Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Research on the Land Consolidation Strategy of Dalian City Based on PESTEL Analysis Model

Standing at the starting point of the"13 th Five-Year Plan",the general situation of Dalian City,the current status and characteristics of land use,and the strategy of land consolidation planning during the"12 th Five-Year Plan"period are analyzed,and then the political,economic,social,technological,environmental and legal factors that influence the land consolidation of Dalian City are analyzed based on the PESTEL model.Afterwards,measures of land consolidation in Dalian City during the"13 th Five-Year Plan"period are proposed,such as transforming the concept of land consolidation,coordinating opinions of agricultural departments and making scientific decisions,reasonably arranging agricultural space,optimizing the layout of rural residential areas and encouraging moderate scale management of land,broadening the content of land consolidation,and implementing soil testing fertilization.

Security Risk Analysis Model for Identification and Resolution System of Industrial Internet

Identification and resolution system of the industrial Internet is the“neural hub”of the industrial Internet for coordination.Catastrophic damage to the whole industrial Internet industry ecology may be caused if the identification and resolution system is attacked.Moreover,it may become a threat to national security.Therefore,security plays an important role in identification and resolution system of the industrial Internet.In this paper,an innovative security risk analysis model is proposed for the first time,which can help control risks from the root at the initial stage of industrial Internet construction,provide guidance for related enterprises in the early design stage of identification and resolution system of the industrial Internet,and promote the healthy and sustainable development of the industrial identification and resolution system.

Modeling Analysis of Factors Influencing Wind-Borne Seed Dispersal: A Case Study on Dandelion

A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.

Prototyping an open environment for sharing geographical analysis models on cloud computing platform

The sharing of geographical analysis models is of crucial importance for simulating geographic processes and phenomena in the current geographical information systems(e.g.Digital Earth),but there remain some issues that have not been completely resolved.The challenges include,eliminating model heterogeneity and searching for suitable infrastructures to support the open sharing and effective execution of models.Taking advantage of cloud computing,this article aims to address the above issues and develop an open environment for geographical analysis model sharing.On the basis of the analysis of the applicability of cloud computing,the architecture of the open environment is proposed.More importantly,key strategies designed for heterogeneous model description,model encapsulating as well as model deploying and transparent accessing in the cloud are discussed in detail to establish such an environment.Finally,the prototype environment is implemented,and experiments were conducted to verify the environment’s feasibility to support the sharing of geographical analysis models.

Cost analysis model for catalytic conversion of syngas in to light hydrocarbon gases

Bio-gasification is a new technology and considered as a more efficient way to utilize bioenergy.The economic feasibility becomes one of the greatest issues when we apply this new technology.Evaluation of economic feasibility of a bio-gasification facility needs better understanding of its production unit cost under different capacities and different working shift modes.The objective of this study was to evaluate the unit cost of biofuel products(Liquid HCs,Light HCs and Oxygenates CxHyOz)under different capacities using a modeling method.The cost analysis model was developed using Visual Basic Microsoft 2008,computer programming language and mathematical equations.The modeling results showed that the unit costs of biofuel product from bio-gasification facility were significantly affected by production capacities of facilities.As the facility capacity increased from 65 to 10,000 N m^3 h^-1,the biofuel production unit cost of gas(Light HCs),oil(Liquid HCs),and aqueous(Oxygenates CxHyOz)decreased from$38.92 per MMBTU,$30.89 per gallon and$25.74 per gallon to$2.01 per MMBTU,$1.59 per gallon,and$1.33 per gallon,respectively.The results of the sensitivity analysis showed that feedstock cost was the most sensitive cost factor on unit costs for all biofuel products at high capacity.The cost analysis model developed in this study could be used to optimize production unit costs of bio-fuel products from bio-gasification facility.

