The study of slip line field and upper bound method based on associated flow and non-associated flow rules

At present, associated flow rule of traditional plastic theory is adopted in the slip line field theory and upper bound method of geotechnical materials. So the stress characteristic line conforms to the velocity line. It is proved that geotechnical materials do not abide by the associated flow rule. It is impossible for the stress characteristic line to conform to the velocity line. Generalized plastic mechanics theoretically proved that plastic potential surface intersects the Mohr-Coulomb yield surface with an angle, so that the velocity line must be studied by non-associated flow rule. According to limit analysis theory, the theory of slip line field is put forward in this paper, and then the ultimate beating capacity of strip footing is obtained based on the associated flow rule and the non-associated flow nile individually. These two results are identical since the ultimate bearing capacity is independent of flow role. On the contrary, the velocity fields of associated and non-associated flow rules are different which shows the velocity field based on the associat- ed flow rule is incorrect.

Scaling Rules for the Percolation Model of Dielectric Breakdown

Aim To study the dIelectric breakdown phenomenon in the materials with quenched disorder. Methods Renormolization group methods were used. Results The percolation limit for breakdown pc , the breakdown field Ec～(Pc-p)v, and the fractal dimension of the structure of dielectric breakdown df were obtained. Conclusion The breakdown properties of the materials with quenched disorder are characterized by universal power laws, where the exponents are universal.

A NEW EVIDENCE UPDATING RULE BASED ON CONDITIONAL EVENT

Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledge in AI. The appearance of uncertain reasoning urges us to measure the belief of rule. Now,most of uncertain reasoning models represent the belief of rule by conditional probability. However,it has many limitations when standard conditional probability is used to measure the belief of expert system rule. In this paper,AI rule is modelled by conditional event and the belief of rule is measured by conditional event probability,then we use random conditional event to construct a new evidence updating method. It can overcome the drawback of the existed methods that the forms of focal sets influence updating result. Some examples are given to illustrate the effectiveness of the proposed method.

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.

Study on the Medication Rules of Traditional Chinese Medicine Prescriptions for the Treatment of New Crown Pneumonia Based on Data Mining Technology

[Objectives]This study was conducted to analyze the medication rules of clinical prescriptions of traditional Chinese medicine decoction pieces for the treatment of novel coronavirus pneumonia(COVID-19)during the epidemic in multiple regions based on data mining technology,so as to provide a reference for the treatment of COVID-19 with traditional Chinese medicine.[Methods]The traditional Chinese medicine prescriptions used since the outbreak of COVID-19 in Hubei Province during the fight against the epidemic from February 25,2020 to February 14,2022,the traditional Chinese medicine prescriptions used by Guizhou traditional Chinese medicine expert team aiding Hubei Province,the traditional Chinese medicine prescriptions for rehabilitation and conditioning of patients in Ezhou of Hubei Province after discharge,the traditional Chinese medicine prescriptions for the prevention and treatment of COVID-19 in Guizhou Province,and the traditional Chinese medicine prescriptions for the treatment of COVID-19 collected from the end of 2019 to the present from the Chinese database of CNKI were collected as the data of this study.Excel was used to establish a database and enter it into the TCM inheritance calculation platform V3.5,and the association rules and k-means clustering algorithm were used to analyze the frequency of herbal medicines in prescriptions during the treatment of COVID-19,the frequency of four natures,five flavors,meridian distribution,and drug combinations.[Results]A total of 1859 COVID-19 patients treated with traditional Chinese medicine were included,and the proportion of males was higher than that of females,and middle-aged and elderly people were the most common group.A total of 2170 prescriptions of traditional Chinese medicine were included,involving a total of 383 traditional Chinese medicines.High-frequency medicines included poria,Radix Bupleuri,Radix Scutellariae,Herba Pogostemonis,Fructus Forsythiae,Flos Loniceraeetc.The four natures were mainly concentrated in cold,warm and neutral,and the five flavors were mainly concentrated in bitter,pungent and sweet.The herbal medicines were mainly attributed to the lungs and stomach meridians,and were mainly of heat-clearing,exterior syndrome-relieving and diuresis-promoting and damp-clearing types.A total of 24 high-frequency herbal combinations and 35 association rule were excavated,and 3 types of formulas were obtained by cluster analysis.[Conclusions]The analysis results and medicine combinations obtained in the formulas are consistent with the traditional Chinese medicine treatment theory of COVID-19 caused by wind-heat filth accompanied with damp and toxin.

