AN APPLICATION OF TOPOLOGICAL ANALYSIS TO STUDYING THE THREE-DIMENSIONAL FLOW IN CASCADES;PART I—TOPOLOGICAL RULES FOR SKIN-FRICTION LINES AND SECTION STREAMLINES

Based on the working of Lighthill and Hunt et al., in the present paper the author has established the topological rules adapting to analysing the skin-friction lines and the section streamlines in cascades. These rules are (1) for a rotor cascade without shroud band, the total number of nodal points equals that the saddle points on the skin-friction line vector fields in eachpitch range; (2) for an annular or straight cascade with no-clearances at blade ends, the total number of saddle points is two more than that of nodal points on the skin-friction line fields in a pitch; (3) the total number of saddles in the secondary flow fields on cross-sections in cascade is one less than that of nodes; (4) in the section streamline vector fields on a meridian surface penetrating a flow passage, and on leading and trailing edge sections, the total number of nodes is equal to that of saddles; (5) on the streamline vector fields of a blade-to-blade surface, the total number of nodes is one less than that of saddles.

Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.

A Processor Performance Prediction Method Based on Interpretable Hierarchical Belief Rule Base and Sensitivity Analysis

The prediction of processor performance has important referencesignificance for future processors. Both the accuracy and rationality of theprediction results are required. The hierarchical belief rule base (HBRB)can initially provide a solution to low prediction accuracy. However, theinterpretability of the model and the traceability of the results still warrantfurther investigation. Therefore, a processor performance prediction methodbased on interpretable hierarchical belief rule base (HBRB-I) and globalsensitivity analysis (GSA) is proposed. The method can yield more reliableprediction results. Evidence reasoning (ER) is firstly used to evaluate thehistorical data of the processor, followed by a performance prediction modelwith interpretability constraints that is constructed based on HBRB-I. Then,the whale optimization algorithm (WOA) is used to optimize the parameters.Furthermore, to test the interpretability of the performance predictionprocess, GSA is used to analyze the relationship between the input and thepredicted output indicators. Finally, based on the UCI database processordataset, the effectiveness and superiority of the method are verified. Accordingto our experiments, our prediction method generates more reliable andaccurate estimations than traditional models.

Compatibility Rules of Neonatal Parenteral Nutrition Prescriptions Based on Association Rules and Hierarchical Cluster Analysis

[Objectives]To explore the compatibility rules of neonatal parenteral nutrition(PN)prescriptions based on association rules and hierarchical cluster analysis,thereby providing a reference for standardizing neonatal parenteral nutrition supportive therapy.[Methods]The data about neonatal PN formulations prepared by the Pharmacy Intravenous Admixture Services(PIVAS)of the Affiliated Hospital of Chengde Medical University from July 2015 to June 2021 were collected.The general information of the prescriptions and the frequency of drug use were analyzed with Excel 2019;the boxplot of drug dosing was drawn using GraphPad 8.0 software;and SPSS Modeler 18.0 and SPSS Statistics 26.0 were used to perform association rules and hierarchical cluster analysis.[Results]A total of 11488 PN prescriptions were collected from 1421 newborns,involving 18 kinds of drugs,which were divided into 11 types of nutrients.Association rules analysis yielded 84 nutrient substance combinations.The combination of fat emulsion-water-soluble vitamins-fat-soluble vitamins-glucose-amino acids had the highest confidence(99.95%).The hierarchical cluster analysis divided nutrients into 5 types.[Conclusions]The prescriptions of PN for newborns were composed of five types of nutrients:amino acids,fat emulsion,glucose,water-soluble vitamins,and fat-soluble vitamins.According to the lack of electrolytes and trace elements,appropriate drugs can be chosen to meet nutritional demands.This study provides reference basis for reasonable selection of drugs for neonatal PN prescriptions and further standardization of PN supportive therapy in newborns.

Composition Analysis and Identification of Ancient Glass Products Based on L1 Regularization Logistic Regression

In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.

