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The design, fabrication and experimental validation of defected microstrip structure (DMS) are proposed to address the problem of near-end crosstalk (NEXT) and far-end crosstalk (FEXT) between the microstrip transmission lines in a printed circuit board.

The proposed DMS evolved with the combination of spur line (L-shaped DMS) and U-shaped DMS topologies. This technique reduces the strength of electromagnetic coupling and suppresses crosstalk by optimizing the capacitive and inductive coupling ratio between the linked microstrip lines. The practical inductance value is much more significant in DMS than in defected ground structures (DGS), but the capacitance value remains the same.

A DMS unit is etched on the aggressor microstrip line instead of the DGS circuit. Because there is no leakage via the ground plane and the circuit size is far smaller than with DGS, the enclosure issue is disregarded. DMS structures have a larger effective inductance and are resistant to electromagnetic interference. A tightly coupled transmission line structure with minimal separation between the coupled microstrip line is designed using DMS. Further research must be conducted to improve the NEXT, FEXT and spacing between the transmission lines.

Simulation and actual measurement results show that the proposed DMS structure can effectively suppress crosstalk by analysing the S-parameters, namely, S_12, S_13 and S_14, with measured values of 1.48 dB, 20.65 dB and 21.099 dB, respectively. The data rate is measured to be 1.34 Gbps as per the eye diagram characterization. The results show that the NEXT and FEXT are reduced by approximately 20 dB in the frequency range of 1–11 GHz for mixed signals. The substantial measured results in the vector network analyser coincide with the computer simulation technology microwave studio suite simulation results.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

With the development of integrated circuit and communication technology, digital secure communication has become a research hotspot. This paper aims to design a five-dimensional fractional-order chaotic secure communication circuit with sliding mode synchronous based on microcontroller (MCU).

First, a five-dimensional fractional-order chaotic system for encryption is constructed. The approximate numerical solution of fractional-order chaotic system is calculated by Adomian decomposition method, and the phase diagram is obtained. Then, combined with the complexity and 0–1 test algorithm, the parameters of fractional-order chaotic system for encryption are selected. In addition, a sliding mode controller based on the new reaching law is constructed, and its stability is proved. The chaotic system can be synchronized in a short time by using sliding mode control synchronization.

The electronic circuit is implemented to verify the feasibility and effectiveness of the designed scheme.

It is feasible to realize fractional-order chaotic secure communication using MCU, and further reducing the synchronization error is the focus of future work.

These implementations not only generate excessive voltage levels to enhance the quality of power but also include a detailed investigating of the various modulation methods and control schemes for multilevel inverter (MLI) topologies. Reduced harmonic modulation technology is used to produce 11-level output voltage with the production of renewable energy applications. The simulation is done in the MATLAB/Simulink for 11-level symmetric MLI and is correlated with the conventional inverter design.

This paper is focused on investigating the different types of asymmetric, symmetric and hybrid topologies and control methods used for the modular multilevel inverter (MMI) operation. Classical MLI configurations are affected by performance issues such as poor power quality, uneconomic structure and low efficiency.

The variations in both carrier and reference signals and their performance are analyzed for the proposed inverter topologies. The simulation result compares unipolar and bipolar pulse-width modulation (PWM) techniques with total harmonic distortion (THD) results. The solar-fed 11-level MMI is controlled using various modulation strategies, which are connected to marine emergency lighting loads. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by using SPARTAN 3A field programmable gate array (FPGA) board and the least harmonics are obtained by improving the power quality.

The simulation result compares unipolar and bipolar PWM techniques with THD results. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by a SPARTAN 3A field programmable gate array (FPGA) board, and the power quality is improved to achieve the lowest harmonics possible.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

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.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

As it is known, the electrostatic discharge (ESD) protection design of integrated circuit is very important, among which the silicon controlled rectifier (SCR) is one of the most commonly used ESD protection devices. However, the traditional SCR has the disadvantages of too high trigger voltage, too low holding voltage after the snapback and longer turn-on time. The purpose of this paper is to design a high-performance SCR in accordance with the design window under 0.25 µm process, and provide a new scheme for SCR design to reduce the trigger voltage, improve the holding voltage and reduce the turn-on time.

