Field Of Devices Research Articles

GNN-based Advanced Feature Integration for ICS Anomaly Detection

Recent adversaries targeting the Industrial Control Systems (ICSs) have started exploiting their sophisticated inherent contextual semantics such as the data associativity among heterogeneous field devices. In light of the subtlety rendered in these semantics, anomalies triggered by such interactions tend to be extremely covert, hence giving rise to extensive challenges in their detection. Driven by the critical demands of securing ICS processes, a Graph-Neural-Network (GNN) based method is presented to tackle these subtle hostilities by leveraging an ICS’s advanced contextual features refined from a universal perspective, rather than exclusively following GNN’s conventional local aggregation paradigm. Specifically, we design and implement the Graph Sample-and-Integrate Network (GSIN), a general chained framework performing node-level anomaly detection via advanced feature integration, which combines a node’s local awareness with the graph’s prominent global properties extracted via process-oriented pooling. The proposed GSIN is evaluated on multiple well-known datasets with different kinds of integration configurations, and results demonstrate its superiority consistently on not only anomaly detection performance (e.g., F1 score and AUPRC) but also runtime efficiency over recent representative baselines.

Structural Design and DLP 3D Printing Preparation of High Strain Stable Flexible Pressure Sensors.

Flexible pressure sensors are crucial force-sensitive devices in wearable electronics, robotics, and other fields due to their stretchability, high sensitivity, and easy integration. However, a limitation of existing pressure sensors is their reduced sensing accuracy when subjected to stretching. This study addresses this issue by adopting finite element simulation optimization, using digital light processing (DLP) 3D printing technology to design and fabricate the force-sensitive structure of flexible pressure sensors. This is the first systematic study of how force-sensitive structures enhance tensile strain stability of flexible resistive pressure sensors. 18 types of force-sensitive structures have been investigated by finite element design, simultaneously, the modulus of the force-sensitive structure is also a critical consideration as it exerts a significant influence on the overall tensile stability of the sensor. Based on simulation results, a well-designed and highly stretch-stable flexible resistive pressure sensor has been fabricated which exhibits a resistance change rate of 0.76% and pressure sensitivity change rate of 0.22% when subjected to strains ranging from no tensile strain to 20% tensile strain, demonstrating extremely low stretching response characteristics. This study presents innovative solutions for designing and fabricating flexible resistive pressure sensors that maintain stable sensing performance even under stretch conditions.

AI-powered medical devices for practical clinicians including the diagnosis of colorectal polyps

Background: The integration of medical devices with artificial intelligence (AI) software is rapidly advancing as technology progresses. AI machine learning can be used in commercial medical services to generate practical data; there is evidence that it can be integrated into newly developed devices. However, such devices must undergo approval, regulation, and supervision. The Food and Drug Administration approves regulations for numerous machine-learning medical devices and shares open lists with the public. In this article, we examine recent medical AI devices in different fields, including the diagnosis of colorectal polyps.Current Concepts: Currently, in the field of gastroenterology, there has been a significant amount of research aimed at enhancing adenoma detection rates using tools powered by AI, such as the EndoScreener and GI Genius. Various such devices have also been developed for other fields; examples include the 23andMe Personal Genome Service for DNA detection, Spectral MD’s DeepView platform for wound imaging in surgery, Gili Pro BioSensor for monitoring vital signs, DreaMed Advisor Pro for diabetes, Minuteful for urinary analysis, BrainScope TBI for cerebral diagnosis, Compumedics Sleep Monitoring System for sleep disorders, Idx-DR v2.3 for ophthalmology, and EarliPoint system for pediatrics.Discussion and Conclusion: By the time this article is published, it is likely that even more AI medical devices will have been approved and commercialized. The development of such devices should be strongly encouraged. Additionally, we anticipate greater involvement from practitioners in the development and validation of diverse medical AI devices in Korea.

