Experimental Testing of the Complex Method for Increasing Decision-Making Reliability by Electro-Optical Device for Fire Detection on Background of Dynamic Optical Interferences

2021 ◽  
Author(s):  
Nadezhda Tupikina ◽  
Andrey Kin ◽  
Sergey Lisakov ◽  
Eugene Sypin
Keyword(s):  
Decision Making ◽  
Experimental Testing ◽  
Fire Detection ◽  
Complex Method ◽  
Optical Device

scholarly journals Fire Risk Assessment in Healthcare Settings: Application of FMEA Combined with Multi‐Criteria Decision Making Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fateme Omidvari ◽  
Mehdi Jahangiri ◽  
Reza Mehryar ◽  
Moslem Alimohammadlou ◽  
Mojtaba Kamalinia
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Fire Risk ◽  
Fire Detection ◽  
Healthcare Setting ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Healthcare Settings ◽  
Fire Risk Assessment ◽  
Risk Parameters

Fire is one of the most dangerous phenomena causing major casualties and financial losses in hospitals and healthcare settings. In order to prevent and control the fire sources, first risk assessment should be conducted. Failure Mode and Effect Analysis (FMEA) is one of the techniques widely used for risk assessment. However, Risk Priority Number (RPN) in this technique does not take into account the weight of the risk parameters. In addition, indirect relationships between risk parameters and expert opinions are not considered in decision making in this method. The aim is to conduct fire risk assessment of healthcare setting using the application of FMEA combined with Multi‐Criteria Decision Making (MCDM) methods. First, a review of previous studies on fire risk assessment was conducted and existing rules were identified. Then, the factors influencing fire risk were classified according to FMEA criteria. In the next step, weights of fire risk criteria and subcriteria were determined using Intuitionistic Fuzzy Multiplicative Best-Worst Method (IFMBWM) and different wards of the hospital were ranked using Interval-Valued Intuitionistic Fuzzy Combinative Distance-based Assessment (IVIFCODAS) method. Finally, a case study was performed in one of the hospitals of Shiraz University of Medical Sciences. In this study, fire alarm system (0.4995), electrical equipment and installations (0.277), and flammable materials (0.1065) had the highest weight, respectively. The hospital powerhouse also had the highest fire risk, due to the lack of fire extinguishers, alarms and fire detection, facilities located in the basement floor, boilers and explosive sensitivity, insufficient access, and housekeeping. The use of MCDM methods in combination with the FMEA method assesses the risk of fire in hospitals and health centers with great accuracy.

scholarly journals Wireless Sensor Network for Ignitions Detection: An IoT approach

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 893 ◽  
Author(s):  
Thadeu Brito ◽  
Ana I. Pereira ◽  
José Lima ◽  
António Valente
Keyword(s):  
Decision Making ◽  
Fire Detection ◽  
Barometric Pressure ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Data Simulation ◽  
Central System ◽  
Flame Ignition ◽  
Wide Scale ◽  
Point Data

Wireless Sensor Networks (WSN) can be used to acquire environmental variables useful for decision-making, such as agriculture and forestry. Installing a WSN on the forest will allow the acquisition of ecological variables of high importance on risk analysis and fire detection. The presented paper addresses two types of WSN developed modules that can be used on the forest to detect fire ignitions using LoRaWAN to establish the communication between the nodes and a central system. The collaboration between these modules generate a heterogeneous WSN; for this reason, both are designed to complement each other. The first module, the HTW, has sensors that acquire data on a wide scale in the target region, such as air temperature and humidity, solar radiation, barometric pressure, among others (can be expanded). The second, the 5FTH, has a set of sensors with point data acquisition, such as flame ignition, humidity, and temperature. To test HTW and 5FTH, a LoRaWAN communication based on the Lorix One gateway is used, demonstrating the acquisition and transmission of forest data (simulation and real cases). Even in internal or external environments, these results allow validating the developed modules. Therefore, they can assist authorities in fighting wildfire and forest surveillance systems in decision-making.

