Fuzzy-based forest fire prevention and detection by wireless sensor networks

Forest fires may cause considerable damages both in ecosystems and lives. This proposal describes the application of Internet of Things and wireless sensor networks jointly with multi-hop routing through a real time and dynamic monitoring system for forest fire prevention. It is based on gathering and analyzing information related to meteorological conditions, concentrations of polluting gases and oxygen level around particular interesting forest areas. Unusual measurements of these environmental variables may help to prevent wildfire incidents and make their detection more efficient. A forest fire risk controller based on fuzzy logic has been implemented in order to activate environmental risk alerts through a Web service and a mobile application. For this purpose, security mechanisms have been proposed for ensuring integrity and confidentiality in the transmission of measured environmental information. Lamport's signature and a block cipher algorithm are used to achieve this objective

Design and Performance Study of Improved Fuzzy System with Genetic Algorithm

Technical trading relies heavily on analysis, most of which is statistical in nature. When the data to be modeled is nonlinear, imprecise, or complicated, fuzzy inference systems (FISs) are used in conjunction with computational, mathematical, and statistical modeling methodologies to simulate technical trading. Fuzzy logic may be modeled using linear, nonlinear, geometric, dynamic, and integer programming. These techniques, when combined with fuzzy logic, help the decision-maker arrive at a better solution while still facing some degree of ambiguity or uncertainty. The moving average method is a useful metric that may give trade recommendations to aid investors further. While trading signals inform investors of when to purchase and sell, a simple moving average provides no such information. In this research, we suggest a fuzzy moving average approach in which the intensity of trading signals, measured in terms of trading volume, is determined by using the fuzzy logic rule. In this research, we propose using fuzzy logic technical trading rules, which are more resistant to decision-making mistakes, to mitigate the trading uncertainty inherent in the conventional technical indicators method

A fuzzy approach for feature extraction of brain tissues in Non-Contrast CT

In neuroimaging, brain tissue segmentation is a fundamental part of the techniques that seek to automate the detection of pathologies, the quantification of tissues or the evaluation of the progress of a treatment. Because of its wide availability, lower cost than other imaging techniques, fast execution and proven efficacy, Non-contrast Cerebral Computerized Tomography (NCCT) is the most used technique in emergency room for neuroradiology examination, however, most research on brain segmentation focuses on MRI due to the inherent difficulty of brain tissue segmentation in NCCT. In this work, three brain tissues were characterized: white matter, gray matter and cerebrospinal fluid in NCCT images. Feature extraction of these structures was made based on the radiological attenuation index denoted by the Hounsfield Units using fuzzy logic techniques. We evaluated the classification of each tissue in NCCT images and quantified the feature extraction technique in images from real tissues with a sensitivity of 92% and a specificity of 96% for images from cases with slice thickness of 1 mm, and 96% and 98% respectively for those of 1.5 mm, demonstrating the ability of the method as feature extractor of brain tissues.Postprint (published version

Construcción dinámica de consultas difusas sobre una base de datos de proyectos

In this paper an application for evaluation and control of software projects is presented. The novelty of this application is that it has been developed using an extended database management system with fuzzy logic. In addition to the usual tasks of a project control tool, this application allows to evaluate the management of a project, taking into consideration the benefits of fuzzy queries.En este trabajo se presenta una aplicación para evaluación y control de proyectos de software. La novedad de esta aplicación es que ha sido desarrollada usando un sistema gestor de bases de datos extendido con lógica difusa. Además de las tareas habituales de una herramienta de control de proyectos, esta aplicación permite evaluar la gestión de un proyecto, aprovechando las bondades de consultas difusas

Automated detection of parenchymal changes of ischemic stroke in non-contrast computer tomography: a fuzzy approach

The detection of ischemic changes is a primary task in the interpretation of brain Computer Tomography (CT) of patients suffering from neurological disorders. Although CT can easily show these lesions, their interpretation may be difficult when the lesion is not easily recognizable. The gold standard for the detection of acute stroke is highly variable and depends on the experience of physicians. This research proposes a new method of automatic detection of parenchymal changes of ischemic stroke in Non-Contrast CT. The method identifies non-pathological cases (94 cases, 40 training, 54 test) based on the analysis of cerebral symmetry. Parenchymal changes in cases with abnormalities (20 cases) are detected by means of a contralateral analysis of brain regions. In order to facilitate the evaluation of abnormal regions, non-pathological tissues in Hounsfield Units were characterized using fuzzy logic techniques. Cases of non-pathological and stroke patients were used to discard/confirm abnormality with a sensitivity (TPR) of 91% and specificity (SPC) of 100%. Abnormal regions were evaluated and the presence of parenchymal changes was detected with a TPR of 96% and SPC of 100%. The presence of parenchymal changes of ischemic stroke was detected by the identification of tissues using fuzzy logic techniques. Because of abnormal regions are identified, the expert can prioritize the examination to a previously delimited region, decreasing the diagnostic time. The identification of tissues allows a better visualization of the region to be evaluated, helping to discard or confirm a stroke.Peer ReviewedPostprint (author's final draft

