scholarly journals Reaching a consensus on access detection by a decision system

2014 ◽  
Author(s):  
Cesar Guevara ◽  
Matilde Santos ◽  
Jose Antonio Martin ◽  
Victoria Lopez
Keyword(s):  
Decision System

Training Impact Decision System for Air Force Career Fields: Tides Operational Guide

1995 ◽  
Author(s):  
Robert L. Gosc ◽  
J. L. Mitchell ◽  
J. R. Knight ◽  
Brice M. Stone ◽  
Frederick H. Reuter ◽  
...  
Keyword(s):  
Air Force ◽  
Decision System ◽  
Training Impact

Fuzzy Self-Adaptive Soccer Robot Behavior Decision System Design through ROS

2018 ◽  
Vol 62 (3) ◽  
pp. 304011-3040111 ◽  
Author(s):  
Shih-An Li ◽  
Hsuan-Ming Feng ◽  
Sheng-Po Huang ◽  
Chen-You Chu
Keyword(s):  
System Design ◽  
Soccer Robot ◽  
Decision System ◽  
Robot Behavior ◽  
Self Adaptive

A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control

2018 ◽  
Vol 6 (6) ◽  
pp. 98
Author(s):  
Shreyanshu Parhi ◽  
S. C. Srivastava
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Manufacturing Industry ◽  
Simulation Software ◽  
Shop Floor ◽  
Simulation Tool ◽  
Routing Flexibility ◽  
Decision System ◽  
Multi Objective ◽  
Arena Simulation

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.

scholarly journals Design and Implementation of a Hydroponic Strawberry Monitoring and Harvesting Timing Information Supporting System Based on Nano AI-Cloud and IoT-Edge

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1400
Author(s):  
Sun Park ◽  
JongWon Kim
Keyword(s):  
South Korea ◽  
Monitoring System ◽  
Learning Algorithm ◽  
Great Influence ◽  
Integrated System ◽  
Environmental Data ◽  
Decision System ◽  
Horticultural Crops ◽  
Deep Learning Algorithm ◽  
Growing Environment

The strawberry market in South Korea is actually the largest market among horticultural crops. Strawberry cultivation in South Korea changed from field cultivation to facility cultivation in order to increase production. However, the decrease in production manpower due to aging is increasing the demand for the automation of strawberry cultivation. Predicting the harvest of strawberries is an important research topic, as strawberry production requires the most manpower for harvest. In addition, the growing environment has a great influence on strawberry production as hydroponic cultivation of strawberries is increasing. In this paper, we design and implement an integrated system that monitors strawberry hydroponic environmental data and determines when to harvest with the concept of IoT-Edge-AI-Cloud. The proposed monitoring system collects, stores and visualizes strawberry growing environment data. The proposed harvest decision system classifies the strawberry maturity level in images using a deep learning algorithm. The monitoring and analysis results are visualized in an integrated interface, which provides a variety of basic data for strawberry cultivation. Even if the strawberry cultivation area increases, the proposed system can be easily expanded and flexibly based on a virtualized container with the concept of IoT-Edge-AI-Cloud. The monitoring system was verified by monitoring a hydroponic strawberry environment for 4 months. In addition, the harvest decision system was verified using strawberry pictures acquired from Smart Berry Farm.

scholarly journals Healthcare pathways and resource use: mapping consequences of ambulance assessment for direct care with alternative healthcare providers

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Sofi Varg ◽  
Veronica Vicente ◽  
Maaret Castren ◽  
Peter Lindgren ◽  
Clas Rehnberg
Keyword(s):  
Emergency Department ◽  
Acute Care ◽  
Resource Use ◽  
Healthcare Providers ◽  
Healthcare Utilisation ◽  
Direct Care ◽  
Care Centre ◽  
Decision System ◽  
Geriatric Ward ◽  
Patient Pathways

Abstract Background A decision system in the ambulance allowing alternative pathways to alternate healthcare providers has been developed for older patients in Stockholm, Sweden. However, subsequent healthcare resource use resulting from these pathways has not yet been addressed. The aim of this study was therefore to describe patient pathways, healthcare utilisation and costs following ambulance transportation to alternative healthcare providers. Methods The design of this study was descriptive and observational. Data from a previous RCT, where a decision system in the ambulance enabled alternative healthcare pathways to alternate healthcare providers were linked to register data. The receiving providers were: primary acute care centre or secondary geriatric ward, both located at the same community hospital, or the conventional pathway to the emergency department at an acute hospital. Resource use over 10 days, subsequent to assessment with the decision system, was mapped in terms of healthcare pathways, utilisation and costs for the 98 included cases. Results Almost 90% were transported to the acute care centre or geriatric ward. The vast majority arriving to the geriatric ward stayed there until the end of follow-up or until discharged, whereas patients conveyed to the acute care centre to a large extent were admitted to hospital. The median patient had 6 hospital days, 2 outpatient visits and costed roughly 4000 euros over the 10-day period. Arrival destination geriatric ward indicated the longest hospital stay and the emergency department the shortest. However, the cost for the 10-day period was lower for cases arriving to the geriatric ward than for those arriving to the emergency department. Conclusions The findings support the appropriateness of admittance directly to secondary geriatric care for older adults. However, patients conveyed to the acute care centre ought to be studied in more detail with regards to appropriate level of care.

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