Digital Twin-Based Cyber Range for Industrial Internet of Things

With the continuous integration of information technology and operation technology, Industrial Internet of Things(IIoT) is gradually changing from closed to open. Operators can configure, monitor, or control the industrial production process remotely via Internet, which brings security threats to IIoTs. Since the IIoT focuses on the availability of industrial production, it is unfeasible to study security issues directly on the industrial field. Thus, constructing an IIoT cyber range to reproduce industrial scenarios for offensive and defensive confrontation research is necessary. However, the traditional IIoT cyber range relies on physical industrial field devices that are not reproducible and hard to recover from cyber attacks. To solve these problems, in this paper, we propose a framework for a digital twin based cyber range and a digital twin construction method with multiple models. Cyber ranges with digital twins are more flexible and convenient. Based on the proposed method, an industrial scenario is reproduced using machine learning algorithms to predict temperature changes from different perspectives. The experimental result shows the ability of digital twins to construct an IIoT cyber range to reproduce production processes and replace field devices.

Magnetic Field‐Directed Deep Thermal Therapy via Double‐Layered Microneedle Patch for Promoting Tissue Regeneration in Infected Diabetic Skin Wounds

AbstractAlthough near‐infrared (NIR) light‐based photothermal therapies have shown therapeutic potential for infected wounds, the attenuation of NIR light intensity in tissue has severely limited the usage in deep bacterial infections. Herein, magneto‐thermal responsive bilayer microneedles (Fe‐Se‐HA MNs) consisting of functionalized hyaluronic acid (HA), ferro‐ferric oxide (Fe3O4), and micelle‐protected selenium nanoparticles (SeNPs@LAS) are constructed to overcome this challenge based on a self‐designed disk‐shaped electromagnetic field device (Disk‐ZVS). The electromagnetic field generated by the Disk‐ZVS shows virtually no intensity attenuation in living tissue. Finite element simulations showed that the field intensity and electromagnetic loss are concentrated on the tips of Fe‐Se‐HA MNs. The MNs are able to puncture hard scabs, penetrate into bacterial biofilms, and perform effective magnetic‐thermal conversion for deep hyperthermia sterilization. Following, the Fe‐Se‐HA MNs can be gradually degraded by excessive hyaluronidase in diabetic wound to release SeNPs, which reduce reactive oxygen species (ROS) to regulate wound redox homeostasis. Meanwhile, the SeNPs are beneficial to angiogenesis, which facilitates blood vessel formation and promotes wound repair. Therefore, various functions can be achieved for the Fe‐Se‐HA MNs, such as magneto‐thermal disinfection, deep and non‐invasive tissue penetration, anti‐inflammation, and pro‐angiogenesis, which shows great potential as an adjunctive therapy for infected diabetic wounds.

An investigation into the effectiveness of using acoustic touch to assist people who are blind.

Wearable smart glasses are an emerging technology gaining popularity in the assistive technologies industry. Smart glasses aids typically leverage computer vision and other sensory information to translate the wearer's surrounding into computer-synthesized speech. In this work, we explored the potential of a new technique known as "acoustic touch" to provide a wearable spatial audio solution for assisting people who are blind in finding objects. In contrast to traditional systems, this technique uses smart glasses to sonify objects into distinct sound auditory icons when the object enters the device's field of view. We developed a wearable Foveated Audio Device to study the efficacy and usability of using acoustic touch to search, memorize, and reach items. Our evaluation study involved 14 participants, 7 blind or low-visioned and 7 blindfolded sighted (as a control group) participants. We compared the wearable device to two idealized conditions, a verbal clock face description and a sequential audio presentation through external speakers. We found that the wearable device can effectively aid the recognition and reaching of an object. We also observed that the device does not significantly increase the user's cognitive workload. These promising results suggest that acoustic touch can provide a wearable and effective method of sensory augmentation.

Modeling the relationship between arterial blood pressure and sublingual microcirculatory blood flow assessed by Sidestream Dark Field videomicroscopy: An experimental study in anesthetized piglets.