Regression Analysis of the Number of Association Rules

The typical model, which involves the measures： support, confidence, and interest, is often adapted to mining association rules. In the model, the related parameters are usually chosen by experience; consequently, the number of useful rules is hard to estimate. If the number is too large, we cannot effectively extract the meaningful rules. This paper analyzes the meanings of the parameters and designs a variety of equations between the number of rules and the parameters by using regression method. Finally, we experimentally obtain a preferable regression equation. This paper uses multiple correlation coeficients to test the fitting efiects of the equations and uses significance test to verify whether the coeficients of parameters are significantly zero or not. The regression equation that has a larger multiple correlation coeficient will be chosen as the optimally fitted equation. With the selected optimal equation, we can predict the number of rules under the given parameters and further optimize the choice of the three parameters and determine their ranges of values.

Analysis of the medication rules of the national patent compound for the treatment of functional dyspepsia

Objective:Based on data mining software,applying frequent itemsets,association rules,hierarchical clustering,complex networks and other data mining methods to analyze the usage and compatibility of traditional Chinese medicine(TCM)patent compound for functional dyspepsia.Method:Use the Chinese patent database to search the compound for the treatment of functional dyspepsia,exclude traditional Chinese medicine extracts,single drugs,combined use of Chinese and Western medicines,etc.,screen the patented compound of TCM,establish an Excel data table,and apply data mining software to The data is subjected to frequency statistics,association rules,cluster analysis and complex network analysis.Result:A total of 238 prescriptions for functional dyspepsia were screened.The four qi of the drugs were mainly warm and calm,the five flavors were mainly sweet and spicy,and the spleen and stomach were the main meridians.The top 10 Chinese medicines with higher frequency are Shanzha、Chenpi、Gancao、Maiya、Jineijin、Fuling、Baizhu、Shenqu、Houpo、Banxia;frequent itemsets show that the drugs are mainly compatible with qi and spleen,qi and digestion;association rules The analysis shows that the common drug pairs used in the treatment of functional dyspepsia include Chenpi-Shanzha、Maiya-Shanzha、Jineijin-Shanzha,etc.;cluster analysis found that there are 4 types of drugs for functional dyspepsia,mainly including drugs for regulating qi-flowing for harmonizing stomach,drugs for soothing liver and promoting Qi,drugs for eliminating food and resolving accumulation,drugs for benefiting qi and strengthening spleen;the 22-flavor Chinese medicine in the core drug network,the core compatibility is mainly to eliminate stagnation and spleen.Conclusion:Data mining research provides a reference for the clinical treatment of functional dyspepsia and the development of TCM formulas;Clinical treatment of functional dyspepsia should grasp the basic principles of strengthening vital energy and eliminating pathogenic factors to benefit qi,strengthen the spleen,and eliminate food.It is a basic treatment method,taking into account the methods of regulating qi-flowing for harmonizing stomach,soothing the liver and relieving depression,relieving dampness and dampness,and combining the specific conditions of patients with syndrome differentiation and treatment.

An Object Extraction Model Using Association Rules and Dependence Analysis

Extracting objects from legacy systems is a basic step in system's object orientation to improve the maintainability and understandability of the systems. A new object extraction model using association rules and dependence analysis is proposed. In this model data are classified by association rules and the corresponding operations are partitioned by dependence analysis.

Stock Pattern Mining and Correspondence Analysis Based on Association Rules

In this paper, association rules were applied to mining patterns in stock K-line trend. The pattern which ordinary investors interested in is defined as T-RG (Three-Red Guards). In the mining process, we take the K-line in A-share markets as objects. Through the analysis, investors can select the appropriate point of purchase and selling point. With the help of T-RG, investors can better improve the chance of short-term investment success in A-share markets. In order to explore and validate the T-RG, the main contents of this paper include the following aspects: putting forward a method that judge the validity of rules based on confidence-lift;proposing the meta rule that corresponds to the pattern of T-RG;developing a computer program to extract the T-RG using MATLAB, which supports batch mining;leading fundamental factors into correspondence analysis with identification indexes;reminding the selected stocks, so as to verify the reliability of the identification indexes. According to the above research, something can be learned: In A-share markets, the higher the discriminant index value is, the less number of shares meeting the requirements is;the same discriminant index value, the stock proportion has difference among plates. Confidence P1, P2 and Lift are extremely related to the GC (General Capital), and Lift is extremely related to the Ind (Industry). In the GEM, confidence P1 of mid-cap is near [0.7,1], Lift is near (1,3), confidence P1 of the manufacturing industry is near [0.7,1].

