background and objective: magnetic resonance imaging (mri) is the most sensitive technique to detect multiple sclerosis (ms) plaques in central nervous system. in some cases, the patients who were suspected to ms, whereas mri images are normal, but whether patients don’t have ms plaques or mri images are not enough optimized enough in order to show ms plaques? the aim of the current study is ev...

We present Regular-SAT, an extension of Boolean Satisfiability based on a class of many-valued CNF formulas. Regular-SAT shares many properties with Boolean SAT, which allows us to generalize some of the best known SAT results and apply them to Regular-SAT. In addition, Regular-SAT has a number of advantages over Boolean SAT. Most importantly, it produces more compact encodings that capture pro...

In this paper, we propose a new approach, called lemma-reusing, for accelerating SAT based planning and scheduling. Generally, SAT based approaches generate a sequence of SAT problems which become larger and larger. A SAT solver needs to solve the problems until it encounters a satisfiable SAT problem. Many state-of-the-art SAT solvers learn lemmas called conflict clauses to prune redundant sea...

abstract geosystems or geomorphic systems include terrain structure with processes interactions that work as alone or common and create a series of terrain unites. geosystem elements consist of lines, points, surfaces, and volumes. the ways of relationships between the elements form spatial structure identity. the elements prepare spaces for different land uses, when they are located in ratio t...

We present Regular-SAT, an extension of Boolean Satisfiability based on a class of many-valued CNF formulas. Regular-SAT shares many properties with Boolean SAT, which allows us to generalize some of the best known SAT results and apply them to Regular-SAT. In addition, Regular-SAT has a number of advantages over Boolean SAT. Most importantly, it produces more compact encodings that capture pro...

We present a new type of sat problem called the k-gd-sat, which generalizes k-sat and gd-sat. In k-gd-sat, clause lengths have geometric distribution, controlled by a probability parameter p; for p = 1, a k-gd-sat problem is a k-sat problem. We report on the phase transition between satisfiability and unsatisfiability for randomly generated instances of k-gd-sat. We provide theoretical analysis...

Based on the China Meteorological Administration Land Data Assimilation System (CLDAS) reanalysis data and 12–72 h forecasts of surface (2-m) air temperature (SAT) from European Centre for Medium-Range Weather Forecasts (ECMWF) three numerical weather prediction (NWP) models (CMA-GFS, CMA-SH, CMA-MESO), multi-model ensemble are conducted with a convolutional neural network (CNN) feed-forward (F...

We show that there exists a natural encoding which transforms Min-SAT instances into Max-SAT instances. Unlike previous encodings, this natural encoding keeps the same variables, and the optimal assignment for the Min-SAT instance is identical to the optimal assignment of the corresponding Max-SAT instance. In addition to that the encoding can be generalized to the Min-SAT variants with clause ...

One of the most studied models SAT is random SAT. In this model, instances are composed from clauses chosen uniformly randomly and independently each other. This model may be unsatisfactory in that it fails to describe various features instances, arising real-world applications. Various modifications have been suggested define industrial Here, we focus mainly on aspect community structure. Name...