Microcirculation is frequently assessed using videomicroscopy in the sublingual mucosa. However, limited research has been conducted on the existence of blood flow autoregulation in this region. We conducted a study in an experimental porcine model of pharmacologically induced hypotension to evaluate the relationship between mean arterial pressure (MAP) and the microvascular flow index (MFI). We hypothesized that this relationship would be linear in the absence of autoregulation or bilinear if autoregulation is present. Seven pigs underwent blood pressure changes induced by norepinephrine (hypertension) and sevoflurane (hypotension) administration. Sublingual microcirculation was assessed using a sidestream dark field device, and videos were recorded at different MAP levels ranging from 30 to 110 mmHg. MFI was calculated using the quadrant-based method. For our first hypothesis, we constructed a linear mixed model, while a bilinear model was used for the second hypothesis. The linear model demonstrated a statistically significant association (P = 0.03) described by the equation: MFI = 2.29 + 0.004 x MAP. The bilinear model identified a statistically significant inflection point at MAP = 99 mmHg (P = 0.01) with MFI = 2.7 AU (P < 0.0001). For MAP <99 mmHg, the relationship was: MFI = 2.26 + 0.004 x MAP, and for MAP >99 mmHg, MFI = 2.7. Despite statistical significance, neither model provided a satisfactory graphical fit due to high inter- and intra-individual variability. Consequently, this study did not allow us to draw conclusions regarding the presence of blood autoregulation.

High-quality VO2 films synthesized on polymer substrates using room-temperature pulsed laser deposition and annealing

With the growing trend towards portable and adaptable devices in various fields, the demand for flexible electronics and coatings utilizing phase transition materials like VO2 as a functional layer is rising. However, depositing high-quality crystalline VO2 films directly onto polymer substrates remains challenging due to the thermosensitivity of such materials being barely compatible with usual VO2 deposition methods. In this study, we present a simple method for directly growing VO2 on Kapton substrates. VOx films were first deposited onto the Kapton substrate at room temperature using pulsed laser deposition and subsequently annealed in an oxygen atmosphere at 390 °C. The electrical and optical properties of the VO2/Kapton samples with different film thicknesses were investigated. The 200 nm-thick vanadium dioxide films exhibit the best resistivity contrast with 3.1 orders of magnitude (OOM), while the 50 nm-thick films show the best transmittance change of 54 % at 2500 nm. The switching performances are comparable or even superior to those achieved previously using more complicated synthesis processes such as film transfer, introduction of buffer layers, and ink injection. Additionally, by coupling W elemental doping and thin film strain, we successfully tuned the VO2 transition temperature to room temperature with a dopant concentration of only 1.1 at.% while maintaining a high electrical contrast (2 OOM). The impressive electrical and optical transition performance of the VO2/Kapton samples, combined with their tunable transition temperature, makes them promising candidates for flexible electronic devices and thermochromic smart coatings.

Simultaneous broadband and high circular dichroism with two-dimensional all-dielectric chiral metasurface

Abstract Chiral metasurfaces have great potential in various applications such as polarimetric imaging and biomedical recognition. However, simultaneous broadband and high circular dichroism (CD) with high polarization extinction ratio (PER) remains a challenge. Here, we present a novel approach to realize simultaneous broadband and high CD with high PER in the optical communication band using a two-dimensional all-dielectric chiral metasurface. The structure is formed by a two-level chiral structure of split cross (first-order) and trapezoid-shaped (second-order) of Si nano ribs, respectively, in which constructively coupled first- and second-order of chirality occurs, resulting in the broad chiral response in the far field of multipoles excited by incident light of different chiralities. Theoretical results show that a CD in transmission reaching 0.9 (up to 0.993) and a PER exceeding 20 dB (up to 35 dB) over the entire wavelength range from 1.39 to 1.61 μm can be achieved simultaneously, consistent with the experimental results of CD ∼0.9 and PER of 10 dB (up to 19.7 dB). Our design paves the way for chiral metasurfaces toward practical applications in terms of working bandwidth, high CD and PER as well as integrality of the devices in many fields.