MUPS identification based on discrimination rules

The minimal unsatisfiability-preserving sub-TBoxes（MUPS）of an unsatisfiable class C identified by two equivalent transformations,axiom splitting and ontology reduction,and three discrimination rules comprise minimal sets of axioms which support the unsatisfiability.Discrimination rules classify all MUPS into three types based on the transitivity of unsatisfiability,fully dependent on C（MUPSf）,transitively dependent on C（MUPSt）and uncertainly dependent on C（MUPSu）.The results show that the number of MUPSt is frequently a large fraction of the total number of all MUPS,but only MUPSf catches the root error of C.Modelers and domain experts conduct iterative repair work effectively,considering only MUPSf in each iteration.The classification shows the significance for the evaluation of the quality of ontologies from the perspective of maintenance and for repair work.

Exploring the rules of cropland elevation uplift in China

Cropland elevation uplift(CLEU) has recently become a new challenge for agricultural modernization,food security,and sustainable cropland use in China.Uncovering the rules of CLEU is of great theoretical and practical significance for China’s sustainable agricultural development and rural revitalization strategy.However,existing studies lack in-depth disclosure of multi-scale CLEU evolution rules,making it difficult to support the formulation of specific cropland protection policies.We analyzed the spatio-temporal evolution and multiscale CLEU in China from 1980 to 2020 using the Lorenz curve,gravity center model,hotspot analysis,and cropland elevation spectrum.The results indicated that the center of gravity of cropland moved to the northeast from 1980 to 2000 and then shifted to the northwest.The spatial distribution of cropland became increasingly imbalanced from 1980 to 2000.The change hotspots clustered in the northwest and the northeast,whereas cold-spots were mainly in southeastern China.The average elevation of cropland increased by 17.38 m,and the elevation uplift rule in different regions differed evidently across scales.From 1980 to 2000,all provinces except Xinjiang,Inner Mongolia,Gansu,and Yunnan exhibited CLEU,with Qinghai,Tibet,Beijing,and Guangdong showing the most noticeable uplifting.The CLEU can alleviate the shortage of cropland to some extent.However,without a planning constraint,the CLEU will lead to the increase of ecological risk and food security risk.

Text categorization based on fuzzy classification rules tree

To deal with the problem that arises when the conventional fuzzy class-association method applies repetitive scans of the classifier to classify new texts,which has low efficiency, a new approach based on the FCR-tree（fuzzy classification rules tree）for text categorization is proposed.The compactness of the FCR-tree saves significant space in storing a large set of rules when there are many repeated words in the rules.In comparison with classification rules,the fuzzy classification rules contain not only words,but also the fuzzy sets corresponding to the frequencies of words appearing in texts.Therefore,the construction of an FCR-tree and its structure are different from a CR-tree.To debase the difficulty of FCR-tree construction and rules retrieval,more k-FCR-trees are built.When classifying a new text,it is not necessary to search the paths of the sub-trees led by those words not appearing in this text,thus reducing the number of traveling rules.Experimental results show that the proposed approach obviously outperforms the conventional method in efficiency.

Thermal effect and energy-level transition rule for a mesoscopic LC circuit with inductance-capacitance coupling

This paper reports that the mesoscopic inductance and capacitance coupling LC circuit is quantized by means of the canonical quantization method. Using the ＇invariant eigen-operator＇ method, it deduces the energy-level transition rule when the system is disturbed by an external electromagnetic field. At the same time, the quantum fluctuations for the system at finite temperature are examined by virtue of the generalized Hellmann-Feynman theorem.

The research on rule of Acupoints and Massage Manipulations selection for Post-ischemic Stroke Constipation based on association rule and entropy clustering analysis

Constipation is a common complication of stroke,and it is increasing year by year,which is worthy of attention.In fact,as an effective treatment for Post-ischemic Stroke Constipation,massage has been recognized by doctors at home and abroad.However,In the known research reports,massage prescriptions are complicated,therefore,a simple and effective massage prescription is urgently needed to effectively guide the clinic and promote it.In this study,we used association rule and entropy clustering analysis methods to mine clinical literature on Post-ischemic Stroke Constipation in 7 databases,and combined with data analysis,traditional chinese massage theory and clinical practice,a core new prescription is summarized.The core new prescription of massage in treating Post-ischemic Stroke Constipation take tonifying spleen,nourishing Qi and generating Body Fluid,promoting Qi,invigorating the circulation of blood and eliminating phlegm as the principle of treatment,which is accord with the pathogenesis of this disease,can better guide the clinical practice and facilitate the popularization and application of massage therapy.