Smart city: an advanced framework for analyzing public sentiment orientation toward recycled water

The coronavirus pandemic of the past several years has had a profound impact on all aspects of life, including resource utilization. One notable example is the increased demand for freshwater, a lifeblood of our planet, on the other hand, the smart city vision aims to attain a smart water management goal by investing in innovative solutions such as recycled water systems. However, the problem lies in the public’s sentiment and willingness to use this new resource which discourages investors and hinders the development of this field. Therefore, in our work, we applied sentiment analysis using an extended version of the fuzzy logic and neural network model from our previous work, to find out the general public opinion regarding recycled water and to assess the effects of sentiments on the public’s readiness to use this resource. Our analysis was based on a dataset of over 1 million text content from 2013 to 2022. The results show, from spatio-temporal perspectives, that sentiment orientation and acceptance-behavior towards using recycled water have increased positively. Additionally, the public is more concerned in areas driven by the smart city vision than in areas of medium and low economic development, where investment in sensibilization campaigns is needed

Collaborative elicitation to select a sustainable biogas desulfurization technique for landfills

[EN] The 2015 Paris Agreement within the United Nations Framework Convention on Climate Change establishes three key ways for the reduction of the emissions of Greenhouse Effect Gases: mitigation, adaptation and resilience of ecosystems. In this context, one of the major goals for methane recovery from waste is the process of obtaining biogas from biomass or waste, a form of fuel with zero impact on the carbon footprint of the planet. All possible uses of biogas depend mainly on the degree of purification obtained. The removal of hydrogen sulfide (H2S) is the main weakness in using biogas in industrial applications. If the use of biogas is intended for engines, turbines or to enrich the biogas to obtain natural gas, lowering the levels of H2S will be necessary, in order to avoid corrosion in gas lines and in engines. Biogas desulfurization can be achieved through different techniques: physical, chemical, biological or hybrid procedures. Selecting the most sustainable technique to clean biogas entails a complex problem, which involves the analysis of these desulfurization treatments under different criteria. In this paper, we present a novel collaborative elicitation to select the consensus procedure for the reduction of the concentration of H2S in biogases from landfills. The elicitation technique is based on fuzzy set theory and VIKOR method in order to handle intangible data and to avoid potential bias by the panelists. The proposed hybrid method guarantees traceability and transparency to achieve consensus among the panel of experts during the decision making procedure.Curiel-Esparza, J.; Reyes-Medina, M.; Martín Utrillas, MG.; Martínez-García, MP.; Canto-Perello, J. (2019). Collaborative elicitation to select a sustainable biogas desulfurization technique for landfills. Journal of Cleaner Production. 212:1334-1344. doi:10.1016/j.jclepro.2018.12.095S1334134421

Image (Pre-image) Homomorfisme Interior Subgrup Fuzzy

Dalam makalah ini, akan diperkenalkan notasi image (pre-image) di bawah homomorfisma grup, dan akan dibuktikan image (pre-image) interior subgrup fuzzy (interior subgrup) di bawah homomorfisma grup selalu interior subgrup fuzzy (interior subgrup). [In this paper, we will introduce the image (pre-image) under the group homomorphism, and we will prove the image (pre-image) of the interior of the fuzzy subgroup (the interior of the subgroup) under the group homomorphism is always the interior of the fuzzy subgroup (the interior of the subgroup).

A Review of Digital Image Classification Based on Fuzzy Logic

Fuzzy logic has long been an important issue for in the field of computer science, computer vision, image processing, machine learning and control theory and mathematics. In this review paper, we also see that the basics of fuzzy logic as well as fuzzy logic system (Fuzzy Inference System) use as decision making technique under a linguistic view of fuzzy sets. In this study, we focused to review the fuzzy logic to classification of digital image. The aim of this study was to review the fuzzy logic algorithm for classification of image