Joint Operation Optimization of the Interdependent Water and Electricity Networks
Mohannad Alhazmi – Payman Dehghanian – Mostafa Nazemi
George Washington University
Massimo Mitolo
The Irvine Valley College
Abstract: With the rapid deployment of smart technologies and the growing complexity in our modern society, there is a huge demand for coordination in day-to-day operation of the critical infrastructure networks. The coordination between water and electricity networks particularly stands out and is urgently demanding as (i) water system is one of the most energy-intensive critical infrastructure, and (ii) water unavailability, if experienced, swiftly translates into a health, safety, and national security concern. This paper proposes a comprehensive day-ahead optimization framework for joint operation of the interdependent power and water systems. Different from the conventional paradigms where the power and water systems are independently and individually operated by their respective operators, the proposed optimization framework integrates the Optimal Power Flow (OPF) models in power grids with innovative models of the water distribution systems. The nonlinear hydraulic operating constraints in the proposed optimization models are linearized, resulting into a mixed-integer linear programming (MILP) model formulation. The proposed framework is applied to three 15-node water distribution systems, operated within the IEEE 9-bus test system. The simulation results demonstrate a significant cost saving that will be achieved when the proposed approach is applied for joint operation of power and water networks.
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Intelligent Fashion Recommender System: Fuzzy Logic in Personalized Garment Design
L. C. Wang – X. Y. Zeng – L. Koehl – Y. Chen
Ecole Nationale Supérieure des Arts et Industries Textiles
Abstract. This paper proposes a new intelligent fashion recommender system to select the most relevant garment design scheme for a specific consumer in order to deliver new personalized garment products. This system integrates emotional fashion themes and human perception on personalized body shapes and professional designers’ knowledge. The corresponding perceptual data are systematically collected from professional using sensory evaluation techniques. The perceptual data of consumers and designers are formalized mathematically using fuzzy sets and fuzzy relations. The complex relation between human body measurements and basic sensory descriptors, provided by designers, is modeled using fuzzy decision trees. The fuzzy decision trees constitute an empirical model based on learning data measured and evaluated on a set of representative samples.
The complex relation between basic sensory descriptors and fashion themes, given by consumers, is modeled using fuzzy cognitive maps. The combination of the two models can provide more complete information to the fashion recommender system, making it possible to evaluate if a specific body shape is relevant to a desired emotional fashion theme and which garment design scheme can improve the image of the body shape. The proposed system has been validated in a customized design and mass market selection through the evaluations of target consumers and fashion experts using a method frequently used in marketing study.
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“And though all the winds of doctrine were let loose to play upon the earth,, so Truth be in the field, we do injuriously, by licensing and prohibiting, to misdoubt her strength. Let her and Falsehood grapple; who ever knew Truth put to the worse in a free and open encounter?” — “Areopagitica” 1644 John Milton
“The university is a home of the human spirit,
and when it is ruled by bureaucracy and mediocrity,
the spirit is killed.”
— Roger Scruton
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