QoS-Aware and Energy Data Management in Industrial IoT

Two crucial challenges in Industry 4.0 involve maintaining critical latency requirements for data access and ensuring efficient power consumption by field devices. Traditional centralized industrial networks that provide rudimentary data distribution capabilities may not be able to meet such stringent requirements. These requirements cannot be met later due to connection or node failures or extreme performance decadence. To address this problem, this paper focuses on resource-constrained networks of Internet of Things (IoT) systems, exploiting the presence of several more powerful nodes acting as distributed local data storage proxies for every IoT set. To increase the battery lifetime of the network, a number of nodes that are not included in data transmission or data storage are turned off. In this paper, we investigate the issue of maximizing network lifetime, and consider the restrictions on data access latency. For this purpose, data are cached distributively in proxy nodes, leading to a reduction in energy consumption and ultimately maximizing network lifetime. To address this problem, we introduce an energy-aware data management method (EDMM); with the goal of extending network lifetime, select IoT nodes are designated to save data distributively. Our proposed approach (1) makes sure that data access latency is underneath a specified threshold and (2) performs well with respect to network lifetime compared to an offline centralized heuristic algorithm.

A Novel Tourniquet with an Alarm System, Replaceable Components, and The Ability to Adjust Pressure and Detect Body Temperature for Medical Applications

A tourniquet is a practical device in the medical field that is employed to collect blood and prevent bleeding in medical centers. The need for a durable tourniquet with leveled pressure adjustment capabilities, which indicates the time, can be used for both blood collection and control of intense bleeding, and has replaceable components in case of damage is strongly felt. Thus, developing a tourniquet with the aforementioned features is highly beneficial. The designed tourniquet includes four main parts (end hook, strap, main clip, and pin), and the other three parts are mounted on the strap. This tourniquet has a unique strap design and a sturdy lock and fastener, a body temperature detection sensor, a pressure adjustment section at four levels, a timer with an alarm, buttons (pins) to open the strap, a linen pad, and a special end hook (with an end clamp). The proposed time warning tourniquet with replaceable components has the ability to adjust the pressure, detect the temperature, and create local pressure, and therefore, can boost the performance of the medical staff during blood sampling and bleeding control procedures.

Physics-informed deep learning for lithium-ion battery diagnostics using electrochemical impedance spectroscopy

Lithium-ion batteries (LIBs) are prevalent energy storage devices in industrial fields and modern life, but are subjected to capacity degradation during operation due to the varying internal states. To ensure the efficiency, safety and reliability of LIBs, LIBs diagnostics by analyzing the internal states and estimating the capacity is crucial. However, model-based methods and deep learning models for LIBs diagnostics are mainly based on charging and discharging curves that contain limited information on battery internal states, and suffer from either model inaccuracy or limited interpretability. To achieve accurate and interpretable LIBs diagnostics, a novel physics-informed deep learning (PIDL) framework is proposed in this study using the electrochemical impedance spectroscopy (EIS), which is a powerful, non-invasive and information-rich technique. The EIS together with three physically informative parameters, which are extracted using model-based methods to investigate the varying internal states, are taken as inputs for capacity estimation, and two data fusion manners are proposed and investigated. Besides, to extract physically interpretable and conducive latent features, physical regularization and multi-task learning are incorporated, which make effective use of three information sources: physical knowledge, measurements and domain knowledge. Moreover, to evaluate the predictive uncertainty of capacity estimation, the deep ensemble strategy is adopted. The effectiveness and superiority of the PIDL framework are demonstrated using EIS datasets of eight commercially LIBs collected from the University of Cambridge.

The Ethernet-APL Revolution is Approaching Our Plants

With Ethernet-APL, IT/OT convergence is brought to a next level. High-speed communcation to field devices, elimination of complex infrastructure to extract data from the field, and simplified engineering and maintenance are key advantages. Yet, due to experiences with fieldbus technology, Ethernet-APL is considered as process industry’s last chance for digital field communication. This article presents key success factors. Furthermore, it summarizes the joint community effort by end users and vendors to prevent the repition of flaws experienced during the past fieldbus introduction.

