Interface Method Research Articles

Application of SSA-KNN Algorithm in Fault Analysis of Power Metering Automation System

In view of the great pressure of operation and maintenance of power energy data collection terminal after putting into operation, an intelligent fault diagnosis system for power equipment terminal based on computer was developed. This paper proposes an Agent based on autonomy, promotility, cooperation and interactivity. It also provides a flexible interactive communication interface and load balancing optimization method. It can meet a variety of data transmission specifications and a large number of data service transmission requirements. The SA-KNN algorithm is used to analyze the power quality. Methods The operation data of maintenance electricity were collected. Learning and cluster analysis are carried out by using relevant data, and the calculation model of automatic check device failure is established. At the same time, the outlier points in the collected data are used to accurately locate the fault points of the power grid. This method can realize the comprehensive fault diagnosis of the power grid by using the interaction between the power grid and each component.

Challenges as catalysts: how Waymo’s Open Dataset Challenges shape AI development

AbstractArtificial intelligence (AI) and machine learning (ML) are becoming increasingly significant areas of research for scholars in science and technology studies (STS) and media studies. In March 2020, Waymo, Google/Alphabet’s autonomous vehicle project, introduced the ‘Open Dataset Virtual Challenge’, an annual competition leveraging their Waymo Open Dataset. This freely accessible dataset comprises annotated autonomous vehicle data from their own Waymo vehicles. Yearly, Waymo has continued to host iterations of this challenge, inviting teams of computer scientists to tackle evolving machine learning and vision problems using Google's data and tools. This article analyses these challenges, situating them within the context of the ‘Grand Challenges’ of artificial intelligence (AI), which aimed to foster accountable and commercially viable advancements in the late 1980s. Through two exploratory workshops, we adopted a ‘technographic’ approach to examine the pivotal role of challenges in the development and political economy of AI. Serving as an organising principle for the AI innovation ecosystem, the challenge connects companies and external collaborators, driving advancements in specific machine vision domains. By exploring six key themes—interface methods, incrementalism, metrics, AI vernacular, applied domains, and competitive advantages—the article illustrates the role of these challenges in shaping AI research and development. By unpacking the dynamic interaction between data, computation, and labour, these challenges serve as catalysts propelling advancements towards self-driving technologies. The study reveals how challenges have historically and presently shaped the evolving landscape of self-driving and AI technologies.

High conductivity of 2D hydrogen substituted graphyne nanosheets for fast recovery NH3 gas sensors at room temperature

The current two-dimensional (2D) material based NH3 sensors generally suffer from low response values and sluggish recovery dynamics, which is resulted from their inferior conductivity. Herein, high conductivity (0.045 S/m) of 2D hydrogen substituted graphyne (HsGY) nanosheets are successfully synthesized employing aqueous/organic interface method and using them for the first time for the detection of NH3 at room temperature. The resultant gas sensing performance shows that the 2D HsGY nanosheets exhibit a high gas response value (4.9) to 100 ppm NH3 and fast recovery time (108 s) at the room temperature. The NH3 gas sensing mechanism is discussed by utilizing density functional theory (DFT) calculations. The present study provides novel gas sensing material for the development of high-performance room temperature NH3 sensors.

Interface debonding defect detection for CFST columns based on EMI measurements: Experiment, numerical simulation and blind inspection in practice

Concrete-filled steel tube (CFST) members have been widely used in skyscrapers and long-span bridges. Non-uniformly distributed hydration heat during curing, inadequate compaction during construction and unavoidable shrinkage and creep of mass concrete in service most likely lead to interface debonding defects between concrete core and steel tube, which has been a common concern. The development of effective non-destructive inspection methods for interface bonding condition of existing CFST members is critical. In this study, an interface debonding defect detection method based on electromechanical impedance (EMI) measurement using surface-mounted piezoelectric-lead-zirconate-titanate (PZT) sensors is proposed at first. Then, experimental study on the feasibility of the proposed approach is carried out with scaled CFST specimens with artificially mimicked interface debonding defects. EMI of surface-mounted PZT sensors at different frequency bands are measured and compared to verify the detectability of the proposed approach for the mimicked interface debonding defects. Thirdly, a multi-physics CFST-PZT coupling finite element model (FEM) with interface debonding defects is established, and EMI of surface-mounted PZT sensors at different locations is simulated. The influence of interface debonding defects on EMI measurements is illustrated. Finally, a blind inspection on the interface bonding condition of selected CFST columns in an existing skyscraper in service using the proposed approach is carried out. Both bonding and debonding defect in the tested CFST columns are detected correctly and validated with drilling hole observation. Experimental, numerical and engineering application results show the proposed approach is effective for interface debonding detection of CFST members and sensitive to minor debonding defect of 0.3 mm in CFST members.

