scholarly journals Accelerating data sharing, visualization and analysis to support efficient disease monitoring and more real-time decision making in the swine industry using the Disease BioPortal platform.

2019 ◽  
Vol 6 ◽  
Author(s):  
Beatriz Martínez-López ◽  
Dale Polson ◽  
Erin Lowe ◽  
Zack Whedbee ◽  
Rodger Main
2020 ◽  
Vol 50 (5) ◽  
pp. 325-339
Author(s):  
Xiaojia Guo ◽  
Yael Grushka-Cockayne ◽  
Bert De Reyck

Improving airport collaborative decision making is at the heart of airport operations centers (APOCs) recently established in several major European airports. In this paper, we describe a project commissioned by Eurocontrol, the organization in charge of the safety and seamless flow of European air traffic. The project’s goal was to examine the opportunities offered by the colocation and real-time data sharing in the APOC at London’s Heathrow airport, arguably the most advanced of its type in Europe. We developed and implemented a pilot study of a real-time data-sharing and collaborative decision-making process, selected to improve the efficiency of Heathrow’s operations. In this paper, we describe the process of how we chose the subject of the pilot, namely the improvement of transfer-passenger flows through the airport, and how we helped Heathrow move from its existing legacy system for managing passenger flows to an advanced machine learning–based approach using real-time inputs. The system, which is now in operation at Heathrow, can predict which passengers are likely to miss their connecting flights, reducing the likelihood that departures will incur delays while waiting for delayed passengers. This can be done by off-loading passengers in advance, by expediting passengers through the airport, or by modifying the departure times of aircraft in advance. By aggregating estimated passenger arrival time at various points throughout the airport, the system also improves passenger experiences at the immigration and security desks by enabling modifications to staffing levels in advance of expected surges in arrivals. The nine-stage framework we present here can support the development and implementation of other real-time, data-driven systems. To the best of our knowledge, the proposed system is the first to use machine learning to model passenger flows in an airport.


Author(s):  
Stefano Pensa ◽  
Elena Masala

Since spatial decision processes have to deal with large number of actors, opinions and interests, literature commonly agrees in recognising data sharing and communication as essential in achieving decisional tasks (Van den Brink et al., 2007; MacEachren et al., 2004). The following chapter describes a methodological instrument for managing data, namely the Interactive Visualisation Tool (InViTo). InViTo aims at supporting spatial decision-making processes by proposing a framework for data knowledge. Principally based on Grasshopper, a free plug-in for McNeel's Rhinoceros, InViTo combines GIS data with CAD drawings and raster images for generating interactive spatial visualisations. It is conceived to display in real time the relationships between the territory and planning choices; thus, it is particularly indicated for stimulating discussions and sharing information in collaborative processes. Its high flexibility allows its use in different case studies with a variety of purposes and scales. Innovative elements in approaching spatial decision processes are discussed.


Author(s):  
Shreyanshu Parhi ◽  
S. C. Srivastava

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS.  The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.


2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.


Pathogens ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 47
Author(s):  
Giovanni Franzo ◽  
Michele Drigo ◽  
Matteo Legnardi ◽  
Laura Grassi ◽  
Maria Luisa Menandro ◽  
...  

Differently from alpha- and betaherpesviruses affecting swine, interest in the recently discovered Suid gammaherpesvirus 3, Suid gammaherpesvirus 4, and Suid gammaherpesvirus 5, also known as porcine lymphotropic herpesviruses (PLHV-1, PLHV-2, and PLHV-3), has largely focused on their role as potential zoonotic agents in cases of xenotransplantation. However, their role as primary pathogens of swine or as co-factors for other lymphotropic infections has essentially been neglected. The present study aims at filling this gap, evaluating the association between PLHVs infection and different clinical conditions and/or porcine circovirus (PCV) co-infection. One hundred seventy-six samples were obtained from different animals located in a high-density pig area of Northern Italy in the period 2017–2020. The presence of PLHVs and PCVs was tested and quantified by specific real-time PCR: PLHVs were widespread among pigs (PLHV-1, PLHV-2, and PLHV-3 prevalence was 28.97%, 10.79%, and 4.54%, respectively) and detected in all considered tissues and clinical conditions. Frequent co-infections were also observed among PLHVs and with PCVs, although a significant association was not detected with the exception of a positive interaction between PLHV-1 and PLHV-3, and a negative one between PLHV-2 and PCV-2. Significantly, no association between PLHVs, alone or in co-infection, emerged with any of the considered clinical signs, their frequency being comparable between healthy and diseased animals. Based on these pieces of evidence and despite their high prevalence, PLHVs’ relevance for the swine industry appears negligible, either as primary pathogens or as predisposing factors for circovirus-induced diseases.


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