Transient pressure analysis of polymer flooding fractured wells with oil-water two-phase flow

The oil-water two-phase flow pressure-transient analysis model for polymer flooding fractured well is established by considering the comprehensive effects of polymer shear thinning,shear thickening,convection,diffusion,adsorption retention,inaccessible pore volume and effective permeability reduction.The finite volume difference and Newton iteration methods are applied to solve the model,and the effects of fracture conductivity coefficient,injected polymer mass concentration,initial polymer mass concentration and water saturation on the well-test type curves of polymer flooding fractured wells are discussed.The results show that with the increase of fracture conductivity coefficient,the pressure conduction becomes faster and the pressure drop becomes smaller,so the pressure curve of transitional flow goes downward,the duration of bilinear flow becomes shorter,and the linear flow appears earlier and lasts longer.As the injected polymer mass concentration increases,the effective water phase viscosity increases,and the pressure loss increases,so the pressure and pressure derivative curves go upward,and the bilinear flow segment becomes shorter.As the initial polymer mass concentration increases,the effective water phase viscosity increases,so the pressure curve after the wellbore storage segment moves upward as a whole.As the water saturation increases,the relative permeability of water increases,the relative permeability of oil decreases,the total oil-water two-phase mobility becomes larger,and the pressure loss is reduced,so the pressure curve after the wellbore storage segment moves downward as a whole.The reliability and practicability of this new model are verified by the comparison of the results from simplified model and commercial well test software,and the actual well test data.

Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N): II. Paradigm Application to a Bernoulli Model Comprising Uncertain Parameters

This work presents the application of the recently developed “Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N)” to a simplified Bernoulli model. The 5th-CASAM-N builds upon and incorporates all of the lower-order (i.e., the first-, second-, third-, and fourth-order) adjoint sensitivities analysis methodologies. The Bernoulli model comprises a nonlinear model response, uncertain model parameters, uncertain model domain boundaries and uncertain model boundary conditions, admitting closed-form explicit expressions for the response sensitivities of all orders. Illustrating the specific mechanisms and advantages of applying the 5th-CASAM-N for the computation of the response sensitivities with respect to the uncertain parameters and boundaries reveals that the 5th-CASAM-N provides a fundamental step towards overcoming the curse of dimensionality in sensitivity and uncertainty analysis.

Spatial Analysis and Modelling of Wind Farm Site Suitability in Nasarawa State, North-Central Nigeria

There has been an increasing global and local interest in developing renewable, clean, and cheap energy towards achieving Goal number 7 of the Sustainable Development Goals (SDG). However, decisions involving suitable and sustainable locations for renewable energy projects remain an important task. This study employed Geographic Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) to spatially analyze and model wind farm site suitability in Nasarawa State. The aim is to integrate the environmental, social, and economic aspects of decision-making for identifying sustainable wind farm sites. The study distinguished between two sets of decision criteria: decision constraints and decision factors. The former defined the exclusion zones while the latter were standardized based on fuzzy logic to depict varying degrees of suitability across the State. The MCDA applied the weighted linear combination method, with relative weights generated through pairwise comparisons of the analytic hierarchy process to analyze three policy scenarios: equal weights, environmental/social priority, and economic priority scenario. A combination of resulting composite maps from the constraints and the factors gave the final suitability maps. The resulting suitability index (SI) for the respective policy scenario describes the degrees of suitability: Ideal locations were denoted by one (1) and the not suitable locations by zero (0), with values in-between depicting varying degrees of wind farm site suitability. Based on the SI, priority locations indicating areas with good prospects, in addition to the most suitable parcels of land, were identified and delineated. The composite decision constraint revealed that wind farm projects would not be viable in more than half (57.58%) of the State. Wind speed was the major constraint and accounted for the exclusion of 46.25%, with a mean fuzzy membership value of 0.2008 indicating low suitability across the State. Also, the average acceptable wind farm location for the three-policy scenario was 33.33% of the entire study area. Lafia, Obi, Keana, Awe, Nasarawa-Eggon, Wamba and Kokona LGAs were the identified priority Local Government Areas (LGAs). However, only Lafia, Obi, and Nasarawa-Eggon were consistent with changes in the policy objectives. All the priority LGAs have one or more of the most suitable parcels within their administrative boundaries except for Wamba. Despite the severe limitations of wind speed, substantial parts of Nasarawa State still provide great development potentials for wind energy. The “most suitable” locations in Lafia, Nasarawa-Eggon, and Obi LGAs should have first consideration for the development of wind energy in the State.

