Chemical process optimization and control are affected by (1) plant-model mismatch, (2) disturbances, (3) constraints for safe operation. Reinforcement learning policy would be a natural way to solve this due its ability address stochasticity, directly account the effect of future uncertainty feedback in proper closed-loop manner; all without need an inner loop. One main reasons why reinforceme...

Since many real-world problems can be designed as optimization problems, heuristic algorithms are increasingly preferred by researchers. The Arithmetic Optimization Algorithm (AOA) is a newly developed algorithm. It uses four arithmetic operations in its structure. addition and subtraction operators enhanced the AOA's local search capability, while multiplication division global capability. has...

The paper presents a study in which participants learned computer literacy by having a spoken conversation with AutoTutor, an intelligent tutoring system with conversational dialogue. Thirty students completed a multiple-choice pre-test, a 35-minute training session, and a multiple-choice post-test. After completing the post-test, students reviewed their tutorial interaction and judged what emo...

This paper focuses on the creation of word-lists for making diphone recordings for speech synthesis. Such lists often consist of nonsense words, which has the advantage that the phonetic environment can be constrained, and it is easy to produce lists containing all possible combinations. However, this approach has the disadvantage that non-experts may find it difficult to read the nonsense-word...

where f̂k = ∫ π −π f(θ)e −ikθ dθ, k ∈ Z, are the Fourier coefficients of f . Further, we assume that g ∈ C(∂D) with g > 0, that K ⊂ ∂D is closed and has positive measure (in practice, K will be an interval or a collection of intervals on ∂D), and that φ ∈ C(K) with |φ| ≤ g on K. Finally, we assume that g, φ and K are symmetric, i.e., φ(e) = φ(e−iθ), g(e) = g(e), and K = K. Under these assumption...

Constrained optimization via the Genetic Algorithm (GA) is often a challenging endeavor, as the GA is most directly suited to unconstrained optimization. Traditionally, external penalty functions have been used to convert a constrained optimization problem into an unconstrained problem for GA-based optimization. This approach requires the somewhat arbitrary selection of penalty draw-down coeffi...