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Apriori_Goal algorithm for constructing association rules for a database with a given classification

arXiv.org Artificial Intelligence

An efficient algorithm, Apriori_Goal, is proposed for constructing association rules for a relational database with a given classification. The algorithm's features are related to the specifics of the database and the method of encoding its records. The algorithm proposes five criteria that characterize the quality of the rules being constructed. Different criteria are also proposed for filtering the sets used when constructing association rules. The proposed method of encoding records allows for an efficient implementation of the basic operation underlying the computation of rule characteristics. The algorithm works with a relational database, where the columns can be of different types, both continuous and discrete. Among the columns, a target discrete column is distinguished, which defines the classification of the records. This allows the original database to be divided into $n$ subsets according to the number of categories of the target parameter. A classical example of such databases is medical databases, where the target parameter is the diagnosis established by doctors. A preprocessor, which is an important part of the algorithm, converts the properties of the objects represented by the columns of the original database into binary properties and encodes each record as a single integer. In addition to saving memory, the proposed format allows the complete preservation of information about the binary properties representing the original record. More importantly, the computationally intensive operations on records, required for calculating rule characteristics, are performed almost instantly in this format using a pair of logical operations on integers.


Ukrainian drone attack sparks massive blast at arsenal in Russia

Al Jazeera

A Ukrainian drone attack targeting an armoury has caused a giant fireball, leading to a partial evacuation in western Russia. The attack, reported early on Wednesday, targeted a large arsenal close to the town of Toropets, some 400km (250 miles) northwest of Moscow in the Tver region. It illustrates Ukraine's continued effort to show it can strike at targets deep inside Russia. The drone attack caused an "extremely powerful detonation" and destroyed a large warehouse of the Main Missile and Artillery Directorate of the Russian Ministry of Defence and sparked a fire 6km (3.7 miles) wide, an unnamed source from the Ukrainian security services said. "The warehouse contained missiles intended for Iskander tactical missile systems, Tochka-U tactical missile systems, guided aerial bombs and artillery ammunition," the source told news wires.


Current Trends and Applications of Dempster-Shafer Theory (Review)

arXiv.org Artificial Intelligence

The article provides a review of the publications on the current trends and developments in Dempster-Shafer theory and its different applications in science, engineering, and technologies. The review took account of the following provisions with a focus on some specific aspects of the theory. Firstly, the article considers the research directions whose results are known not only in scientific and academic community but understood by a wide circle of potential designers and developers of advanced engineering solutions and technologies. Secondly, the article shows the theory applications in some important areas of human activity such as manufacturing systems, diagnostics of technological processes, materials and products, building and construction, product quality control, economic and social systems. The particular attention is paid to the current state of research in the domains under consideration and, thus, the papers published, as a rule, in recent years and presenting the achievements of modern research on Dempster-Shafer theory and its application are selected and analyzed.