Impairment of Continuous Insulin Delivery Therapy and Analysis from Graeco-Latin Square Design Model

The desire to deliver measured amount of insulin continuously to patients with type I diabetes, for glycemic control, has attracted a lot of attention. Continuous subcutaneous insulin infusion has seen some success in recent years. However, occlusion of insulin delivery may prevent the patient from receiving the prescribed dosage, with adverse consequence. An in vitro study of insulin delivery is performed, using different insulin pumps, insulin analogs and operating conditions. The aim is to identify incidences of occlusion due to bubble formation in the infusion line. A detailed statistical analysis was performed on the data collected to determine any significant differences and deviations in insulin delivery rates that might be due to factors such as: pump type, the set basal flow rate, insulin type, vibration, and possible insulin occlusion due to air bubble formation within the infusion line. Our findings from the Graeco-Latin Square design model show that there are statistical differences due to the devices, and statistical identifiable clusters are used to distinguish the devices. Such hierarchical models used to describe the analyses, include the flow rate, the pump types, and the activity level.

The finite element analysis of articular cartilage fiber-reinforced composite model under rolling load

Articular cartilage is a layer of low-friction,load-bearing soft hydrated tissue covering bone-ends in diarthrosis,which plays an important role in spreading the load,reducing the joint contact stress,joint friction and wear during exercise.The vital mechanical function

An Application of Machine Learning to Thalassemia Diagnosis

Mediterranean anemia is a genetic disease that currently relies heavily on expert clinical experience to determine whether patients are affected. This method is overly reliant on expert experience and is not precise enough. This paper proposes two modeling methods to predict whether patients have Mediterranean anemia. The first method involves using Principal Component Analysis (PCA) to reduce the dimensionality of the data, followed by logistic regression modeling (PCA-LR) on the reduced dataset. The second method involves building a Partial Least Squares Regression (PLS) model. Experimental results show that the prediction accuracy of the PCA-LR model is 87.5% (degree = 2, λ=4), and the prediction accuracy of the PLS model is 92.5% (ncomp = 4), indicating good predictive performance of the models.

An Emotion Analysis Method Using Multi-Channel Convolution Neural Network in Social Networks

As an interdisciplinary comprehensive subject involving multidisciplinary knowledge,emotional analysis has become a hot topic in psychology,health medicine and computer science.It has a high comprehensive and practical application value.Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research.The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period,so as to understand their normal state,abnormal state and the reason of state change from the information they wrote.In view of the fact that convolutional neural network cannot make full use of the unique emotional information in sentences,and the need to label a large number of highquality training sets for emotional analysis to improve the accuracy of the model,an emotional analysismodel using the emotional dictionary andmultichannel convolutional neural network is proposed in this paper.Firstly,the input matrix of emotion dictionary is constructed according to the emotion information,and the different feature information of sentences is combined to form different network input channels,so that the model can learn the emotion information of input sentences from various feature representations in the training process.Then,the loss function is reconstructed to realize the semi supervised learning of the network.Finally,experiments are carried on COAE 2014 and self-built data sets.The proposed model can not only extract more semantic information in emotional text,but also learn the hidden emotional information in emotional text.The experimental results show that the proposed emotion analysis model can achieve a better classification performance.Compared with the best benchmark model gram-CNN,the F1 value can be increased by 0.026 in the self-built data set,and it can be increased by 0.032 in the COAE 2014 data set.