Measuring the usability effectiveness of using card menus and tree menus in school web applications

The aim of this research is to measure the usability effectiveness of a web application by using card menus and tree menus using user-friendly criteria and access speed as indicated by the number of clicks made by the user. The method used in this research is the Task-centered User Interface method, where this method allows for planning and evaluating the arrangement of the interface according to user needs. There are four stages in this method, including user identification by conducting needs analysis, the second phase is user interface design. The third phase is the implementation of the card menu and tree menu design, and the fourth face is testing the usability and effectiveness requirements. From the research that has been carried out regarding measuring the effectiveness of using card menus, it is more effective to use than tree menus because you can directly lift the menu and access it. Meanwhile, for usability, the card menus have a higher usability index than the tree menus. Meanwhile, for usability measurements carried out by direct observation and distributing questionnaires, the resulting percentage of user understanding, ease, and speed for the card menu display was 87% and for the tree menu was 60% so that the card menu display was more accepted by users than the tree menu. The new thing provided by the results of this research is in the form of suggestions that can be used by web application developers to use the right type of menu in building web-based applications with the same specifications as in the case of school finance applications.

A novel surface-derivative-free of jumps AIIM with triangulated surfaces for 3D Helmholtz interface problems

Triangular surface-based 3D IIM (Immersed Interface Method) algorithms face major challenges due to the need to calculate surface derivative of jumps. This paper proposes a fast, easy-to-implement, surface-derivative-free of jumps, augmented IIM (AIIM) with triangulated surfaces for 3D Helmholtz interface problems for the first time, which combines the simplified AIIM with domain decomposed and embedding techniques. The computational domain is divided into sub-domains along the interface and the solutions of sub-domains are continuously extended into larger regular domains by embedding. The jumps in normal derivative of solution along the interfaces in the extended domains are introduced as unknowns to impose the original jump relations. The original problem is simplified into Helmholtz interface problems with constant coefficients by coupling them with the augmented equation, which is then solved using fast simplified AIIM. This approach eliminates the need to compute surface derivatives of jumps, making implementation of 3D IIM based on triangulated surfaces fairly simple. Numerical results demonstrate that the algorithm is efficient and can achieve the overall second-order accuracy.

Investigation on shear behavior of the interface between engineered cementitious composites and normal-strength concrete

Engineering cementitious composites (ECC), possessing excellent mechanical properties for good durability, can be applied to repair and strengthen reinforced concrete structures. In the present study, the interface shear behavior between ECC and normal-strength concrete was studied. Thirty bonded joint specimens were fabricated and subjected to push-out direct-shear tests. The construction methods of ECC mixture (precast and cast-in-place), ECC strength, and interface bonding methods (i.e., Epoxy resin, UHPC, cast-in-place ECC, cast-in-place ECC with chiseling, and bolts) were investigated. The results indicated that interface bonding methods have a significant influence on the failure modes and interface shear strength between ECC and existing concrete. There were three failure modes: interface debonding, interface debonding converted to concrete fracture, and concrete matrix destruction failure. Epoxy resin bonded specimens exhibited the highest shear strength, and cast-in-place ECC bonded specimens showed the lowest shear strength. Moreover, the shear performance of the ECC and the normal-strength concrete interface was analyzed in terms of interfacial shear strength and shear stiffness, bond-slip curve, and shear transfer mechanism. Finally, an analytical model for estimating the interfacial shear strength considering the interfacial bonding methods was established, with its predictions having high accuracy.

