During the past decades, fiber-optic technology has become a very popular tool for vital signs monitoring. Thanks to its advantageous properties, such as noninvasiveness, biocompatibility, and ...resistance to electromagnetic interferences, this methodology started to be explored under the conditions of a magnetic resonance (MR) environment. This review article presents the motivation and possibilities of using fiber-optic sensors (FOSs) in MR environment and summarizes the studies dealing with experimental validation of their compatibility with MR. Several aspects of the presented issue are highlighted and discussed, such as suitability of the fiber-optic approach for MR triggering, precision of vital sign detection, development of sensor designs, and its application to patient's body. From the literature review, it can be concluded that FOSs have promising future in the field of cardiorespiratory monitoring in MR environment. This is mainly due to their advantages originating from sensing mechanical signals instead of electrical ones, which makes them resistant to MR interference and extrasystoles. Moreover, these sensors are easy to use, reusable, and suitable for combined monitoring. However, there are several shortcomings that should be solved in future research before introducing them to clinical practice, namely, signal's delay or optimal placement of sensors.
The application of fiber-optic-based sensors, especially in the magnetic resonance (MR) environment and the sleep laboratory, has become an intensely discussed topic. Although these sensors offer ...significant benefits, their practical deployment has two very challenging issues-it is necessary to find a suitable way to construct and encapsulate sensors, and it is also required to ensure that an appropriate advanced signal processing method is chosen. This study focuses on the latter area, aiming to apply advanced methods of processing measured biosignals obtained from fiber-optic sensors that use light interference for their function. These sensors are characterized by the fact that we can classify the measured biosignals as phonocardiography (PCG). This article describes in length the determination of a patient's heart rate (HR) as a basic parameter determining his or her state of health. The study is based on results collected from 11 test subjects (five females and six males), using the following three testing methods: empirical mode decomposition (EMD), complete ensemble EMD with adaptive noise (CEEMDAN), and wavelet transform (WT). The evaluation was conducted by determining the probability of correct detection with the use of overall accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and the harmonic mean between SE and PPV (<inline-formula> <tex-math notation="LaTeX">F1 </tex-math></inline-formula>). The functionality of the system was verified against the relevant reference in the form of simultaneously measured electrocardiograms (ECGs), from which reference annotations were estimated. This work showed that WT seems to be a suitable method, when, for all 11 tested signals, it achieved an ACC of >95%, based on the evaluation parameters, and at the same time, its computational complexity was the lowest of the tested methods.
The massive increase in urban population has created a slew of socioeconomic and environmental issues. Among these problems, the most notable is the disposal of solid waste and the search for an ...effective system for it. Many scholars employing various fuzzy set-like methodologies have considered it a fuzzy multi-criteria or multi-attribute decision-making problem due to the involvement of criteria and anticipated uncertainty. The goal of the current study is to use an innovative methodology to tackle the expected uncertainties present in the solid waste site selection problem (SOWSSP). Such uncertainties may be seen in decision-makers’ choices of parameters (or subparameters) and the degree to which they accept approximations for various options. Therefore, a novel mathematical structure called fuzzy parameterized possibility single valued neutrosophic hypersoft set (Fppsv-NHSS) is characterized first and then integrated with modified Sanchez’s method to resolve the SOWSSP through the proposal of an intelligent algorithm. The steps of the proposed algorithm are explained with a self-explanatory example. The relationship between the suitability of solid waste management systems and sites is discussed, and their rankings are determined with rich descriptions of their feasibility. The preferential aspects of this study are that it is capable of managing uncertainties depicted by the nature of parameters and approximations of alternatives by using the concept of fuzzy parameterization and possibility grades respectively. It employs particular mathematical formulations to determine the fuzzy parameterized degrees and possibility grades that are missing in the existing literature. It facilitates the decision-makers to evaluate the alternatives independently, with the choice being indeterminate. With the help of comparison, the computed results are found to be consistent and reliable due to their preferential features.
•Innovative approach for solid waste site selection under uncertainty.•Fuzzy parameterized possibility single valued neutrosophic hypersoft set used.•Trustworthy decision support framework can be designed.•New algebraic model to address site selection demand characterized.
Non-invasive electrocardiography (NI-ECG) has become an indispensable tool for monitoring fetal and neonatal cardiac activity throughout the stages of pregnancy and postpartum care. This review ...emphasizes the distinct advantages of NI-ECG, including extended monitoring capabilities and valuable insights into fetal and neonatal health. The exploration of textile electrodes is highlighted as a promising alternative, offering improved comfort and reduced skin irritation compared to traditional adhesive electrodes. However, challenges in NI-ECG persist, with electrode placement, quantity, and noise removal being key considerations. The review underscores the significance of addressing interference sources, such as maternal and fetal body signals, motion artifacts, and electrode-skin contact. Additionally, the discussion extends to computer-aided diagnostics, presenting novel approaches for classifying fetal and neonatal health during pregnancy and delivery. Ongoing research aims to optimize electrode placement, develop advanced noise reduction algorithms, and explore sophisticated classification methodologies. These advancements hold the potential to enhance electronic monitoring, enabling early detection of abnormalities and promoting improved outcomes in prenatal and neonatal care.
