Integrated semantic similarity model based on ontology

To solve the problem of the inadequacy of semantic processing in the intelligent question answering system. an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and informarion content is presented in this paper. With the help of interrelationship between concepts, the information content ofconcepts and the strength of the edges in the ontology network. we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user‘s question and answers in knowlegdge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is vety satisfied.     

The refinement algorithm consideration in text clustering scheme based on multilevel graph

To construct a high efficient text clustering algorithm, the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed, The model is applied to text clustering. The performance of clustering algorithm has to be improved with the refinement algorithm application, The experiment result demonstrated that the muhilevel graph text clustering algorithm is available,     

A components library system model and the support tool

Component-based development needs a well-designed components library and a set of support tools. This paper presents the design and implementation of a components library system model and its support tool UMLCASE. A set of practical CASE tools is constructed. UMLCASE can use UML to design Use Case Diagram. Class Diagram etc. And it integrates with components library system.     

A new self-adapting admission control algorithm for differential service in Web clusters

A new admission control algorithm considering the network self-similar access characteristics is proposed. Taking advantage of the mathematical model of the network traffic admission control which can effectively overcome the self-similar characteristics of tile network requests, through the scheduling of the differential service queue based on priority while at the same time taking into account various factors including access characteristics of requests, load information, etc. smoothness of the admission control is ensured by the algorlthm proposed in this paper. We design a non-linear self-adapting control algorithm by introducing an exponential admission function, thus overcomes the negative aspects introduced by static threshold parameters. Simulation results show that the scheme proposed in this paper can effectively improve the resource utilization of the clusters, while at the same time protecting the service with high priority. Our simulation resuhs also show that this algorithm can improve system stability and reliability too.     

An improved double-threshold method based on gradient histogram

This paper analyzes the characteristics of the output gradient histogram and shortages of several traditional automatic threshold methods in order to segment the gradient image better. Then an improved double-threshold method is proposed, which is combined with the method of maximum classes variance, estimatingarea method and double-threshold method. This method can automatically select two different thresholds to segment gradient images. The computer simulation is performed on the traditional methods and this algorithm and proves that this method can get satisfying result.     

Decision cost feature weighting and its application in intrusion detection

This paper introduces the cost sensitive feature weighting strategy and its application in intrusion detection. Cost factors and cost matrix are proposed to demonstrate the misclassification cost for IDS. How to get the whole minimal risk. is mainly discussed in this paper in detail. From experiments, it shows that although decision cost based weight learning exists somewhat attack miselassifieation, it can achieve relatively low misclassification costs on the basis of keeping relatively high rate of recognition precision.     

Early association of electrocardiogram alteration with infarct size and cardiac function after myocardial infarction

OBJECTIVE: Myocardial infarction (MI) is the main cause of heart failure, but the relationship between the extent of MI and cardiac function has not been clearly determined. The present study was undertaken to investigate early changes in the electrocardiogram associated with infarct size and cardiac function after MI. METHODS: MI was induced by ligating the left anterior descending coronary artery in rats. Electrocardiograms, echocardiographs and hemodynamic parameters were assessed and myocardial infarct size was measured from mid-transverse sections stained with Masson's trichrome. RESULTS: The sum of pathological Q wave amplitudes was strongly correlated with myocardial infarct size (r = 0.920, P < 0.0001), left ventricular ejection fraction (r = -0.868, P < 0.0001) and left ventricular end diastolic pressure (r = 0.835, P < 0.0004). Furthermore, there was close relationship between MI size and cardiac function as assessed by left ventricular ejection fraction (r = -0.913, P < 0.0001) and left ventricular end diastolic pressure (r = 0.893, P < 0.0001). CONCLUSION: The sum of pathological Q wave amplitudes after MI can be used to estimate the extent of MI as well as cardiac function.