Precise detection of awareness in disorders of consciousness using deep learning framework

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC. We initiated our research with a benchmark dataset comprising 140 participants, including 76 unresponsive wakefulness syndrome (UWS), 25 minimally conscious state (MCS), and 39 Controls, from three independent sites. We developed a cascade 3D EfficientNet-B3-based deep learning framework tailored for discriminating MCS from UWS patients, referred to as “DeepDOC”, and compared its performance against five state-of-the-art machine learning models. We also included an independent dataset consists of 11 DOC patients to test whether our model could identify patients with cognitive motor dissociation (CMD), in which DOC patients were behaviorally diagnosed unconscious but could be detected conscious by brain computer interface (BCI) method. Our results demonstrate that DeepDOC outperforms the five machine learning models, achieving an area under curve (AUC) value of 0.927 and accuracy of 0.861 for distinguishing MCS from UWS patients. More importantly, DeepDOC excels in CMD identification, achieving an AUC of 1 and accuracy of 0.909. Using gradient-weighted class activation mapping algorithm, we found that the posterior cortex, encompassing the visual cortex, posterior middle temporal gyrus, posterior cingulate cortex, precuneus, and cerebellum, as making a more substantial contribution to classification compared to other brain regions. This research offers a convenient and accurate method for detecting covert awareness in patients with MCS and CMD using rs-fMRI data.

Prediction method of oil-water interface between injection and production wells in fault-controlled fractured-cavity reservoirs

Prediction method of oil-water interface between injection and production wells in fault-controlled fractured-cavity reservoirs

Deep Metric Learning With Locality Sensitive Mining for Self-Correcting Source Separation of Neural Spiking Signals.

Automated source separation algorithms have become a central tool in neuroengineering and neuroscience, where they are used to decompose neurophysiological signal into its constituent spiking sources. However, in noisy or highly multivariate recordings these decomposition techniques often make a large number of errors. Such mistakes degrade online human-machine interfacing methods and require costly post-hoc manual cleaning in the offline setting. In this article we propose an automated error correction methodology using a deep metric learning (DML) framework, generating embedding spaces in which spiking events can be both identified and assigned to their respective sources. Furthermore, we investigate the relative ability of different DML techniques to preserve the intraclass semantic structure needed to identify incorrect class labels in neurophysiological time series. Motivated by this analysis, we propose locality sensitive mining, an easily implemented sampling-based augmentation to typical DML losses which substantially improves the local semantic structure of the embedding space. We demonstrate the utility of this method to generate embedding spaces which can be used to automatically identify incorrectly labeled spiking events with high accuracy.

In Rat Organotypic Hippocampal Slice Cultures, Conventional Antiepileptic Medications are Unable to Inhibit Epileptiform Activity

Context and Goal: Prior research has shown that organotypic hippocampal slice cultures (OHSCs) can elicit tonic-clinic seizure-like events (SLEs), which resemble the electroencephalographic correlates of limbic seizures in humans and animals. We have investigated whether OHSCs can be used as in vitro models of limbic seizures to research seizures processes and vetting novel antiepileptic substances. Experimental Strategy: The interface method was used to cultivate OHSCs. Under submerged conditions, the levels of extracellular potassium and neuronal activity were observed. Lowering magnesium concentrations or administering the potassium channel blocker 4-aminopyridine both caused SLEs. Analysis was done on the impact of common antiepileptic medications (AEDs) on SLEs, including carbamazepine, phenytoin, valproic acid, clonazepam, diazepam, and phenobarbital sodium. Important Outcomes: AEDs did not stop the over 93% of OHSCs from happening induction of SLEs or cease current seizure activity even in the presence of hazardous dosages. The postnatal age at explanation (P2–P10), the manner of seizure provocation, and the length of in vitro cultivation (2 months) had no bearing on this chemoresistance. GABAA-agonist muscimol or glutamate antagonists were able to reversibly block SLEs. Inferences and Conclusions: Unlike animal models of thermoresistant seizures, where responders and nonresponses may only be distinguished after an experiment, we describe an easy to set up in vitro model of tonic-clinic SLEs that is a priori thermoresistant. OHSCs may be useful for investigating the mechanisms underlying medication-resistant seizures and for the discovery of novel anticonvulsive substances that may one day be used to treat drugresistant epilepsy.

Experimental and numerical study on projectile impact damage of EBC-SiC/SiC

The ingested particles or debris will cause high-speed & low-energy impact to the hot end components of aeroengine. Few literature focus on the projectile impact of SiC/SiC with Environmental Barrier Coating(EBC). The impact of 2 mm projectile was specially studied for Si/Yb2Si2O7/Yb2SiO5-SiC/SiC. Gas gun system was used to conduct impact testing at the speed of 3 m/s∼353m/s. The optical microscope, Scanning Electronic Microscope(SEM), micro CT were used to observe the impact and tension after impact(TAI) damage. For TAI, Digital Image Correlation (DIC) was used to conduct the full-field strain detection around the impact point. Meanwhile, the Smoothed Particle Hydrodynamics (SPH) methodology was programmed in C++ and developed to simulate SiC/SiC impact problem by introducing modified Hashin-Rotem criteria, extending interface method to 3D and adding GPU accelerated algorithm. The results indicate that threshold velocities of EBC huge peeling and SiC/SiC penetration are different, TAI residual strength also has extinct threshold at the velocity of 246 m/s with 37.1% declining extent, and the impact pit depth of SPH simulation is in good agreement with the experiment.