This study explores the effective use of a spectral area defined by a radiation source for multipoint measurements with fiber Bragg grating (FBG) sensors. The capacity of the sensor network based on ...a wavelength multiplex is limited by the spectral work area of the used radiation source and by several other parameters, such as the spectral parameters of individual sensors, type of the measured quantity and measurement range, sensitivity coefficients, production tolerances, and protection zones among the measuring channels. This is why it is necessary to use this limited area in an "economical" manner. The initial part of this article explores modeling of sensor networks using Bragg gratings, an output of which is an analysis of the impact of individual parameters on the capacity of a sensor network. These models are then applied to the mathematical definition of the given network proposal formed by real sensors. At the end, the stated principles are verified by real measurements with a sensor network formed by five Bragg sensors. The study points to the necessity of paying close attention to the proposals of sensor networks with FBG for the purpose of the effective use of the given spectral work area, increasing capacity, and reducing the possibility of crosstalk when assessing the Bragg sensors.
The selection of antivirus masks is an important problem in the context of the ongoing COVID-19 pandemic. Multiple attribute decision-making (MADM) algorithmic approaches can be used to evaluate and ...compare different masks based on multiple criteria, such as effectiveness, comfort, and cost. An aggregation of interval-valued multi-fuzzy hypersoft sets provides a flexible framework for handling uncertainty and imprecision in the MADM process. This approach allows for the integration of multiple sources of information such as expert opinions and empirical data, and considers the different levels of uncertainty and ambiguity associated with each criterion. By using the matrix-manipulated aggregation of interval-valued multi-fuzzy hypersoft sets like the induced fuzzy matrix, α-level matrix, threshold matrix, and mid-threshold matrix, an algorithm is proposed for the optimal selection of material for manufacturing antivirus masks. The robustness of the algorithm is maintained by following simple computation-based stages that enable a wide range of multidisciplinary readers to understand the idea vividly. By using this algorithm, it is possible to improve the accuracy and reliability of the decision-making process and to better balance the trade-offs between the different criteria, i.e., the computed results of the proposed algorithm and the structural aspects of the proposed approach are both compared with some relevant existing structures. Computation-based and structural comparisons are presented to assess the adaptability and reliability of the study. The first one is meant to check reliability, while the second is meant to check flexibility. In both cases, however, the presented approach yields the required standard. By comparing the prospective structure to the relevant developed model, the implications of the proposed framework are explored.
Třebaže se autoři humanistických veršů, oslavujících český venkov, v mnoha ohledech řídili předpisy antických rétorů a mnoho převzali kromě toho z vrcholných antických děl i z prací jiných humanistů, ...přece prokázali schopnost vystihnout zvláštnosti popisovaných krajů a projevili také určitý smysl pro přírodu.
In the current period, there has been a prominent and gradual upswing in the application of Internet of Energy (IoE) sensors in smart cities. These sensors play a vital role across diverse aspects of ...the energy sector, ranging from producing energy to haggling with the complexities of the smart grid. The IoE sensors use fiber optics technology that increases the speed and bandwidth of data transfer in smart grid applications. Incorporating IoE sensors, including fiber optics, is paramount to rehabilitating extensive IoE sensor data into practical information to distribute energy based on prices, availability, and demand for smart homes and electric vehicles. However, from energy generation to consumption, many nodes are incorporated. Therefore, security is a crucial challenge to processing accurate IoE sensor data for energy generation and consumption in smart cities. This paper presents blockchain-enabled, energy-efficient IoE smart grid architecture for smart homes and electric vehicle applications. The proposed architecture suggests blockchain-energy-efficient IoE sensors data scheduling (BEDS) algorithm schemes that consist of blockchain, smart grid, and vehicle and smart home schemes. The paper considers grid data based on sensors for different applications. The proposed system integrates fiber optics, collecting and offloading sensors to the grid for execution. This study aims to process IoE sensor data based on blockchain with a minimum processing time of 29% and less power consumption of 41%. Simulation results show that BEDS has less processing time and energy consumption than existing proof-of-work and proof-of-stake blockchain methods in smart grid networks.
•A smart-grid architecture for energy production in smart cities.•Blockchain energy data scheduling (BEDS) algorithm framework.•An energy-efficient blockchain-enabled IoE smart grid architecture.