Study on medication rules of traditional Chinese medicine for Meniere's disease based on data analysis

Objective:Study on medication rules of traditional Chinese medicine in treating Meniere's disease based on data mining technology.Methods:Computer retrieval with since establishment of the“CNKI”,“WF”,“VIP”,there have been literatures on the treatment of Meniere syndrome with Traditional Chinses medicine.Memory preprocessing in accordance with inclusion criteria.Then,EXCLE 2010,SPSS Statistics(ver.25)and SPSS Modeler(ver.18.0)were adopted respectively for frequency analysis,cluster analysis and association rules analysis.Result:A total of 133 references were included in this study,146 prescriptions,192 kinds of drugs,and the total frequency of drugs was 1702.The high frequency Meniere syndrome types were spleen deficiency and phlegm dampness syndrome,wind phlegm syndrome,gallbladder depression and phlegm disturbance syndrome,hyperactivity of liver yang syndrome,phlegm and blood stasis syndrome.The efficacy of drug frequency≥25 were summarized as follows,antiasthmatic drugs for relieving phlegm and relieving cough,diuresis-removing dampness,Tonic drugs,etc.High frequency meridian of drugs are:lung,liver,spleen,etc.High frequency drug properties are:temperature,cold,flat etc.High frequency drug taste:bitter,sweet,pungent,etc.Core drugs:Pinellia,Atractylodes,Poria,Gastrodia,etc.The main prescriptions werealisma soup,Banxia Baizhu Tianma Decoction,Zhengan Xifeng Decoction and Xiaochaihu Decoction.Conclusion:In this study,data mining was used to sort out the treatment of Meniere's disease by traditional Chinese medicine.It was found that the treatment of Meniere's disease was mainly to calm the liver and strengthen the spleen,supplemented by regulating qi and activating blood,clearing heat and opening orifices,tonifying deficiency and tranquilizing mind.

Rules of Pesticide Use for Food Crop Diseases and Pests: A Concise Diagram Based on Correspondence Analysis

In order to ensure food security, the selection of pesticide must take into account the controlling effect and economy in the chemical control of food crop diseases and pests. Although China has registered a large number of pesticides and fungicides on food crops, traditional statistical methods cannot treat the complex relationships between crops, pests and diseases, as well as pesticides. To this end, the correspondence analysis was used to mine the data of pesticides being registered after January 1, 2010 for the prevention and control of pests and diseases on wheat, corn, and rice in China, in order to reveal the general rules of pesticide use for the prevention and control of grain crop pests and diseases and to provide scientifically recommended pesticide regimens.(1) Recommended pesticides for wheat diseases and pests: For underground pest control, phoxim, diazinon or clothianidin is recommended;imidacloprid is recommended for aphid control;avermectin is recommended for mite control;chlorpyrifos is recommended for midge control;the pesticides for rust control could be selected according to the order of epoxiconazole>flutriafol>kresoxim-methyl>cyproconazole≈hexaconazole;tebuconazole is recommended for the prevention and control of smut;difenoconazole is recommended for the simultaneous occurrence of take-all, smut and sheath blight;it is recommended to use carbendazim or thiophanate-methyl for the control of scab;and triazolone or pyraclostrobin is recommended for the control of powdery mildew.(2) Recommended pesticides for corn diseases and pests: For the control of underground pests, fipronil, carbosulfan or chlorpyrifos are recommended;thiamethoxam is recommended for control of planthoppers and corn aphids;Bacillus thuringiensis or phoxim is recommended for control of corn borers;pyraclostrobin is recommended for the control of northern leaf blight;tebuconazole is recommended for the control of head smut;and fludioxonil+metalaxyl-M is recommended for the control of corn stalk rot.(3) Recommended pesticides for rice diseases and pests: It is recommended to use triazophos, avermectin analogs or methoxyfenozide for the control of borers;for rice planthoppers, the pesticides could be selected in order of pymetrozine>imidacloprid>thiamethoxam>thiazide>nitenpyram;avermectin analogs are recommended for the control of rice leaf rollers;tebuconazole is recommended for the control of rice false smut;prochloraz and its manganese salts are recommended for the control of bakanae disease;hymexazol is recommended for the control of wilt disease;thifluzamide or hexaconazole is recommended for the control of sheath blight;and the pesticides for the control of rice blast are in order of tricyclazole>kasugamycin>fenoxanil>isoprothiolane>Bacillus subtilis. In addition, potential applications of correspondence analysis in other fields of plant protection are discussed.