Flow Performance Analysis of Double-Chamber Gas–Liquid Transferring Device under Gas Inlet Condition

Gas-liquid mixed transportation technology is the core technology and plays a key role in the development of oil and gas production and transportation industry. Three different models of double-chamber gas-liquid transferring devices for gas field were selected as the research objects of this paper, and Fluent software was used to analyze the flow performance under the 100% gas content inlet condition. The gas-liquid two-phase distribution and the periodic relationship between pressure, temperature, tank liquid height with time of the device were calculated. The analysis revealed that the internal flow law of different models of devices is similar. A device’s operating cycle generally includes three processes ′ suction-compression-discharge ′, the pressure and liquid height within the two tanks change alternately, and the calculation formula of the cycle period has been provided. The highest temperature in the device appears at the top pipe during the compression process. The velocity at the vertical pipe at the device’s outlet is the fastest. The research methods and results can offer a theoretical reference for the design, optimization and application of the double-chamber gas-liquid transferring device.

A New Multi-Dimensional Depletion Concept of Homogenization Field Devices

A New Multi-Dimensional Depletion Concept of Homogenization Field Devices

The Prediction of Landslide Slip Surface Based on the Correlation Between Relative Density and Dynamic Cone Penetration Test

Relative density is one of the most important properties indicating the strength and state of compaction of the soil. The dynamic cone penetration test is considered one of the fastest field tests for evaluating the relative strength of soil layers, including density. In this study, an attempt is made to correlate the relative density of the landslide soil with the dynamic cone penetration results. The aim of this study was to delineate the boundary between moving and in-situ soil for the prediction of slip surfaces and finally to conceptualise the underlying mechanism behind the initiation of a landslide. The results of the penetration tests give an increasing index of 1.9 - 2.4 cm/blow, 2.8 - 3 cm/blow and 3.2 cm/blow for the upper, middle and lower parts (toe), respectively. Using the correlation equation, the calculated relative density in the field was found to agree well with the relative density measured in the laboratory with a standard deviation of ±1.5%. The relationship between the relative density and the penetration index shows an inverse relationship where the resistance of the soil to dynamic penetration increases as the relative density of the soil increases, thus decreasing the penetration index. This result can be used to accurately conceptualize the mechanism behind a landslide using a simple and rapid field device.

End organ perfusion and pediatric microcirculation assessment.

Cardiovascular instability and reduced oxygenation are regular perioperative critical events associated with anesthesia requiring intervention in neonates and young infants. This review article addresses the current modalities of assessing this population's adequate end-organ perfusion in the perioperative period. Assuring adequate tissue oxygenation in critically ill infants is based on parameters that measure acceptable macrocirculatory hemodynamic parameters such as vital signs (mean arterial blood pressure, heart rate, urinary output) and chemical parameters (lactic acidosis, mixed venous oxygen saturation, base deficit). Microcirculation assessment represents a promising candidate for assessing and improving hemodynamic management strategies in perioperative and critically ill populations. Evaluation of the functional state of the microcirculation can parallel improvement in tissue perfusion, a term coined as "hemodynamic coherence". Less information is available to assess microcirculatory disturbances related to higher mortality risk in critically ill adults and pediatric patients with septic shock. Techniques for measuring microcirculation have substantially improved in the past decade and have evolved from methods that are limited in scope, such as velocity-based laser Doppler and near-infrared spectroscopy, to handheld vital microscopy (HVM), also referred to as videomicroscopy. Available technologies to assess microcirculation include sublingual incident dark field (IDF) and sublingual sidestream dark field (SDF) devices. This chapter addresses (1) the physiological basis of microcirculation and its relevance to the neonatal and pediatric populations, (2) the pathophysiology associated with altered microcirculation and endothelium, and (3) the current literature reviewing modalities to detect and quantify the presence of microcirculatory alterations.

Very low excess noise Al0.75Ga0.25As0.56Sb0.44 avalanche photodiode.

