Human thought, perception, reasoning, and problem solving are highly dependent on causal inferences. This paper presents a set of cognitive models for causation analyses and causal inferences. The taxonomy and mathematical models of causations are created. The framework and properties of causal inferences are elaborated. Methodologies for uncertain causal inferences are discussed. The theoretic...

Character Recognition (CR) has been studied from the past several decades, and is still a demanding research topic in the field of pattern recognition and image processing. There is a large demand for Optical Character Recognition on hand written documents. Now days, the rapidly growing computational power enables the implementation of the present Character Recognition methodologies and creates...

When simulating a physical system with discrete sates, one often would like to generate a sample from the stationary distribution of a Markov chain. This report focuses on three sampling methodologies which do not rely on explicitly computing the stationary distribution. Two of these lead to algorithms which can generate an exact sample in nite time. The third yields a sample whose distribution...

Heterogeneous network-based distributed and parallel computing is gaining increasing acceptance as an alternative or complementary paradigm to multiprocessor-based parallel processing as well as to conventional supercomputing. While algorithmic and programming aspects of heterogeneous concurrent computing are similar to their parallel processing counterparts, system issues, partitioning and sch...

Content-based image retrieval has become one of the most active research areas in the past few years. In this paper various methodologies used in the research area of Content Based Image Retrieval methods using Soft Computing techniques are discussed. The comparison and analysis of various soft computing techniques like Fuzzy Logic (FL), Artificial Neural Network (ANN), Genetic Algorithm (GA) a...

With the rapid development of network technology in recent years, more and more innovative computing models and related applications appear, such as mobile device based cloud computing, social network, intelligent manufacturing and e‐business, et al. Under these situations, massive data will be generated, stored and processed under various circumstances and different requirement. In order to ef...

Soft computing (SC) is an association of computing methodologies that includes as its principal members fuzzy logic, neurocomputing, evolutionary computing and probabilistic computing. We present a collection of methods and tools that can be used to perform diagnostics, estimation, and control. These tools are a great match for real-world applications that are characterized by imprecise, uncert...

Cognitive Computing (CC) is an emerging paradigm of intelligent computing theories and technologies based on cognitive informatics, which implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. The development of Cognitive Computers (cC) is centric in cognitive computing methodologies. A cC is an intelligent computer for knowledge pr...

This paper presents three new methodologies for the basic operations, which aim at finding new ways of computing union (maximum) and intersection (minimum) membership values by taking into effect the entire membership values in a fuzzy set. The new methodologies are conceptually simple and easy from the application point of view and are illustrated with a variety of problems such as Cartesian p...

Trust management in pervasive computing environments is one of top research areas for quite some years. Although first efforts started in the mid-nineties, the real momentum came some twelve years ago. From that time such methodologies started to appear that were addressing the core of trust phenomenon. Among those naïve Bayesian statistics based methodologies should be mentioned first, then De...