An empirical analysis on community residents' perception and major influencing factors of rural tourism development

With the rapid development of rural tourism in China,community residents,as important stakeholders in the development of rural tourism,their perceptions and attitudes directly affect the sustainable and healthy development of local rural tourism.Taking the community residents of Xiaogucheng Village in Hangzhou as the research object,using the methods of field interviews and questionnaires,a multiple regression model was established to conduct an empirical analysis on the perception and main factors affecting the development of rural tourism of community residents.The results show that the development of rural tourism in villages with better economic development is not as popular as expected;Where community residents have made ideological progress and are willing to participate in tourism development,the development effect of rural tourism is remarkable;In addition,community residents also hope that their personal abilities can be combined with rural tourism for common development;The destruction of community environment has a slight impact on the development of rural tourism,which shows that the attention is not enough.Finally,based on the analysis conclusion,it provides new ideas and inspiration for the sustainable development of rural tourism:improving the community residents’participation in rural tourism system,establishing the guidance mechanism of community residents’tourism vocational education,and consolidating the achievements of community ecological environment management.

Longitudinal genetic analysis of growth-related traits in red swamp crayfish Procambarus clarkii (Girard)

The red swamp crayfish,Procambarus clarkii,is an economically important species especially in China.Their exoskeleton places serious constraints on growth and culture management.Their growth is achieved through intermittent molting/ecdysis.The longitudinal genetic dynamics for growth-related traits at different ecdysial points in P.clarkii has been unclear to date.In this study,conditional genetic analysis was carried out for growth-related traits(body weight,body length,chela length,and cephalothorax length)based upon a mixed genetic model with conditional additive,dominance,and genotype by environment effects in P.clarkii.A complete diallel cross was made among three geographic populations of P.clarkii for the genetic mating design.Results of the conditional genetic analysis showed that from 4 th molt to 9 th molt the conditional additive variations were increased significantly whereas the conditional non-additive genetic variations(dominance and genotype by environment interaction)were decreased significantly for these growth-related traits.This indicated that lots of new expression of additive effect genes for body weight,body length,chela length,and cephalothorax length occurred during ontogeny,and environment played a signifi cant role in the expression of genes affecting these growth-related traits.Growth of the four traits was mainly affected by non-additive genetic effects in early developmental stage(prior to 4 th molt).The cumulative conditional additive variation for the growth-related traits from 4 th molt to 9 th molt accounted for a large majority of the total conditional additive variations from 2 nd molt to 9 th molt,indicating that this period was very important for the growth of this species.Using the conditional analysis method,dynamics of growth-related traits during an important ontogenetic phase of red swamp crayfish was uncovered.Our results provide valuable insights into refining production of this species.

Investigation for Smartfood’s Market Ability Based on Regression Analysis

Product Development at Smartfood is considering adding a new low-carbohydrate food product labeled K-Pack to their product line.Hence,the company needs to estimate the product’s profit potential and choose the best marketing strategy.In order to investigate the different factors’impact on sales,we establish a multiple regression model.In our model,we consider selling price,advertisement payment,and selling location as independent variables and the sale is a dependent variable.Based on the empirical test,we found that the sales of the product increase as the selling price and the ads investment increase,and locations near bakery sections lead to higher sales.We also found that the final profits increase as the selling price and the ads investment increase.As a result of the analysis made with the model,we provide the company with a full-scale estimation of sales and suggestions on their marketing strategy:higher price,higher advertisement payment,and selling locations near the stores’bakery sections.Compared with the original prediction made by the company’s staff,the methods followed are more accurate and provide suggestions more specifically.

Service Quality Measurement and Competition Strategy Analysis of Online Shopping

E-Commerce refers to such business behavior as conducting trades on a virtual network through the Internet.The core elements contributing to the success of online stores include not only the web-based presentation and the low-price strategy but the quality of online service as well.Importance-Performance Analysis is a method frequently used to evaluate performance and analyze competition strategies.Using IPA,this study analyzed and investigated the service quality of the online shopping of a case company and proposed 10 indexes to measure the service quality of online shopping.a number of suggestions on competition strategies were provided for the case company to improve its competition strategies.