Application Analysis of Nursing Students'Grades in Course Relevance Based on Association Rule Mining Algorithm Apriori

By analyzing the correlation between courses in students’grades,we can provide a decision-making basis for the revision of courses and syllabi,rationally optimize courses,and further improve teaching effects.With the help of IBM SPSS Modeler data mining software,this paper uses Apriori algorithm for association rule mining to conduct an in-depth analysis of the grades of nursing students in Shandong College of Traditional Chinese Medicine,and to explore the correlation between professional basic courses and professional core courses.Lastly,according to the detailed analysis of the mining results,valuable curriculum information will be found from the actual teaching data.

Precise Multi-Class Classification of Brain Tumor via Optimization Based Relevance Vector Machine

The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain tumors.The brain tumor is characterized by an anomalous proliferation of brain cells that can either be benign or malignant.Most tumors are misdiagnosed due to the variabil-ity and complexity of lesions,which reduces the survival rate in patients.Diagno-sis of brain tumors via computer vision algorithms is a challenging task.Segmentation and classification of brain tumors are currently one of the most essential surgical and pharmaceutical procedures.Traditional brain tumor identi-fication techniques require manual segmentation or handcrafted feature extraction that is error-prone and time-consuming.Hence the proposed research work is mainly focused on medical image processing,which takes Magnetic Resonance Imaging(MRI)images as input and performs preprocessing,segmentation,fea-ture extraction,feature selection,similarity measurement,and classification steps for identifying brain tumors.Initially,the medianfilter is practically applied to the input image to reduce the noise.The graph-cut segmentation technique is used to segment the tumor region.The texture feature is extracted from the output of the segmented image.The extracted feature is selected by using the Ant Colony Opti-mization(ACO)algorithm to improve the performance of the classifier.This prob-abilistic approach is used to solve computing issues.The Euclidean distance is used to calculate the degree of similarity for each extracted feature.The selected feature value is given to the Relevance Vector Machine(RVM)which is a multi-class classification technique.Finally,the tumor is classified as abnormal or nor-mal.The experimental result reveals that the proposed RVM technique gives a better accuracy range of 98.87%when compared to the traditional Support Vector Machine(SVM)technique.

High rate of clinically relevant improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis

BACKGROUND The minimal clinically important difference(MCID)is defined as the smallest meaningful change in a health domain that a patient would identify as important.Thus,an improvement that exceeds the MCID can be used to define a successful treatment for the individual patient.AIM To quantify the rate of clinical improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis.METHODS Patients were treated with the Global Unite total shoulder platform arthroplasty between March 2017 and February 2019 at Herlev and Gentofte Hospital,Denmark.The patients were evaluated preoperatively and 3 months,6 months,12 months,and 24 months postoperatively using the Western Ontario Osteoarthritis of the Shoulder index(WOOS),Oxford Shoulder Score(OSS)and Constant-Murley Score(CMS).The rate of clinically relevant improvement was defined as the proportion of patients who had an improvement 24 months postoperatively that exceeded the MCID.Based on previous literature,MCID for WOOS,OSS,and CMS were defined as 12.3,4.3,and 12.8 respectively.RESULTS Forty-nine patients with a Global Unite total shoulder platform arthroplasty were included for the final analysis.Mean age at the time of surgery was 66 years(range 49.0-79.0,SD:8.3)and 65%were women.One patient was revised within the two years follow-up.The mean improvement from the preoperative assessment to the two-year follow-up was 46.1 points[95%confidence interval(95%CI):39.7-53.3,P<0.005]for WOOS,18.2 points(95%CI:15.5-21.0,P<0.005)for OSS and 37.8 points(95%CI:31.5-44.0,P<0.005)for CMS.Two years postoperatively,41 patients(87%)had an improvement in WOOS that exceeded the MCID,45 patients(94%)had an improvement in OSS that exceeded the MCID,and 42 patients(88%)had an improvement in CMS that exceeded the MCID.CONCLUSION Based on three shoulder-specific outcome measures we find that approximately 90%of patients has a clinically relevant improvement.This is a clear message when informing patients about their prognosis.

To Split or to Unify?-A Comparative Study on Functional Equivalence Translation Theory and Relevance Translation Theory

Functional equivalence,a focus in the translation studies,has been bombarded with numerous criticisms.Meanwhile,relevance translation theory,proposed by Ernst-August Gutt,offers a united theoretical framework for translation studies.The development of the translation theories does not rely on the appearance of a brand-new theory,but on the successful connection among various theories.To split or to unify,it is a question and it will direct the further development of translation studies.Analyzing the similarities and differences between these two theories,the author are striving for a unity of them and striking a better way to approach translation studies.

A Theoretic Study on the Translation Model from Relevance Theory

Relevance Theory holds that the language communication of human beings is an ostensive-inferential process of searching for relevance.Translation as a communication across language and culture,involves a dual process of communication among the source language author,the translator and the target language readers,during which the translator infers the communicative intention of the source language author,then by assessing the cognitive environments of the target language readers,makes the optimally relevant translation so that the translation can be equivalent in relevant aspects.

The Relevance between the Ego and the Other——a Theoretical Account of Relevance in Translation

This paper focuses on the notion of relevance in translation,aiming to clarify the cognitive motivation of translation,which can serve as an account of relevance in translation.

Study on C-E Translation of Advertisements Based on Relevance Theory

The main errors in translating Chinese advertisements into English are pragmatic failures in which target-language readers fail to find the optimal relevance between the target text and source text.The translation strategies proposed under the guidance of Relevance Theory can effectively help translators find out optimal relevance in the process of translating Chinese advertisements into English to avoid pragmatic failures.