scholarly journals An Assessment of RFID Applications in Manufacturing Companies

2015 ◽  
Vol 6 (4) ◽  
pp. 33-42 ◽  
Author(s):  
Bartłomiej Gładysz
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Research Program ◽  
Cyber Physical Systems ◽  
Complex Method ◽  
Manufacturing Companies ◽  
Rfid Technology ◽  
Physical Systems ◽  
Early Decision ◽  
Rfid Applications

Abstract The meaning of Cyber Physical Systems and an Internet of Things with indication of RFID position in those concepts was outlined. Research program related to assessment of RFID technology was presented. Author deducted on problems related to RFID implementations and RFID essentially for logistics of manufacturing companies. Research goals and problems were formulated. Tools, techniques, models and methods that could be utilized were proposed and discussed. Research was focused on design of a new method to support early decision making phases for RFID application in logistics of manufacturing companies. Author stated that literature and practice lacks of complex method to answer if RFID is strategically important for the company, which processes should be RFID-supported, how RFID-supported processes should be designed and if RFID-support is rational. Framework for assessment of RFID technology with illustrative example was discussed.

scholarly journals INFORMATION SYSTEM FOR EVALUATION OF THE STATE OF INTOXICATION OF THE ORGANISM BASED ON THE BAYES NETWORK

2021 ◽  
Vol 3 (163) ◽  
pp. 144-151
Author(s):  
O. Moyseenko
Keyword(s):  
Decision Making ◽  
Information System ◽  
Expert System ◽  
Knowledge Base ◽  
Expert Knowledge ◽  
Experimental Testing ◽  
Postoperative Treatment ◽  
Formal Representation ◽  
Medical Systems ◽  
Electrode Potentials

An expert system is a computer program that simulates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field. It is a program that emulates the interaction a user might have with a human expert to solve a problem. The end user provides input by selecting one or more answers from a list or by entering data. An Expert System is a problem solving and decision making system based on knowledge of its task and logical rules or procedures for using knowledge. Both the knowledge and the logic are obtained from the experience of a specialist in the area. This paper considers approaches to building a knowledge base for medical systems. In developing the knowledge base of the information system, Bayesian networks were chosen as the basis for the decision-making model by type of patient pathology. This choice was due to the availability of these networks the ability to work with uncertain knowledge used in the diagnosis of diseases, in choosing the optimal course of treatment and subsequent prediction of patients. In addition, they offer the most adequate formal representation of inaccurate knowledge, as they are the result of a synthesis of statistical methods of data analysis and artificial intelligence. The presence of hydrosulfide ion intoxication (HS-intoxication), divalent iron ion intoxication (Fe-intoxication), the patient's absence of pathology and the value of Ag2S and Pt electrode potentials were selected as nodes of this network. Based on the accumulated experience of monitoring the condition of patients during their postoperative treatment (data obtained in collaboration with Ivano-Frankivsk National Medical University), as well as experimental data, conditional probabilities of values that can take the readings of the electrodes were established. Experimental testing of the adequacy of the proposed and implemented model was performed on an array of data from potentiometric measurements of patients' biomaterial. The prediction made by the network was taken as the node that had the highest probability of being in a state that indicates the presence of a pathology. Comparison of the results of the network with data obtained by other methods showed their convergence in 85% of cases. Thus, the developed network can be used to facilitate the process of diagnosing the presence and type of intoxication of the patient and is included in the information system for monitoring the patient's condition.

The Suppositional Rule

2020 ◽  
pp. 15-30
Author(s):  
Timothy Williamson
Keyword(s):  
Decision Making ◽  
Experimental Testing ◽  
Mathematical Proof ◽  
Ramsey Test ◽  
New Information

The chapter describes the role of suppositions in conditional thinking, from everyday decision-making to mathematical proof, and the cognitive role of imagination in developing the consequences of suppositions. It proposes that the primary way of assessing a conditional ‘If A, C’ is to suppose A and on that basis assess C; whatever attitude you take to C conditionally on A (such as acceptance, rejection, or something in between) take unconditionally to ‘If A, C’; this corresponds to the Ramsey Test or Suppositional Rule. Such offline assessment’s similarities to, and differences from, online updating on new information are discussed. Other ways of assessing ‘If A, C’ are also considered, including experimental testing by making A true, and reliance on memory or testimony without new first-hand testing.

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