SVR-Miner:Mining Security Validation Rules and Detecting Violations in Large Software

For various reasons,many of the security programming rules applicable to specific software have not been recorded in official documents,and hence can hardly be employed by static analysis tools for detection.In this paper,we propose a new approach,named SVR-Miner(Security Validation Rules Miner),which uses frequent sequence mining technique [1-4] to automatically infer implicit security validation rules from large software code written in C programming language.Different from the past works in this area,SVR-Miner introduces three techniques which are sensitive thread,program slicing [5-7],and equivalent statements computing to improve the accuracy of rules.Experiments with the Linux Kernel demonstrate the effectiveness of our approach.With the ten given sensitive threads,SVR-Miner automatically generated 17 security validation rules and detected 8 violations,5 of which were published by Linux Kernel Organization before we detected them.We have reported the other three to the Linux Kernel Organization recently.

A Survey on Methods and Applications of Intelligent Market Basket Analysis Based on Association Rule

The market trends rapidly changed over the last two decades.The primary reason is the newly created opportunities and the increased number of competitors competing to grasp market share using business analysis techniques.Market Basket Analysis has a tangible effect in facilitating current change in the market.Market Basket Analysis is one of the famous fields that deal with Big Data and Data Mining applications.MBA initially uses Association Rule Learning(ARL)as a mean for realization.ARL has a beneficial effect in providing a plenty benefit in analyzing the market data and understanding customers’behavior.An important motive of using such techniques is maximizing the business profit as well as matching the exact customer needs as closely as possible.In this survey paper,we discussed several applications and methods of MBA based on ARL.Also,we reviewed some association rule learning measurements including trust,lift,leverage,and others.Furthermore,we discuss some open issues and future topics in the area of market basket analysis and association rule learning.

Rule acquisition of three-way semi-concept lattices in formal decision context

Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way semi-concept lattices have three-way operators with weaker constraints,which can generate more concepts.In this article,the problem of rule acquisition for three-way semi-concept lattices is discussed in general.The authors construct the finer relation of three-way semi-concept lattices,and propose a method of rule acquisition for three-way semi-concept lattices.The authors also discuss the set of decision rules and the relationships of decision rules among object-induced three-way semi-concept lattices,object-induced three-way concept lattices,classical concept lattices and semi-concept lattices.Finally,examples are provided to illustrate the validity of our conclusions.

协同与对位:多模态符号视域下的绘本叙事——以《Rules of Summer》为例

在绘本叙事中,有效利用多模态符号间的差异和矛盾,配合绘本阅读方式的不同,调动读者自主展开多模态符号间的协作和对位,可以实现故事叙述,同时丰富叙事层次。从多模态系统整体出发,有意识、有技巧地利用多模态符号系统间的差异和共生,是绘本创作中多模态符际资源配置的手法,也是提升绘本叙事品质和丰富绘本叙事意义的方法。

Influences of nonassociated flow rules on three-dimensional seismic stability of loaded slopes

The influences of soil dilatancy angle on three-dimensional （3D） seismic stability of locally-loaded slopes in nonassociated flow rule materials were investigated using a new rotational collapse mechanism and quasi-static coefficient concept. Extended Bishop method and Boussinesq theorem were employed to establish the stress distribution along the rupture surfaces that are required to obtain the rate of internal energy dissipation for the nonassociated flow rule materials in rotational collapse mechanisms. Good agreement was observed by comparing the current results with those obtained using the translational or rotational mechanisms and numerical finite difference method. The results indicate that the seismic stability of slopes reduces by decreasing the dilatancy angle for nonassociated flow rule materials. The amount of the mentioned decrease is more significant in the case of mild slopes in frictional soils. A nearly infinite slope under local loading, whether its critical failure surface is 2D or 3D, not only depends on the magnitude of the external load, but also depends on the dilataney angle of soil and the coefficient of seismic load.