New insight into prediction of phase behavior of natural gas hydrate by different cubic equations of state coupled with various mixing rules

Progress in hydrate thermodynamic study necessitates robust and fast models to be incorporated in reservoir simulation softwares. However, numerous models presented in the literature makes selection of the best,proper predictive model a cumbersome task. It is of industrial interest to make use of cubic equations of state(EOS) for modeling hydrate equilibria. In this regard, this study focuses on evaluation of three common EOSs including Peng–Robinson, Soave–Redlich–Kwong and Valderrama–Patel–Teja coupled with van der Waals and Platteeuw theory to predict hydrate P–T equilibrium of a real natural gas sample. Each EOS was accompanied with three mixing rules, including van der Waals(vd W),Avlonitis non-density dependent(ANDD) and general nonquadratic(GNQ). The prediction of cubic EOSs was in sufficient agreement with experimental data and with overall AARD% of less than unity. In addition, PR plus ANDD proved to be the most accurate model in this study for prediction of hydrate equilibria with AARD% of 0.166.It was observed that the accuracy of cubic EOSs studied in this paper depends on mixing rule coupled with them,especially at high-pressure conditions. Lastly, the present study does not include any adjustable parameter to be correlated with hydrate phase equilibrium data.

Operating Rule Classification System of Water Supply Reservoir Based on Learning Classifier System

An operating rule classification system based on learning classifier system （LCS）, which learns through credit assignment （bucket brigade algorithm, BBA） and rule discovery （genetic algorithm, GA）, is established to extract water-supply reservoir operating rules. The proposed system acquires an online identification rate of 95% for training samples and an offline rate of 85% for testing samples in a case study. The performances of the rule classification system are discussed from the rationality of the obtained rules, the impact of training samples on rule extraction, and a comparison between the rule classification system and the artificial neural network （ANN）. The results indicate that the LCS is feasible and effective for the system to obtain the reservoir supply operating rules.

A Comparative Study of f_B within QCD Sum Rules with Two Typical Correlators up to Next-to-Leading Order

The B-meson decay constant fB is an important component for studying the B-meson decays, which can be studied through QCD sum rules. We make a detailed discussion on f B from two sum rules up to next-to- leading order, i.e. sum rules I and II, which are derived from the conventional correlator and the correlator with chiral currents respectively. It is found that these two sum rules are consistent with each other. The sum rules H involves less non-perturbative condensates as that of sum rules I, and in principle, it can be more accurate if we know the dimensionfour gluon condensate well. It is found that fB decreases with the increment of mb, and to compare with the Belle experimental data on fB, both sum rules I and H prefer smaller pole b-quark mass, mb= 4.68 ± 0.07 GeV. By varying all the input parameters within their reasonable regions and by adding all the uncertainties in quadrature, we obtain fB=172-25^＋23 MeV for sum rules I and fB =214-34^26 MeV for sum rules П.

Prescription and treatment rules for the prescriptions containing Poria cocos and Atractylodes macrocephala couplet medicine based on traditional Chinese Medicine inheritance support platform

Objectives:To provide a theoretical basis for the development of the new products of Poria cocos-Atractylodes macrocephala couplet medicine.Methods:All prescription preparations containing Poria cocos and Atractylodes macrocephala were collected from the Drug Standards of the Ministry of Public Health Drug Standard·Traditional Chinese Medicine Set Prescription Preparation(called Traditional Chinese Medicine Set Prescription Preparation for short).After standardization,the information of each prescription preparation was input into the Chinese Traditional Medicine Inheritance Support Platform(V2.5),and the relevant rules of the software were adopted.Data mining methods were used to analyze the frequency of drugs,main symptoms and diseases in prescriptions,and to analyze the regularity of prescriptions.The prescription rules of top 2 high frequency attending syndromes and diseases were analyzed.Results:There were total of 337 prescription preparations containing couplet medicine of Poria cocos and Atractylodes macrocephala,107 kinds of main symptoms and 66 kinds of diseases.The high frequency syndromes were deficiency of Qi and blood and weakness of spleen and stomach,and the high frequency syndromes were anorexia and irregular menstruation.Conclusion:The couplet medicine of Poria cocos-atractylodes macrocephala prescription is mainly used to treat digestive tract diseases and gynecological diseases;it mostly takes tonifying deficiency efficat.It can treat different diseases being compatible with different medicinal materials.The study can provide theoretical basis for clinical application and new drug development of the couplet medicine of Poria cocos-atractylodes macrocephala.

Generating Fuzzy Rule-based Systems from Examples Based on Robust Support Vector Machine

This paper firstly proposes a new support vector machine regression (SVR) with a robust loss function, and designs a gradient based algorithm for implementation of the SVR, then uses the SVR to extract fuzzy rules and designs fuzzy rule-based system. Simulations show that fuzzy rule-based system technique based on robust SVR achieves superior performance to the conventional fuzzy inference method, the proposed method provides satisfactory performance with excellent approximation and generalization property than the existing algorithm.

