MOGA-II for an Automotive Cooling Duct Optimization on Distributed Resources

Author(s):  
Silvia Poles ◽  
Paolo Geremia ◽  
F. Campos ◽  
S. Weston ◽  
M. Islam
2020 ◽  
Vol 41 (S1) ◽  
pp. s502-s504
Author(s):  
Taylor McIlquham ◽  
Anna Sick-Samuels ◽  
Carrie Billman ◽  
Jennifer Andonian ◽  
Melissa Dudley ◽  
...  

Background: Measles is a highly contagious virus that reemerged in 2019 with the highest number of reported cases in the United States since 1992. Beginning in March 2019, The Johns Hopkins Hospital (JHH) responded to an influx of patients with concern for measles as a result of outbreaks in Maryland and the surrounding states. We report the JHH Department of Infection Control and Hospital Epidemiology (HEIC) response to this measles outbreak using a multidisciplinary measles incident command system (ICS). Methods: The JHH HEIC and the Johns Hopkins Office of Emergency Management established the HEIC Clinical Incident Command Center and coordinated a multipronged response to the measles outbreak with partners from occupational health services, microbiology, the adult and pediatric emergency departments, marketing and communication and local and state public health departments. The multidisciplinary structure rapidly developed, approved, and disseminated tools to improve the ability of frontline providers to quickly identify, isolate, and determine testing needs for patients suspected to have measles infection and reduce the risk of secondary transmission. The tools included a triage algorithm, visitor signage, staff and patient vaccination guidance and clinics, and standard operating procedures for measles evaluation and testing. The triage algorithms were developed for phone or in-person and assessed measles exposure history, immune status, and symptoms, and provided guidance regarding isolation and the need for testing. The algorithms were distributed to frontline providers in clinics and emergency rooms across the Johns Hopkins Health System. The incident command team also distributed resources to community providers to reduce patient influx to JHH and staged an outdoor measles evaluation and testing site in the event of a case influx that would exceed emergency department resources. Results: From March 2019 through June 2019, 37 patients presented with symptoms or concern for measles. Using the ICS tools and algorithms, JHH rapidly identified, isolated, and tested 11 patients with high suspicion for measles, 4 of whom were confirmed positive. Of the other 26 patients not tested, none developed measles infection. Exposures were minimized, and there were no secondary measles transmissions among patients. Conclusions: Using the ICS and development of tools and resources to prevent measles transmission, including a patient triage algorithm, the JHH team successfully identified, isolated, and evaluated patients with high suspicion for measles while minimizing exposures and secondary transmission. These strategies may be useful to other institutions and locales in the event of an emerging or reemerging infectious disease outbreak.Funding: NoneDisclosures: Aaron Milstone reports consulting for Becton Dickinson.


Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 641
Author(s):  
Michał Jasiński

Analysis of the connection between different units that operate in the same area assures always interesting results. During this investigation, the concerned area was a virtual power plant (VPP) that operates in Poland. The main distributed resources included in the VPP are a 1.25 MW hydropower plant and an associated 0.5 MW energy storage system. The mentioned VPP was a source of synchronic, long-term, multipoint power quality (PQ) data. Then, for five related measurement points, the conclusion about the relation in point of PQ was performed using correlation analysis, the global index approach, and cluster analysis. Global indicators were applied in place of PQ parameters to reduce the amount of analyzed data and to check the correlation between phase values. For such a big dataset, the occurrence of outliers is certain, and outliers may affect the correlation results. Thus, to find and exclude them, cluster analysis (k-means algorithm, Chebyshev distance) was applied. Finally, the correlation between PQ global indicators of different measurement points was performed. It assured general information about VPP units’ relation in point of PQ. Under the investigation, both Pearson’s and Spearman’s rank correlation coefficients were considered.


2018 ◽  
Vol 54 (5) ◽  
pp. 4612-4620 ◽  
Author(s):  
Jose M. Cano ◽  
Angel Navarro-Rodriguez ◽  
Andres Suarez ◽  
Pablo Garcia

2021 ◽  
Author(s):  
Gregory Kaminski ◽  
Philip Odonkor

Abstract The decreasing cost of implementation and increasing regulatory incentive to lower energy use have led to an increased adoption of distributed energy resources in recent years. This increased adoption has been further fueled by a surge in energy consciousness and the expansion of energy-saving products and technologies. To lower reliance on the electrical grid and fully realize the benefits of distributed energy resources, many consumers have also elected to use battery systems to store generated energy. For owners of multiple buildings, or multiple owners willing to share the operational cost, building clusters may be formed to more effectively take advantage of these distributed resources and storage systems. The implementation of these systems in existing buildings introduces the question of what makes a “good” building cluster. Furthermore, the scalable nature of distributed energy sources and storage systems create countless possibilities for system configuration. Through comparison of unique two-building clusters from a stock of five buildings with a given distributed energy resource (in this case, a solar photovoltaic panel array) and energy storage system, we develop a fundamental understanding of the underlying factors that allow building clusters to be less reliant on the utility grid and make better use of energy generation and storage systems.


2013 ◽  
Vol 670 ◽  
pp. 57-64
Author(s):  
D. Wu ◽  
Q.X. Hu ◽  
Y. Yao

Facing the abundant service resources, how to make the heterogeneous distributed resources information system has the meaning that can be understand between man-machine and machines, search conveniently and implement the resources integration, achieve information access and query better as well as the interoperability between systems, it is a challenge it faces which implementing the resources sharing and intelligence services, but also a problem which to improve the service informatization level for RM industries to be solved. To facility services resource sharing in Rapid Manufacturing (RM) industry, mainly discussed demand analysis and establishment principle of RM domain ontology. Based on the many years of experience and enterprise instances, domain ontology was described conceptual and expressed knowledgeable and model structure was established. The knowledge representation method is adopted based on the domain ontology query model and partial examples of service description are given. In order to solve semantic fuzziness and realize integration, interoperability and reusability of enterprise service by building domain ontology which can satisfy shared understanding of interested parties. On this basis, integrated service system architecture was designed to support resource sharing. The methods had been applied preliminarily and would provide the basis for the future work and extended field.


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