In this paper we introduce some new methods using which importance of a variable in a Boolean function can be computed. Such methods can easily be used for computing variable order to construct BDDs. The measures of a variable's importance are based on information-theoretic criteria, and require computation of entropy of a variable, as deened by us, for a given function. We have found that entr...

The main statistics used in rough set data analysis, the approximation quality, is of limited value when there is a choice of competing models for predicting a decision variable. In keeping within the rough set philosophy of non–invasive data analysis, we present three model selection criteria, using information theoretic entropy in the spirit of the minimum description length principle. Our ma...

One of the main problems in cryptography is to give criteria to provide good comparators of cipher systems. The security of a cipher system must include the security of the algorithm, the security of the key generator and management module (see [BM94], [CM97],[Mau92a]) and the security of the cryptographic key agreement protocol (see [Mau93a],[MC94],[Mau93b],[Mau92b]). This paper gives show the...

We link the weighted maximum entropy and the optimization of the expected Fβmeasure, by viewing them in the framework of a general common multi-criteria optimization problem. As a result, each solution of the expected Fβ-measure maximization can be realized as a weighted maximum likelihood solution a well understood and behaved problem. The specific structure of maximum entropy models allows us...

in today’s competitive market, for a business firm to win higher profit among its rivals, it is of necessity to evaluate, and rank its potential customer segments to improve its customer relationship management (crm). this brings the importance of having more efficient decision making methods considering the current fast growing information era. these decisions usually involve several criteria,...

We link the weighted maximum entropy and the optimization of the expected Fβmeasure, by viewing them in the framework of a general common multi-criteria optimization problem. As a result, each solution of the expected Fβ-measure maximization can be realized as a weighted maximum likelihood solution a well understood and behaved problem. The specific structure of maximum entropy models allows us...

Criteria of measure quantifying quantum coherence, a unique property of quantum system, are proposed recently. In this paper, we first give an uncertainty-like expression relating the coherence and the entropy of quantum system. This finding allows us to discuss the relations between the entanglement and the coherence. Further, we discuss in detail the relations among the coherence, the discord...

Friction is a dissipative irreversible process; therefore, entropy is produced during frictional contact. The rate of entropy production can serve as a measure of degradation (e.g. wear). However, in many cases friction leads to self-organization at the surface. This is because the excess entropy is either driven away from the surface, or it is released at the nanoscale, while the mesoscale ent...

We introduced the concept of C-space entropy recently in [9] as a measure of knowledge of Cspace for sensor-based exploration and path planning for general robot-sensor systems. The robot plans the next sensing action to maximally reduce the expected C-space entropy, also called the Maximal expected Entropy Reduction, or MER criterion. The resulting view planning algorithms showed significant i...

Gathering the most information by picking the least amount of data is a common task in experimental design or when exploring an unknown environment in reinforcement learning and robotics. A widely used measure for quantifying the information contained in some distribution of interest is its entropy. Greedily minimizing the expected entropy is therefore a standard method for choosing samples in ...