AN INCREMENTAL UPDATING ALGORITHM FOR MINING ASSOCIATION RULES

In this letter, on the basis of Frequent Pattern(FP) tree, the support function to update FP-tree is introduced, then an Incremental FP (IFP) algorithm for mining association rules is proposed. IFP algorithm considers not only adding new data into the database but also reducing old data from the database. Furthermore, it can predigest five cases to three cases.The algorithm proposed in this letter can avoid generating lots of candidate items, and it is high efficient.

The analysis of acupoint selection rules for acupuncture treating functional constipation

Objective: To analyze the prescription rule of acupuncture for functional constipation (FC), and explore the effective core clinical acupuncture prescriptions. Methods:The randomized controlled trials published in the PubMed, CNKI, Wanfang, and VIP databases were retrieved from January 1, 2010 to January 31, 2020. And the key information about acupuncture therapy for FC in these RCTs was collected according to the predetermined inclusion and exclusion criteria. Eventually, the statisticians analyzed the use frequency of single acupoints and meridian acupoints by descriptive statistical method and explored the combination rule between different acupoints by association rules. Results: Twenty six randomized controlled trials were included, with a total of 29 acupoints. Tianshu (ST25), Shangjuxu (ST37) and Zhongwan (RN12) were the top 3 frequency of acupuncture therapy for FC and the top 3 frequency meridian had been chosen were the stomach meridian of Foot-Yangming, the spleen meridian of Foot-Taiyin and Ren channel. The two acupoints with high support and compatibility frequency ranking in the top 3 are Tianshu (ST25) - Shangjuxu (ST37), Tianshu (ST25) - Zhongwan (RN12), Tianshu (ST25) - Zusanli (ST36). The three acupoints with compatibility frequency ranking in the top 2 are Tianshu (ST25) - Shangjuxu (ST37) - Zusanli (ST36), and Tianshu (ST25) - Shangjuxu (ST37) - Zhigou (SJ6). Conclusion: Tianshu (ST25) is the most common acupoint for acupuncture therapy of FC. Tianshu (ST25) and Shangjuxu (ST37) are the core acupoints to provide basis for clinical practice and future clinical research.

Studies on the impact of the evolution of Volleyball Rules upon technology and tactics

As it developed to today, Volleyball evolved from a game for the purpose of entertainment initially to a competitive Olympic sport. Through various periods of Volleyball development, we can find that when some old rules can not adapt to the volleyball development, it will lead to changes in the rules, it is this continuous improvement and change that inject vigor to volleyball and bring vitality, and promote the innovative development of volleyball skills and tactics, in turn the constant enrichment and development of volleyball skills and tactics required the game rules constantly revised and improved, as promoted and restricted each other, analysis of the mutual relationship between volleyball game rules and technology or tactics can not only in favor of volleyball skills, like evolving tactics, but also beneficial to volleyball competition rules maturity. Development of Volleyball Rules has been the inexhaustible power to development of sports project, researching of the competition rules has been recognized as a major breakthrough in the field of sports in various projects to promote sports development. Volleyball Rules - from the generated moment until today, has evolved many times. This evolution is not blind, random; it follows its inherent rule. A contest rule, which has a close relationship with the development of sports technology, are the basic norms and principles of sports game. They promote each other, while mutually restraint. Analysis of the relationship between volleyball competition rules and the technology or tactics, is not only conducive to the development of athletic skills, but also to the maturity of competition rules.

THAPE: A Tunable Hybrid Associative Predictive Engine Approach for Enhancing Rule Interpretability in Association Rule Learning for the Retail Sector

Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.

Semantic Consistency and Correctness Verification of Digital Traffic Rules

The consensus of the automotive industry and traffic management authorities is that autonomous vehicles must follow the same traffic laws as human drivers.Using formal or digital methods,natural language traffic rules can be translated into machine language and used by autonomous vehicles.In this paper,a translation flow is designed.Beyond the translation,a deeper examination is required,because the semantics of natural languages are rich and complex,and frequently contain hidden assumptions.The issue of how to ensure that digital rules are accurate and consistent with the original intent of the traffic rules they represent is both significant and unresolved.In response,we propose a method of formal verification that combines equivalence verification with model checking.Reasonable and reassuring digital traffic rules can be obtained by utilizing the proposed traffic rule digitization flow and verification method.In addition,we offer a number of simulation applications that employ digital traffic rules to assess vehicle violations.The experimental findings indicate that our digital rules utilizing metric temporal logic(MTL)can be easily incorporated into simulation platforms and autonomous driving systems(ADS).