Relevance theory: the Cognitive Pragmatic Foundation of Code-switching

The paper will discuss the process of code-switching and its cognitive pragmatic motivation from the point of relevance.And code-switching is also regarded as a kind of communicative strategy.The process of the production of code-switching is also the cooperation and mutual constrain of communicator’s cognitive environment and ability.Cognitive effect can be obtained through communicator’s processing cognitive environment with their cognitive ability.In this process,the cooperation of cognitive ability and cognitive environment gives a guarantee to successful communication with code-switching.

Analysis of Iconicity Base on Relevance Theory

Iconicity as one of the very important research items of cognitive linguistics refers to the natural, non-arbitrary rela?tionship between form and meaning. The study of iconicity has great significance of revealing the relationship between concept and cognition and can help people better understand the essence of language. This paper presents an analysis of the three iconicity principles- distance iconicity,quantity iconicity and sequencing iconicity-base on the relevance theory. The purpose of this pa?per is to offer a new dimension to iconicity analysis and finding more connections between the form of language and real mean?ing.

A Study on Translation of Chinese Culture-loaded Words from the Per-spective of Relevance Theory

The essay tends to analyze the translation of Chinese Culture-loaded words from the perspective of Relevance Theory.The theory gains its prominence by studying the translation process and transcending the conflicts between literal and free translation. It incorporates recent work in cognitive linguistics, with ostensive-inference as its key model. Under the influence of Relevance theory, the translation of culture-loaded words is reader-oriented. Translators are obliged to help target readers to establish new assumptions to achieve equivalent response.

Relevance Theory and Advanced Vocational College English Listening Comprehension

This thesis draws on Sperber and Wilson’s principle of relevance to expound listening comprehension is an ostensiveinferential process based on the cognitive context in searching for optimal relevance,thus to explore a range of effective suggestions and new thoughts.

The Application of Relevance Theory to College English Reading Teaching

This paper expounds relevance theory and its principle. It also introduces the method to apply it to college English reading teachingto improve college students’ reading proficiency.

Seismic liquefaction potential assessment by using relevance vector machine

Determining the liquefaction potential of soil is important in earthquake engineering. This study proposes the use of the Relevance Vector Machine （RVM） to determine the liquefaction potential of soil by using actual cone penetration test （CPT） data. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The results are compared with a widely used artificial neural network （ANN） model. Overall, the RVM shows good performance and is proven to be more accurate than the ANN model. It also provides probabilistic output. The model provides a viable tool for earthquake engineers to assess seismic conditions for sites that are susceptible to liquefaction.

Relevance vector machine technique for the inverse scattering problem

A novel method based on the relevance vector machine（RVM） for the inverse scattering problem is presented in this paper.The nonlinearity and the ill-posedness inherent in this problem are simultaneously considered.The nonlinearity is embodied in the relation between the scattered field and the target property,which can be obtained through the RVM training process.Besides,rather than utilizing regularization,the ill-posed nature of the inversion is naturally accounted for because the RVM can produce a probabilistic output.Simulation results reveal that the proposed RVM-based approach can provide comparative performances in terms of accuracy,convergence,robustness,generalization,and improved performance in terms of sparse property in comparison with the support vector machine（SVM） based approach.

Medical implication in the Bible and its relevance to modern medicine

The Ho/y Bibe, as the root of Western civilization, has imposed great influence in the fields far beyond religion. In this thesis, the author intended to reveal the medical implication in the Ho/y Bib/e and its relevance to the modern medical science by exploring the biblical medical information and comparing it with the current medical theory and practice. The conclusion of the exploration is surprising yet inspiring： the Ho/y Bibe, as an ancient religious book, contains rich medical information around themes such as sexual relations, dietary guidelines, hygiene, etc., which is not at odds, but in harmony with the modern medicine.

Feature Selection via Analysis of Relevance and Redundancy

Feature selection is an important problem in pattern classification systems. High dimension fisher criterion（HDF） is a good indicator of class separability. However, calculating the high dimension fisher ratio is difficult. A new feature selection method, called fisher-and-correlation （FC）, is proposed. The proposed method is combining fisher criterion and correlation criterion based on the analysis of feature relevance and redundancy. The proposed methodology is tested in five different classification applications. The presented resuits confirm that FC performs as well as HDF does at much lower computational complexity.

User’s Relevance of PIR System Based on Cloud Models

A new method to evaluate fuzzily user＇s relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method for personalized information retrieval （PIR） system can efficiently judge multi-value relevance, such as quite relevant, comparatively relevant, commonly relevant, basically relevant and completely non-relevant, and realize a kind of transform of qualitative concepts and quantity and improve accuracy of relevance judgements in PIR system. Experimental data showed that the method is practical and valid. Evaluation results are more accurate and approach to the fact better.

Relevance of early intervention in Fahr's disease: understanding through a case study

SUMMARY Intracranial calcification may result from disturbances in calcium metabolism. It often remains asymptomatic, but may present with symptoms like seizure and neurological deficits. Correction of the underlying metabolic disturbance before damage of neuronal tissues due to intracranial calcification may be useful in preventing irreversible neurological deficits. This window period may be the crucial period that needs a thorough clinical evaluation and urgent intervention. We highlight the case of an adult woman with Fahr's disease presented with generalised tonic-clonic seizure. The management priorities were also discussed along with review of literature.