AlxGa1-xAsySb1-y grown lattice-matched to InP has attracted significant research interest as a material for low noise, high sensitivity avalanche photodiodes (APDs) due to its very dissimilar electron and hole ionization coefficients, especially at low electric fields. All work reported to date has been on Al concentrations of x = 0.85 or higher. This work demonstrates that much lower excess noise (F = 2.4) at a very high multiplication of 90 can be obtained in thick Al0.75Ga0.25As0.56Sb0.44 grown on InP substrates. This is the lowest excess noise that has been reported in any III-V APD operating at room temperature. The impact ionization coefficients for both electrons and holes are determined over a wide electric field range (up to 650 kV/cm) from avalanche multiplication measurements undertaken on complementary p-i-n and n-i-p diode structures. While these ionization coefficients can fit the experimental multiplication over three orders of magnitude, the measured excess noise is significantly lower than that expected from the β/α ratio and the conventional local McIntyre noise theory. These results are of importance not just for the design of APDs but other high field devices, such as transistors using this material.

The terahertz isolator and switch based on the nonreciprocal feature of magnetized InSb layered photonic structure

In this paper, a multifunctional device based on a one-dimensional (1-D) magnetized InSb layered photonic structure (LPS) that can achieve the function of a magnetic-controlled isolator and switch is proposed, with the advantages of multi-function. The external conditions for realizing the LPS function are temperature 303 K, magnetic field B1 = 0–0.3 T, B2 = 0 T, which are easier to obtain through an applied magnetic field device. B1 and B2 differ only in intensity. Both B1 and B2 are applied magnetic fields parallel to the positive y-axis. The change of magnetic field can influence the the cyclotron frequency of the electron which affect the dielectric constant of the tensor form, and finally lead to the change of refractive index (RI), resulting in interesting electromagnetic phenomena. Temporal inversion symmetry and spatial inversion symmetry could be easily broken to actualize nonreciprocal phenomena because of the magneto-optic effect of Indium antimonide (InSb) and an asymmetric arrangement of quasi-periodic media. For the isolator, the transmittance of forwarding propagation arrives at 0.994 and the backward scale is much closer to 0. The isolation and insertion loss achieves 34 dB and 0.0269 dB, and the range of the angle stabilization is from 17° to 31°. For the switch operating, just changing the value of B1 from 0.3 T to 0 T, can realize the function of the switch operating instead of an isolator. This shift is easier to reach by turning off the magnetic field. The extinction ratio attains 99.8 % and angle stabilization is between 9° and 31°. This magnetic-structure multifunctional LPS can play a vital constructive role in medicine, computing, and other fields.

Wave energy converter power take-off characterization: comparing dynamometer and field data

Through dynamometer testing of a wave energy converter’s (WEC’s) power take-off system (PTO), we characterize friction and establish a relationship between shaft speed and torque. This characterization is conducted through oscillation of the shaft with a velocity-controlled motor, yielding some key differences between lab tests and response of the system in the field. In this work, we develop an understanding of these differences, provide both linear and nonlinear representations of the PTO that can be used in hydrodynamic modeling, and assess how accurately these representations are reflected in data collected in the field. &#x0D; &#x0D; The WEC used in this testing is the TigerRAY, built by CPower as part of a WEC-UUV (uncrewed underwater vehicle) system funded by the Naval Facilities Engineering Systems Command. The full device is a two-body point absorber with a subsurface heave plate that acts to hydrodynamically stabilize the system and serves as a docking and charging station for the UUV. The system is undergoing its second year of development and testing, which includes both at-sea trials and shore-side dynamometer experiments at the University of Washington Applied Physics Lab. The dynamometer system records torque at the WEC drive shaft, as well as motor shaft speed. Data acquisition on board the WEC simultaneously records key generator information, such as current, voltage, and angular shaft position. &#x0D; &#x0D; Through comparison of lab and field data, we draw conclusions about the limits of a velocity-controlled dynamometer. Since this control scheme allows near-instantaneous changes in applied torque, it pushes the WEC through electrical system-induced torque spikes more quickly than is possible in the field. Reduction in the control gains of the dynamometer smooths the applied torque curve at the expense of added noise in the velocity profile. We weigh these tradeoffs using data obtained from field testing of the device in a real wave field. Additionally, we identify key characteristics in the dynamometer data and how they impact device performance in the field. Finally, we make recommendations about how to move forward with future dynamometer testing given these lessons learned.