Graphdiyne Preparation and Application in Photocatalytic Hydrogen Evolution.

Graphdiyne (GDY) is a new two-dimensional carbon network material composed of sp2 hybrid carbon and sp hybrid carbon conjugation. It has unique physical and chemical properties, such as high porosity, good electrical conductivity, high carrier mobility, adjustable band gap, and so on. The preparation of GDY and GDY derivatives by adjusting physical and chemical methods and changing monomers has become the key material in the fields of photocatalysis, energy storage, life science, and so on. In this paper, new methods for controllable growth of GDY are reviewed, including liquid phase chemical classical total synthesis, chemical vapor deposition, the interface method, the explosion method, and the mechanically driven ball milling method. FT-IR, Raman, NMR, and XAS are the main means to characterize the structure of GDY. Finally, the representative application of GDY in the field of photocatalytic hydrogen evolution is summarized, and its future development has been explored.

A conservative sharp interface method for incompressible viscous two-phase flows with topology changes and large density ratio

Topology change of interfaces often leads to unresolved interface structures such as tiny droplets/bubbles, which requires the regularization of the order parameter and consequently causes artificial modification of volume fraction of the fluids. This could give rise to unphysical oscillation of pressure and cause the failure of computation, in particular for two-phase flows involving large density ratio. We develop a robust conservative sharp-interface method for incompressible viscous two-phase flows with topology changes and large density ratio. The method consists of a cut-cell meshing approach that dynamically generates unstructured meshes in the vicinity of the interface, a second-order finite volume scheme in the Arbitrary Lagrangian–Eulerian framework, and a projection method. The jump conditions at the interfaces are incorporated into the calculation of fluxes at the cell faces of the unstructured meshes that coincide with the reconstructed interfaces, to ensure that they are strictly satisfied at the interface. Unlike a pseudo-compressible formulation used in the previous study, the projection method prevents the oscillation of pressure in the presence of topology change. Special treatments are proposed to further improve the robustness of the method when dealing with unresolved interface structures, including removal of tiny droplets, adjustment of spatial discretization and restriction of the maximum curvature calculated. In such a way, two-phase flows involving topology change and large density ratio can be numerically resolved in a sharp-interface, efficient and robust manner. The performance of the proposed method is systematically examined by a series of numerical tests, including spurious currents, oscillation of a suspended droplet, droplet deformation in shear flows, breakup of a liquid thread, rising bubbles and partial coalescence of a droplet with a pool. The numerical results are compared against analytical solution, benchmark results or experimental data, and good agreement has been achieved.

Controlling gas–liquid flow and enhancing heat transfer in a T-junction microchannel by wettability-engineered walls

Characteristics of gas–liquid flow and heat transfer in a cross-flow T-junction microchannel with wettability-engineered walls are numerically investigated in this paper. The validated diffuse interface method is adopted for interface capture. First, the effects of wall wettability on bubble formation and transportation are studied. Three flow patterns are observed due to different combinations of the bottom and the top wall contact angles. On this basis, two methods are proposed to enhance the heat transfer. One is to increase the two-phase interfacial contact area by dividing the microchannel into three functional regions, which can promote the heat exchange at the two-phase interface. The other is to increase the velocity fluctuation intensity by alternating the contact angle along the channel, which can enhance mixing between the hot liquid layer adjacent to the wall and the cool liquid core. These two methods are applicative for steady and unsteady problems, respectively. The flow states, velocity vectors, and streamlines are used to analyze the fluid and thermal mixing mechanism. Meanwhile, a quantitative comparison of the wall temperature is made at a given wall heat flux. The obtained results can provide fresh insights into the gas–liquid flow control and the heat transfer enhancement in a microchannel, which are valuable for the design of microreactors and radiators.

