<span>The energy efficiency in the debutanizer reboiler combustion can be monitored from oxygen content of flue gas reboiler. The measurement conducted situ using an sensor. However, soot that may appear around sensor due to process obstruct sensor’s function. In-situ redundancy sensors’ unavailability is a significant problem when damaged, so measures must made directly by workers portab...

Evaluating the expectation of a quantum circuit is classically difficult problem known as mean value (QMV). It used to optimize approximate optimization algorithm and other variational eigensolvers. We show that such an can be improved substantially by using approximation rather than exact expectation. Together with efficient classical sampling algorithms, minimal gate count thus improve effici...

The field of Reinforcement Learning (RL) in machine learning relates significantly to the domains of classical and instrumental conditioning in psychology, which give an understanding of biology’s approach to RL. In recent years, there has been a thrust to correlate some machine learning RL algorithms with brain structure and function, a benefit to both fields. Our focus has been on one such st...

Approximate arithmetic circuits are an attractive alternative to accurate because they have significantly reduced delay, area, and power, albeit at the cost of some loss in accuracy. By keeping errors due approximate computation within acceptable limits, can be used for various practical applications such as digital signal processing, filtering, low power graphics neuromorphic computing, hardwa...

This paper presents a novel approach to the design of an adaptive fuzzy sliding mode controller for depth control of an autonomous underwater vehicle (AUV). So far, AUV’s dynamics are highly nonlinear and the hydrodynamic coefficients of the vehicles are difficult to estimate, because of the variations of these coefficients with different operating conditions. These kinds of difficulties cause ...

The design and analysis of fault diagnosis architectures using the model-based analytical redundancy approach has received considerable attention during the last two decades. One of the key issues in the design of such fault diagnosis schemes is the eeect of modeling uncertainties on their performance. This paper describes a fault diagnosis algorithm for a class of nonlinear dynamic systems wit...

This paper focuses on visualizing densities. We first give a small generalization of kernel density estimators which is appropriate for smoothing general point masses including statistical data, but also more general data forms. We give a heuristic discussion to show that our smoother has some desirable approximation properties. We also show that for this class of kernel smoother the 12or 3-dim...

Our approach to this problem was to use reinforcement learning with a function approximator to approximate the state value function [RSS98]. In our case, a +1 reward was given for every completed line, so that the value function would encode the long-term number of lines that is going to be completed by the algorithm. In order to achieve this, we extract features from the game state, and use gr...