We prove that adding upwards closed first-order dependency atoms to first-order logic with team semantics does not increase its expressive power (with respect to sentences), and that the same remains true if we also add constancy atoms. As a consequence, the negations of functional dependence, conditional independence, inclusion and exclusion atoms can all be added to first-order logic without ...

Recently, resolving the problem of evaluation and ranking the potential suppliers has become as a key strategic factor for business firms. With the development of intelligent and automated information systems in the information era, the need for more efficient decision making methods is growing. The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with confl...

In this paper, firstly, a new intuitionistic fuzzy (IF) entropy has been put forward, which considered both the uncertainty and the hesitancy degree of IF sets. Through comparing with other entropy measures, the advantage of the new entropy measure is obvious. Secondly, based on the new entropy measure, a new decision making method of a multi-attribute decision making problem was subsequently p...

In the grapheme to phoneme conversion problem for Korean, two main approaches have been discussed: knowledge-based and data-driven methods. However, both camps have limitations: the knowledge-based hand-written rules cannot handle some of the pronunciation changes due to the lack of capability of linguistic analyzers and many exceptions; data-driven methods always suffer from data sparseness. T...

In this paper we examine an Information-Theoretic method for solving noisy linear inverse estimation problems which encompasses under a single framework a whole class of estimation methods. Under this framework, the prior information about the unknown parameters (when such information exists), and constraints on the parameters can be incorporated in the statement of the problem. The method buil...

Combining logic with probabilities is a core idea to uncertain reasoning. Recently, approaches to probabilistic conditional logics based on first-order languages have been proposed that employ the principle of maximum entropy (ME), e.g. the logic FO-PCL. In order to simplify the ME model computation, FO-PCL knowledge bases can be transformed so that they become parametrically uniform. On the ot...

Soft computing is likely to play aprogressively important role in many applications including image enhancement. The paradigm for soft computing is the human mind. The soft computing critique has been particularly strong with fuzzy logic. The fuzzy logic is facts representationas a rule for management of uncertainty. Inthis paperthe Multi-Dimensional optimized problem is addressed by discussing...

A central question for knowledge representation is how to encode and handle uncertain knowledge adequately. We introduce the probabilistic description logic ALCP that is designed for representing context-dependent knowledge, where the actual context taking place is uncertain. ALCP allows the expression of logical dependencies on the domain and probabilistic dependencies on the possible contexts...

We classify all path-delay faults of a combinational circuit into three categories: singly-testable (ST), multiply-testable (MT), and singly-testable dependent (ST-dependent). The classification uses any unaltered single stuck-at fault test generation tool. Only two runs of this tool on a model network derived from the original network are performed. As a by-product of this process, we generate...

Non-performing asset (NPA) has been in a serious attention by banks over the past few years. NPA causes huge loss to banks; hence, it becomes an extremely critical step deciding which loans have capabilities become NPA, and thereby grant ones reject. In this paper, focuses on exact crux of matter, algorithm is proposed designed handle financial data very meticulously predict with high accuracy ...