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Artificial intelligence plays an important role in medicine. Specially, expert systems can be designed for diagnosis of disease.Artificial intelligence can be used for diagnosis of disease. This study proposes an expert system for diagnosis of Multiple Sclerosis based on clinical symptoms and demographic characteristics. Specially, it recommends patients to refer to a specialist for further investigation.In this empirical study, some symptoms of Multiple Sclerosis are mapped to fuzzy sets. Moreover, several rules are defined for prediction of Multiple Sclerosis. The fuzzy sets and rules form the knowledge base of the expert system. Patients enter their symptoms and demographic information via a user interface and Mamdani method is used in inference engine to produce the appropriate recommendation.The precision, recall, and F-measure are used as criteria to analyze the efficiency of the expert system. The results show that the designed expert system can recommend patients for further investigation as effective as specialists. Specially, while the proposed expert system recommended referring to a doctor for some healthy users, most of the MS patients are diagnosed.The proposed expert system in this study can analyze the symptoms of patients to predict the Multiple Sclerosis disease. Therefore, it can investigate initial status of patients in a rapid and cost-effective manner. Moreover, this system can be applied in situations and places, which human experts are unavailable.

One of the principles of Web of Data is linking resources to related ones. The rdfs:seeAlso link plays an important role in interlinking datasets and web resources.W3C defines rdfs:seeAlso to provide additional information about subject resources by interlinking datasets. This definition is general and can have various interpretations and implementations. In this paper, we tackle the problem of specializing the rdfs:seeAlso link by identifying more specific definitions and patterns that can assist individuals and organization in recognizing the target web resources that provide additional information about the subject resource. We investigate this problem in information retrieval applications and specify the desired patterns by probing databases that traditionally use seeAlso in their structure and referencing system. The structure of described databases and systems are similar to the structure of Web of Data. The provided usages of seeAlso show that many of the explained patterns are common that can be applied in Web of Data. We have conducted an empirical study to analyse the comprehensiveness of several patterns in traditional web. The results show that the investigated patterns constitute a significant portion of seeAlso usages.

A new algorithm based on the least-squares method is proposed for online power system frequency estimation. The algorithm is based on a formula which holds for every three consecutive samples. Several of these formulae are written for some consecutive triples of samples and the least-squares method is applied to estimate the frequency. A revised version of the approach with less computation burden at the cost of little decline in estimation accuracy is presented. Response time and processing time of the algorithm are discussed. The effect of data window size, sampling frequency, noise, harmonic, interharmonic, exponentially decaying dc, and filtering on the performance of the approach is discussed. The approach is compared with that of a recent similar paper and a demodulation approach.

The rdfs:seeAlso predicate plays an important role in linking web resources in semantic web. Based on the W3C definition, it shows that the object resource provide additional information about the subject resource. Since providing additional information can take various forms, the definition is generic. In the other words, the rdfs:seeAlso link can present different meanings to the users and it can represents different kind of patterns and relationships between web resources. These patterns are unknown and have to be specified to help organizations, and individuals to interlink, and publish their datasets on Web of Data using the rdfs:seeAlso link. In this paper, we investigate to the traditional usages of seealso and then present a methodology to specify the patterns of rdfs:seeAlso usages in Semantic Web. The results of our investigation show that the discovered patterns constitute a significant portion of rdfs:seeAlso usages in Web of Data.