values of 0.416 and 0.599,respectively.Tidal channels were negatively related to MD patch numbers,while roads were positively related to that.In any case,road construction showed larger impacts on landscape type shifting than that of tidal channel development in the YRD.

Factors affecting daily activities of patients with cerebral infarction

BACKGROUND： Stroke is the leading cause of death and long-term disability. This study was undertaken to investigate the factors influencing daily activities of patients with cerebral infarction so as to take interventional measures earlier to improve their daily activities.METHODS： A total of 149 patients with first-episode cerebral infarction were recruited into this prospective study. They were admitted to the Encephalopathy Center, Department of Neurology, the First Affiliated Hospital of Wenzhou Medical College in Zhejiang Province from August 2008 to December 2008. The baseline characteristics of the patients and cerebral infarction risk factors on the first day of admission were recorded. White blood cell （WBC） count, plasma glucose （PG）, and many others of laboratory targets were collected in the next morning. Barthel index （BI） was calculated at 2 weeks and 3 months respectively after onset of the disease at the outpatient clinic or by telephone call. Lung infection, urinary tract infection and atrial fibrillation if any were recorded on admission. The National Institute of Health Stroke Scale （NIHSS） scores and the GCS scores were recorded within 24 hours on and after admission, at the second week, and at the third month after the onset of cerebral infarction respectively.RESULTS： The factors of BI at 2 weeks and 3 months after onset were the initial PG level, WBC count and initial NIHSS scores. Besides, urinary tract infection on admission was also the factor for BI at 3 months.CONCLUSION： Active measures should be taken to control these factors to improve the daily activities of patients with cerebral infarction.

Spatiotemporal Characteristics of Wetlands Ecosystem in the Niger Delta Region

Wetlands are classified as essential and valuable components of the ecosystem. Wetlands are significant for ecosystem services such as nutrient cycles, soil formation and water treatment. Nearly half of the world’s wetlands have vanished in the last century because of anthropogenic activities, agricultural land use, and urban development, one of such places that are faced with the challenges of sustainability is the wetland habitats. This study aimed at assessing the spatial temporal characteristics of wetlands ecosystem in the Niger Delta Region of Nigeria from 1986-2016. The secondary data include raw satellite imageries obtained from the archive of the United States Geological Survey and Earth Explorer. The data set includes a notable period of four years landsat images for, 1986, 1996, 2006 and 2016. The maps were projected using Universal Transverse Mercator (UTM) projection system and datum WGS 84 of zone 32. Satellite images of the study area were acquired from the United States Geological Survey (USGS). The USGS uses the LandSat5 Thematic Mapper (TM) Landsat7 Thematic Mapper, Enhanced Thematic Mapper (ETM+), Thermal Infrared Sensor (TIRS) and Landsa8 Operational Land Imager (OLI) to generate high resolution images that are useful for this type of study. The satellite imageries were also analyzed using GIS and Remote Sensing techniques by computing of Normalized Differential Vegetation Index (NDVI) values for the entire study area by conversion of spectral reflectance values into NDVI values. The satellite images covering the area were acquired and analyzed using ArcGIS10.6. A total area of 25,053.93 (km2) was delineated in the study area. After processing the imagery, five land use/land cover (LULC) classes were developed in ArcGIS environment, such as Built-up area, Fallow land, Vegetation, Wetland and Waterbody. This study concludes that changes in wetland landscape patterns will produce profound impacts in urban areas where there are rapid anthropogenic activities. Anova table showed a huge significant relationship between time and vegetation decrease across the study area at 0.027 which is less than 0.05 significance level. Wetlands warming and drying will cause the shrinking and reduction of wetland in sizes from accelerated wetland degradation. Therefore, there is an interaction and mutual influence between dynamic changes of wetland landscape patterns and other land use classes.

Solution and Application of the Matrix Equation Ax=b

In this paper,we first give the solution concept of the fuzzy matrix equation =. Secondly,we discuss the property of the solution and give the method of solving the fuzzy matrix equation A=. Finally,we present an application of solving fuzzy matrix equation A= to the fuzzy linear regression analysis,establish a new model of fuzzy linear regression,and introduce a new method of estimating parameters.

Statistical approach to determination of overhaul and maintenance cost of loading equipment in surface mining

The purpose of this research was to develop a new approach in determination of overhaul and maintenance cost of loading equipment in surface mining. Two statistical models including univariate exponential regression (UER) and multivariate linear regression (MLR) were used in this study. Loading equipment parameters such as bucket capacity, machine weight, engine power, boom length, digging depth, and dumping height were considered as variables. The results obtained by models and mean absolute error rate indicate that these models can be applied as the useful tool in determination of overhaul and maintenance cost of loading equipment. The results of this study can be used by the decision-makers for the specific surface mining operations.

A Hybrid Dynamical-Statistical Approach for Predicting Winter Precipitation over Eastern China

Correlation analysis revealed that winter precipitation in six regions of eastern China is closely related not only to preceding climate signals but also to synchronous atmospheric general circulation fields. It is therefore necessary to use a method that combines both dynamical and statistical predictions of winter precipitation over eastern China （hereinafter called the hybrid approach）, in this connection, seasonal real-time prediction models for winter precipitation were established for the six regions. The models use both the preceding observations and synchronous numerical predictions through a multivariate linear regression analysis. To improve the prediction accuracy, the systematic error between the original regression model result and the corresponding observation was corrected. Cross-validation analysis and real-time prediction experiments indicate that the prediction models using the hybrid approach can reliably predict the trend, sign, and interannual variation of regionally averaged winter precipitation in the six regions of concern. Averaged over the six target regions, the anomaly correlation coefficient and the rate with the same sign of anomaly between the cross-validation analysis and observation during 1982-2008 are 0.69 and 78%, respectively. This indicates that the hybrid prediction approach adopted in this study is applicable in operational practice.

Increasing trend of lightning activity in the South Asia region

Lightning is an important natural source of wildfires and oxynitride,and hence significantly influences ecological systems and atmospheric chemistry.Here,we choose South Asia,an important region for global water reallocation and global climate changes,to examine lightning variations based on the longest existing lightning dataset from the OTD/LIS observations.We identify a clear increase in lightning density in the research region,increasing at a rate of 0.096 fl km^(-2)a^(-1)over the last two decades.Multiple linear regression analysis is adopted to identify the main influencing factors among ten potential thermodynamic or microphysical factors and the crucial areas contributing to the increases in lightning.The surface latent heat flux along the west coast of the Indian subcontinent is the largest contributor,explaining52%of the lightning variance and contributing to a 0.025 fl km^(-2)a^(-1)increase.The sea surface temperature in the Arabian Sea,the convective available potential energy(CAPE)over the northwestern Indian subcontinent,and the wind shear along the northwestern coast also make important contributions to the lightning increase,indicating that the thermodynamic effects overwhelm the microphysical effects on lightning activity over the South Asia region.

RELATIVE LEVELS OF INDOOR AND OUTDOOR PARTICLE NUMBER CONCENTRATIONS IN A RESIDENTIAL BUILDING IN XI'AN

The time series of indoor and outdoor particle number concentrations in a naturally ventilated residential building in Xi＇an were tested simultaneously for 7 days in summer. The relationships between indoor and outdoor concentrations were examined and discussed, and linear regression analysis was employed to correlate the indoor and outdoor concentrations. The diurnal cycles of indoor and outdoor particle concentrations of different particle size ranges all showed positive correlations between indoor and outdoor number concentrations, The I/O ratios of number concentrations varied with the increase of particle size in the range of 0.89 （±0.19） to 0.99 （±0.15）.