İlhami Muharrem Orak

Artificial neural network application for modeling the rail rolling process

Rail rolling process is one of the most complicated hot rolling processes. Evaluating the effects of parametric values on this complex process is only possible through modeling. In this study, the production parameters of different types of rails in the rail rolling processes were modeled with an artificial neural network (ANN), and it was aimed to obtain optimum parameter values for a different type of rail. For this purpose, the data from the Rail and Profile Rolling Mill in Kardemir Iron & Steel Works Co. (Karabuk, Turkey) were used. BD1, BD2, and Tandem are three main parts of the rolling mill, and in order to obtain the force values of the 49kg/m rail in each pass for the BD1 and BD2 sections, the force and torque values for the Tandem section, parameter values of 60, 54, 46, and 33kg/m type rails were used. Comparing the results obtained from the ANN model and the actual field data demonstrated that force and torque values were obtained with acceptable error rates. The results of the present study demonstrated that ANN is an effective and reliable method to acquire data required for producing a new rail, and concerning the rail production process, it provides a productive way for accurate and fast decision making.

A Review on Semantic Text and Multimedia Retrieval and Recent Trends

Semantic web works on producing machine readable data and aims to deal with large amount of data. The most important tool to access the data which exist in web is the search engine. Traditional search engines are insufficient in the face of the amount of data that consists in the existing web pages. Semantic search engines are extensions to traditional engines and overcome the difficulties faced by them. This paper summarizes semantic web, concept of traditional and semantic search engines and infrastructure. Also semantic search approaches are detailed. A summary of the literature is provided by touching on the trends. In this respect, type of applications and the areas worked for are considered. Based on the data for two different years, trend on these points are analyzed and impacts of changes are discussed. It shows that evaluation on the semantic web continues and new applications and areas are also emerging. Multimedia retrieval is a newly scope of semantic. Hence, multimedia retrieval approaches are discussed. Text and multimedia retrieval is analyzed within semantic search.

A Review on Semantic Web and Recent Trends in Its Applications

Semantic web works on producing machine readable data. So semantic web aims to overcome the amount of data that is consisted. The most important tool to access the data which exist in web is the search engine. Traditional search engines are insufficient in the face of the amount of data that is consisted as a result of the existing pages on the web. Semantic search engines are extensions to traditional search engines and improved version. This paper summarizes semantic web, traditional and semantic search engine concepts and infrastructure. Also semantic search approaches and differences from traditional approach are detailed. A summary of the literature is provided by touching on the trends on this area. In this respect, type of applications and the areas worked for are considered. Based on the data for two different years, trend on these points are analyzed and impacts of changes are discussed. It shows that evaluation on the semantic web continues and new applications and areas are also emerging.

Semantic querying on multimedia data

Effective information retrieval is not provided with manual multimedia processing methods against huge amount of multimedia data which is produced in nowadays. Even automatic annotation generation methods are hard to address, they only operate on image processing step. Ultimately, it does not mean having a system that retrieve, relate and interpret the retrieved data. This study is done for filling the gap that is mentioned. In the study, inquiry is done by use of semantic web infrastructure on the produced, processed data of multimedia which is a source of ontologies. It is aimed to build a framework to introduce meaning on result data with semantic search. In this manner, it will be possible to access the knowledge effectively on multimedia datasets.