Traumatic brain injury and intracranial hypertension often require treatment to optimize patient outcome. There are a variety of complex medical conditions that can preclude standard approaches to the treatment of intracranial hypertension. We describe a case where a novel approach using continuous dialysis with trisodium citrate was used to optimize the outcome of a young male with acute renal...

How does a boundedly rational optimizing agent make decisions? Can such an agent learn to behave rationally? We address these questions in a standard regulator environment. Our behavioral primitive is anchored to the shadow price of the state vector. The regulator forecasts the value of an additional unit of the state tomorrow, and uses this forecast to choose her control. The value of the cont...

B ulk petrochemical manufacturing is a highly competitive global industry. When margins are tight, manufacturers seek ways to optimize performance and to reduce costs while maximizing yields and revenue. Optimization options include alternative feeds, plant/process revamps and improved operations to achieve better separation and yields to lower energy consumption, to minimize product loss and t...

This paper proposes using the genetic algorithms to optimize the PI regulator parameter in the prime mover simulation system. In this paper, we compared the step response characteristics under the conditions of the genetic algorithms and traditional method by MATLAB simulation and field test tested the dynamic characteristics of the prime mover simulation system. The results proved that genetic...

Many real-world analytics problems involve two significant challenges: prediction and optimization. Because of the typically complex nature each challenge, standard paradigm is predict-then-optimize. By large, machine learning tools are intended to minimize error do not account for how predictions will be used in downstream optimization problem. In contrast, we propose a new very general framew...

While the mass of refrigerant contained in a vapor compression cycle has a significant effect on the cycle’s power consumption, conventional cycle architectures cannot optimize energy efficiency by varying the mass as ambient conditions and operational requirements change. This paper proposes a new system architecture that allows the refrigerant mass circulating in the system to be modulated ov...

Response surface methodology (RSM) using a central composite design (CCD) was employed to optimize the conditions for extraction of antioxidants from black soybean (Glycine max var) sprouts. Three influencing factors: liquid-solid ratio, period of ultrasonic assisted extraction and extraction temperature were investigated in the ultrasonic aqueous extraction. Then Response Surface Methodology (...