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The purpose of this paper is to present a method to calculate the transient induced voltages along the underground pipelines and analyze the transient interference generated in the pipelines due to the inductive coupling in the fault‐to‐ground condition of power lines in close proximity.

Based on finite difference‐time domain method, an improved method is proposed to calculate transient inductive interference in underground metallic pipelines due to a fault in nearby power lines. The frequency‐dependent problem in the analysis of transient interference is solved in phase domain. Compared with the traditional method, the disposal of phase‐modal transformation matrices’ frequency‐dependent characteristic is avoided and the calculation is simplified by using vector fitting approach and recursive algorithm greatly in the proposed method.

A novel improved method is proposed to calculate transient induced voltage distribution along underground metallic pipelines due to a fault in nearby power lines. Results show that the peak value of transient induced voltage at the most critical point is about 1.15 times of the magnitude in the steady state without the fault removed and the analysis of transient inductive interference is necessary in the fault‐to‐ground case of power lines.

In order to mitigate the interference from power lines to nearby pipelines, pipelines should be good grounded and positioned as far away from the power line as possible. In high soil resistivity areas, the common corridor should be avoided.

The paper presents a method to calculate the transient induced voltages along the underground pipelines and analyze the transient interference generated in the pipelines due to the inductive coupling in the fault‐to‐ground condition of nearby power lines. The proposed method is general and can also be applied to other transient interference studies such as crosstalk problems of communication networks and interference between power lines and aboveground pipelines or communication cables. Effects of various parameters upon the inductive interference generated in underground pipelines due to a fault in nearby power lines are analyzed to be a guide for controlling the inductive interference.

The purpose of this paper is to compute the values of induced voltages and currents in an underground gas pipeline, which shares the same right of way with a high voltage power line (HVPL) in unbalanced phase currents regime, in order to detect the possibility of the AC corrosion occurring in the pipeline.

The analysis of the induced voltages in metallic structures (gas pipeline) was done using a professional analysis and modeling software which uses the electromagnetic field method.

It was shown that during fault conditions, large currents and voltages are induced on the pipelines, which may pose a threat to operating personnel and equipment. Induced voltages also occur in cases of unbalanced phase currents of the HVPL, which may pose a threat voltage that could lead to damages of the underground gas pipeline due to corrosion phenomena.

Because the electromagnetic field approach involves complicated analytical expression and introduces serious computational difficulties, among which matrix of coefficients representing the set of simultaneous linear equations, the use of professional analysis and modeling software is justified.

The paper reveals that even in unbalanced phase currents regime of the HVPL, the nearby metallic structures that share the same right of way with the transmission line are in danger of degradation because of the induced voltages, whose values exceed the values imposed by regulation.

The purpose of this paper is to make a study of electromagnetic interference between electrical power lines and nearby underground metallic pipelines.

The equivalent electrical circuit of the studied electromagnetic interference problem between electrical power lines and nearby metallic pipelines is created and solved using a loop currents technique based on a hybrid method. The used circuit solving technique was implemented in a software application developed by the authors.

The authors have identified the influence of phase sequence on induced voltage level in an underground pipeline for a double circuit electrical power line. Also the effect of different normal operation and phase to earth fault currents have been revealed.

The study has been made through a research project with the Romanian gas transportation company, in order to find the proper protection techniques for underground metallic pipelines.

The paper reveals the influence of some electrical and geometrical parameters that have not been studied in detail previously.

The purpose of this manuscript is to detect heart fault using Electrocardiogram. Mutually low and high frequency noises such as electromyography (EMG) and power line interference (PLI) degrades the performance of ECG signals.

The ECG record depicts the procedural electrical movement of the heart, which is non-invasive foot age obtained by placing surface electrodes on designated locations of the patient’s skin. The main concept of this manuscript is to present a novel filtering method to cancel the unwanted noises in ECG signal. Here, intrinsic time scale decomposition (ITD) is introduced to suppress the effect of PLI from ECG signals.

In the existing ITD, the gain control parameter is a constant value; however, in this paper it is an adaptive feature that varies according to certain constraints. Simulation outcomes show that the proposed method effectively reduces the effect of PLI and quantitatively express the effectiveness with different evaluation metrics.

The results found by the proposed method are compared with Fourier decomposition technique and eigen value decomposition methods (EDM) to validate the effectiveness of the proposed method.

Following a power blackout, unstable or excessive voltages are common during the first few seconds when power is restored. The Power Pause surge suppressor is a new device that protects electronic equipment from such “after blackout” over‐voltages.

Presents a technique based on the development of an artificial neural network (ANN) model for predicting the electromagnetic inference effects on gas pipelines shared right‐of‐way (ROW) with high voltage transmission lines.

Examines the induced pipeline voltage under different soil resistivity, fault current and separation distance.

The results indicate strong agreement between model prediction and observed values.

Demonstrates that the ANN‐based model developed can predict the induced voltage with high accuracy. The accuracy of the predicted induced voltage is very important for designing mitigation systems that will increase overall pipeline integrity and make the pipeline and appurtenances safe for operating personnel.

In operating any computer system, whether a small personal computer or a large main‐frame system, power protection should be considered with respect to protecting computer data and possibly the hardware. But how much protection is needed? This article addresses basic issues computer users should consider before selecting power protection. Although some of the information applies chiefly to mainframe computers, the basic concepts (backing up data and line filters) apply to all systems.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The purpose of this paper is to present an original iterative nodal approach to calculate the fault current distribution on overhead lines.

By changing the mutual couplings among different conductors into the equivalent voltage sources, node voltages are updated iteratively by using conventional nodal analysis with those additional sources until the convergence is achieved.

The proposed algorithm can handle the complicated topology of a power transmission line and has no difficulties in taking all physical couplings into account. The fault current distribution calculated by this method is in good agreement with those published in the literature. Although the proposed approach is iterative, the CPU time needed is still reasonable compared to the direct solution approach. The memory requirement is low because the coefficient matrix is highly sparse for the nodal analysis of each iteration loop.

The proposed approach can serve as an alternative in calculating the fault current because of its efficiency and ease of implementation.

Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.

MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.

According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.

This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.