A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

Identifying Association Rules among Drugs in Prescription of a Single Drugstore Using Apriori Method

These days, health care systems such as pharmacies and drugstores normally produce high volumes of data. Consequently, utilizing data mining methods in health care systems has become a conventional process. In this research, Apriori algorithm has been applied to perform data mining using the data obtained from the prescriptions ordered within a pharmacy. Ten association rules were achieved from the assigned pharmaceutical drugs in those prescriptions using the aforementioned Apriori algorithm. The accuracy of these rules is also manually studied and reviewed by a physician. Among these association rules, Vitamin D and Calcium pills are the most interrelated medications, and Omeprazole and Metronidazole rankd second in terms of association. The results of this study provide useful feedback information about associations among drugs.

Study on the medication rules of traditional Chinese medicine in the treatment of sleep disorder after stroke based on data mining

Objective:To explore the medication rule of Traditional Chinese Medicine(TCM)in the treatment of sleep disorder after stroke by using data mining technology.Methods:A computer search was used to search the electronic database of clinical literature on the treatment of sleep disorders after stroke by TCM from January 2000 to January 2021.Excel was used to establish the database,and the prescription information was described and analyzed statistically.Using IBM SPSS Modeler 18.0 software,Apriori algorithm was used for TCM association analysis,and IBM SPSS 22.0 software was used for systematic cluster analysis of high-frequency TCM.Results:A total of 67 literatures were included,covering 131 traditional Chinese medicines.The medecines with a higher frequency of sodium use include Ziziphi Spinosae Semen(Suanzaoren),Angelicae Sinensis Radix(Danggui),Ligusticum(Chuanxiong),liquorice(Gancao),Poria cocos(Fuling),and so on.From the effect point of view,deficiency-tonifying medicine,sedative medicine and blood-activating and stasis-removing medicine are commonly used.The medicinal properties are mainly cold,mild and warm.The main medicine flavor are sweet and bitter.The medicines mostly belong to the liver,heart and spleen Meridian.Thirty-three association rules were obtained for medicine pairs and medicine groups from the correlation analysis,and the core combinations were"Ziziphi Spinosae Semen(Suanzaoren)-Tuber fleeceflower stem(Yejiaoteng)","Ziziphi Spinosae Semen(Suanzaoren)-Polygala(Yuanzhi)","Ziziphi Spinosae Semen(Suanzaoren)-Cortex albiziae(Hehuanpi)"and"Angelicae Sinensis Radix(Danggui)-Radix bupleuri(Chaihu)-Radix Paeoniae Alba(Baishao)"and so on.Seven medicine aggregation groups were obtained by medicine cluster analysis.Conclusion:In the treatment of sleep disorder after stroke by TCM,the main method is to calm the heart and mind.Meanwhile,according to different syndrome types,the treatment methods of tonifying the heart and spleen,nourishing the liver and kidney,soothing the liver and softening the liver,clearing heat and resolving phlegm,nourishing the blood and promoting blood circulation are selected,which provide certain reference for clinical treatment.

Acupoint selection rules for acupoint application in lung diseases in the post-epidemic era

Objective:To summarize the rules of acupoint selection of acupoint application to prevent and treat lung diseases under the background the post-epidemic era using data-mining technology.Method:The CNKI,Wanfang database,and VIP database were searched for clinical study articles on lung diseases treated by acupoint application published in the past 5 years.Data-eligible papers were extracted to establish a database of acupoint application for lung disease using Microsoft Excel 2019,with the goal of analyzing the frequency of acupoints,acupoint-meridian association,acupoint-location association,specific acupoint frequency,and cluster analysis.Association rules,consisting of acupoints with an application frequency of≥10,were devised by the Apriori algorithm to explore the correlation between acupoint groups and to analyze the rules of the compatibility of acupoint prescriptions.Results:A total of 229 eligible papers met our inclusion criteria.Forty-seven acupoints were applied,for a total frequency of acupoints of 1,035 times.Among these,acupoints for lung diseases were primarily distributed in the back-and-waist and chest-and-abdomen areas.From the analysis of the association rules,we obtained four groups of acupoint association rules based on acupoint clusters with a frequency≥10 and found that Feishu(BL 13),Tiantu(CV 22),Dazhui(GV 14),Dingchuan(EX-B1),and Danzhong(CV 17)constitute the core acupoints of prescriptions for clinical acupoint application to prevent and treat lung diseases.Conclusion:It is clearly shown that the core acupoints are relatively concentrated and that the selected acupoints were mainly locally selected,which could be a matching reference for the long-term prevention and treatment of lung diseases,including COVID-19.