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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.

Electric motor heating during biomass recovery and its handling on conveyor is a serious concern for the motor performance. Thus, the purpose of this paper is to design and develop a hardware prototype of master–slave electric motors based biomass conveyor system to use the motors under normal operating conditions without overheating.

The hardware prototype of the system used master–slave electric motors for embedded controller operated robotic arm to automatically replace conveyor motors by one another. A mixed signal based embedded controller (C8051F226DK), fully compliant with IEEE 1149.1 specifications, was used to operate the entire system. A precise temperature measurement of motor with the help of negative temperature coefficient sensor was possible due to the utilization of industry standard temperature controller (N76E003AT20). Also, a pulse width modulation based speed control was achieved for master–slave motors of biomass conveyor.

As compared to conventional energy based mains supply, the system is self-sufficient to extract more energy from solar supply with an energy increase of 11.38%. With respect to conventional energy based \ of 47.31%, solar energy based higher energy saving of 52.69% was reported. Also, the work achieved higher temperature reduction of 34.26% of the motor as compared to previous cooling options.

The proposed technique is free from air, liquid and phase-changing material based cooling materials. As a consequence, the work prevents the wastage of these materials and does not cause the risk of health hazards. Also, the motors are used with their original dimensions without facing any leakage problems.

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.

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.

Process mining has emerged in the last decade as one of the most promising tools to discover and understand the actual execution of processes. This paper addresses the application of process mining techniques to analyze the performance of automatic guided vehicles (AGVs) in one of the Body in White circuits of the factory that Stellantis has in Vigo, Spain.

Standard process mining discovery and conformance algorithms are applied to analyze the different AGV execution paths, their lead times, main sources and identify any unexpected potential situations, such as unexpected paths or loops.

Results show that this method provides very useful insights which are not evident for logistics technicians. Even with such automated devices, where the room for decreased efficiency can be apparently small, process mining shows there are cases where unexpected situations occur, leading to an increase in circuit times and different variants for the same route, which pave the road for an actual improvement in performance and efficiency.

This paper provides evidence of the usefulness of applying process mining in manufacturing processes. Practical applications of process mining have traditionally been focused on processes related to services and management, such as order to cash and purchase to pay in enterprise resource planning software. Despite its potential for use in industrial manufacturing, such contributions are scarce in the current state of the art and, as far as we are aware of, do not fully justify its application.

The purpose of this study is to explore the transient characteristics of mixed-flow pumps during startup process.

This study uses a full-flow field transient calculation method of mixed-flow pump based on a closed-loop model.

The findings show the hydraulic losses and internal flow characteristics of the piping system during the start-up process.

Large computational cost.

Improve the accuracy of current numerical simulation results in transient process of mixed-flow pump.

Simplify the setting of boundary conditions in the transient calculation.

Identification of the direction of the sound source is very important for human–machine interfacing in the applications such as target detection on military applications and wildlife conservation. Considering its vast applications, this study aims to design, simulate, fabricate and test a bidirectional acoustic sensor having two cantilever structures coated with piezoresistive material for sensing has been designed, simulated, fabricated and tested.

The structure is a piezoresistive acoustic pressure sensor, which consists of two Kapton diaphragms with four piezoresistors arranged in Wheatstone bridge arrangement. The applied acoustic pressure causes diaphragm deflection and stress in diaphragm hinge, which is sensed by the piezoresistors positioned on the diaphragm. The piezoresistive material such as carbon or graphene is deposited at maximum stress area. Furthermore, the Wheatstone bridge arrangement has been formed to sense the change in resistance resulting into imbalanced bridge and two cantilever structures add directional properties to the acoustic sensor. The structure is designed, fabricated and tested and the dimensions of the structure are chosen to enable ease of fabrication without clean room facilities. This structure is tested with static and dynamic calibration for variation in resistance leading to bridge output voltage variation and directional properties.

This paper provides the experimental results that indicate sensor output variation in terms of a Wheatstone bridge output voltage from 0.45 V to 1.618 V for a variation in pressure from 0.59 mbar to 100 mbar. The device is also tested for directionality using vibration source and was found to respond as per the design.

The fabricated devices could not be tested for practical acoustic sources due to lack of facilities. They have been tested for a vibration source in place of acoustic source.

The piezoresistive bidirectional sensor can be used for detection of direction of the sound source.

In defense applications, it is important to detect the direction of the acoustic signal. This sensor is suited for such applications.

The present paper discusses a novel yet simple design of a cantilever beam-based bidirectional acoustic pressure sensor. This sensor fabrication does not require sophisticated cleanroom for fabrication and characterization facility for testing. The fabricated device has good repeatability and is able to detect the direction of the acoustic source in external environment.

Dielectric barrier discharge (DBD) is widely used in the treatment of skin disease, surface modification of material and other fields of electronics. The purpose of this paper is to design a high-performance power supply with a compact structure for excimer lamps in electronics application.

To design a high-performance power supply with a compact structure remains a challenge for excimer lamps in electronics application, a current-source type power supply in a single stage with power factor correction (PFC) is proposed. It consists of an excitation voltage generation unit and a PFC unit. By planning the modes of the excitation voltage generation unit, a bipolar pulse excitation voltage with a high rising and falling rate is generated. And a high power factor (PF) on the AC side is achieved by the interaction of a non-controlled rectifier and two inductors.

The experimental results show that not only a high-frequency and high-voltage bipolar pulse excitation voltage with a high average rising and falling rate (7.51GV/s) is generated, but also a high PF (0.992) and a low total harmonic distortion (5.54%) is obtained. Besides, the soft-switching of all power switches is realized. Compared with the sinusoidal excitation power supply and the current-source power supply, the proposed power supply in this paper can take advantage of the potential of excimer lamps.

A new high-performance power supply with a compact structure for DBD type excimer lamps is proposed. The proposed power supply can work stably in a wide range of frequencies, and the smooth regulation of the discharge power of the excimer lamp can be achieved by changing the switching frequency. The ideal excitation can be generated, and the soft switching can be realized. These features make this power supply a key player in the outstanding performance of the DBD excimer lamps application.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.