Based on the traditional SCR, an RC-INV trigger circuit is introduced. Through theoretical analysis, TCAD simulation and tape-out verification, it is shown that RC-INV triggering SCR can reduce the trigger voltage, increase the holding voltage and reduce the turn-on time of the device on the premise of maintaining good robustness.

The RC-INV triggering SCR has great performance, and the test shows that the transmission line pulse curve with almost no snapback can be obtained. Compared with the traditional SCR, the trigger voltage decreased from 32.39 to 16.24 V, the holding voltage increased from 3.12 to 14.18 V and the turn-on time decreased from 29.6 to 16.6 ns, decreasing by 43.9% the level of human body model reached 18 kV+.

Under 0.25 µm BCD process, this study propose a high-performance RC-INV triggering SCR ESD protection device. The work presented in this paper has a certain guiding significance for the design of SCR ESD protection devices.

We theorize the critical role of angel investors' affective experiences and first impressions in the context of entrepreneurial finance. We develop a model and propositions to illustrate why angel investors make the decision to continue screening, thus explaining why certain investment proposals make it, while others do not.

Drawing on affective events theory and the literature on affective experiences, we theorize how the perceptions of pitches that trigger positive or/and negative physiological arousal, short-lived emotions, and associated thoughts are different, thus allowing us to build new theory of how these different experiences can influence the outcome of the evaluation process in the initial screening stage.

Our model suggests that the initial evaluation unfolds in five stages: perception of an entrepreneurial pitch, physiological arousal, emotions, first impression, and a decision to continue screening. When different manifestations of physiological arousal and subsequent emotions set the tone of first impressions, they can be either a positive, negative, or mixed experience. While positive and mixed first impression can lead to selection, negative first impression can lead to rejection.

We illustrate what is of value for angel investors when they look for new investments, and why certain entrepreneurial pitches lead to the decision to continue screening, while others do not. We propose that what angel investors feel is particularly important in situations where they are not yet making the ultimate decision to invest money but are involved in decisions about whether to continue to spend time to investigate the investment proposal.

The purpose of this paper is to prevent the destruction of other parts of a wind energy conversion system because of faults, the diagnosis of insulated-gate bipolar transistor (IGBT) faults has become an essential topic of study. Demand for sustainable energy sources has been prompted by rising environmental pollution and energy requirements. Renewable energy has been identified as a viable substitute for conventional fossil fuel energy generation. Because of its rapid installation time and adaptable expenditure for construction scale, wind energy has emerged as a great energy resource. Power converter failure is particularly significant for the reliable operation of wind power conversion systems because it not only has a high yearly fault rate but also a prolonged downtime. The power converters will continue to operate even after the failure, especially the open-circuit fault, endangering their other parts and impairing their functionality.

The most widely used signal processing methods for locating open-switch faults in power devices are the short-time Fourier transform and wavelet transform (WT) – based on time–frequency analysis. To increase their effectiveness, these methods necessitate the intensive use of computational resources. This study suggests a fault detection technique using empirical mode decomposition (EMD) that examines the phase currents from a power inverter. Furthermore, the intrinsic mode function’s relative energy entropy (REE) and simple logical operations are used to locate IGBT open switch failures.

The presented scheme successfully locates and detects 21 various classes of IGBT faults that could arise in a two-level three-phase voltage source inverter (VSI). To verify the efficacy of the proposed fault diagnosis (FD) scheme, the test is performed under various operating conditions of the power converter and induction motor load. The proposed method outperforms existing FD schemes in the literature in terms of fault coverage and robustness.

This study introduces an EMD–IMF–REE-based FD method for VSIs in wind turbine systems, which enhances the effectiveness and robustness of the FD method.