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.
CLICK HERE to order complete paper
Here is a general description of what you might find in the Colorado State University Jewish community:
To get the most accurate and up-to-date information about the Colorado State University Jewish community, I recommend visiting the university’s website or contacting the relevant student organizations and offices on campus. Additionally, you can connect with current students or alumni who are part of the Jewish community at CSU to gain insights into their experiences and activities.
This content is accessible to paid subscribers. To view it please enter your password below or send mike@standardsmichigan.com a request for subscription details.
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.
CLICK HERE to order complete paper
Drivers and Barriers to Implementation of Connected, Automated, Shared, and Electric Vehicles
Abstract: Several converging trends appear to reshape the way citizens and goods move about. These trends are social, including urbanization and population growth, and technological, such as increased automation and connectivity. All these factors influence the market for connected, automated, shared and electric (CASE) vehicles, which presents many opportunities and challenges. The pace of the shift to a profoundly penetrated market for CASE vehicles is far from secure. Such transformation depends on the development of technologies, consumer attitudes, and policies. An expanding body of research has investigated the potential social and behavioral results of deploying CASE vehicles. However, most academic literature to date concentrates on technological issues linked to these vehicles.
There are several teams from federal and state agencies, OEMs, academia, startups, and consortiums working on this complex subject. This study investigates several academic papers, as well as federal and industry reports, considering all the stakeholders mentioned above. Its aim is to present a comprehensive picture of the implementation barriers and drivers of CASE vehicle usage and provide suggestions to solve them. The findings confirm that several issues are currently affecting the implementation of CASE vehicles on the road. Although there have been significant partnerships and collaborations between CASE vehicle stakeholders, namely technology companies, federal-state agencies, and academic scholars, considerable work is still required to solve the remaining barriers facing CASE-related technologies. This would enable decision-makers to create effective policies for future transportation networks and increase the speed of CASE vehicle market penetration to enhance road network’s level of service.
New update alert! The 2022 update to the Trademark Assignment Dataset is now available online. Find 1.29 million trademark assignments, involving 2.28 million unique trademark properties issued by the USPTO between March 1952 and January 2023: https://t.co/njrDAbSpwB pic.twitter.com/GkAXrHoQ9T
— USPTO (@uspto) July 13, 2023
Standards Michigan Group, LLC
2723 South State Street | Suite 150
Ann Arbor, MI 48104 USA
888-746-3670