Human-Induced Vibration Control of Floor Structures Using MTMD System Optimized by MATLAB-SAP2000 Interface

Under human-induced excitations, a floor structure may suffer excessive vibrations due to its large span and low damping ratio. Vertical vibrations, in particular, can become intolerable during resonance events. A tuned mass damper (TMD) is a widely used single-degree-of-freedom dynamic vibration absorber. To enhance the serviceability of a floor structure, a multiple TMD (MTMD) system finds broad application. The parameters of the MTMD must be carefully designed to achieve satisfactory performance. However, existing studies often employ a simplified model of the floor structure with closely spaced modes to optimize the parameters of MTMD. Nonetheless, an oversimplified floor model can lead to a reduction in its control effect. To solve this problem, this study utilizes the OAPI facility of SAP2000 to build a connection with MATLAB. A multi-objective optimization algorithm based on the artificial fish swarm algorithm (AFSA) for MTMD is developed in MATLAB, while the finite element model of a real floor structure is built in SAP2000. The locations of the MTMD system are initially specified in SAP2000 and, through the proposed MATLAB–SAP2000 interface, data can be exchanged between them. Based on the structural dynamic responses to external excitations in SAP2000, the optimization process for the MTMD is carried out in MATLAB. Concurrently, the parameters of the MTMD in SAP2000 are iteratively adjusted until they reach their final optimal values. To underscore the enhancements brought about by the proposed interface and optimization method, a comparative case study is conducted. A group of MTMDs, optimized using a conventional method, is presented for reference. The numerical results indicate that, overall, the proposed MTMD system exhibits superior control effectiveness and robustness.

Amorphous Nickel Nanofilms for Efficient Hydrogen Generation from ammonia borane

AbstractClean and sustainable hydrogen production through liquid hydrogen storage material requires highly active and stable earth‐abundant non‐noble metal to replace expensive and rare noble metals. Herein, nickel nanofilms (Ni/NiO‐NFs) were prepared by the ionic liquid/water interface route. The cationic carbon chain length of the ionic liquid affects the phase composition of the nickel nanofilm, and the ionic liquid with [OMIm][PF6] as the anion has good thermal stability during the synthesis process. The efficiency of Ni/NiO‐NFs catalysts was tested by comparative kinetic analysis of the AB hydrolysis for hydrogen production. The as‐prepared Ni/NiO‐NFs catalyst exhibits excellent hydrogen generation performances, including a hydrogen production rate (2917 ml min−1 gNi−1), and a low activation energy (48.1 kJ/mol). The transition of nickel oxide to metallic nickel and the destruction of the catalyst structure is responsible for the decreased durability. This work highlights the significance of amorphous nanofilms catalysts via the ionic interface method on the regulation of activity for AB hydrolysis.

A new MIB-based time integration method for transient heat conduction analysis of discrete and continuous systems

By incorporating the matched interface and boundary (MIB) method into time integration computation, a new MIB-based time integration (MIBTI) approach is proposed for solving transient heat conduction problems in this work. Indeed, this is a truly effective time-domain MIB method that can directly discretize space and time derivatives, and the transient heat conduction problem (an initial-value problem) is transformed into a pseudo-space boundary-value problem. The initial and final time points are regarded as boundary points in the transformed space domain. Two algorithms are developed to deal with the final time point. Unlike conventional recursive schemes for time integration, all unknown variables can be determined by solving the transformed boundary-value problem in the present approach. Various discrete and continuous systems without and with internal heat sources under different boundary conditions are considered to examine the working performance of the proposed method. The applicability of the time stability criterion in the conventional recursive schemes to the proposed method is also discussed. It is found that excellent numerical stability and convergence can be achieved by using the present MIBTI method for solving transient heat conduction problems.

An integrated microfluidic platform for on-demand single droplet dispenser with high accuracy by electrohydrodynamic (EHD) printing technique

Droplet microfluidics has revolutionized single-cell analysis, allowing for ultra-high-throughput sorting of droplets to meet the demands of single-cell sorting. However, accurately and efficiently dispensing target droplets into specific containers for downstream analysis has remained a challenge. Here, we present an integrated microfluidic droplet dispenser based on the electrohydrodynamic (EHD) principle, capable of on-demand single droplet dispensing with high accuracy. Our system uses optical signal activation and EHD actuation to isolate and dispense droplets. The microfluidic droplet auto dispenser consists of four main modules: a pump-drive chip module, an optical automatic signal recognition module, a high voltage control module, and an automated X-Y translation stage module. By optimizing the chip structure and voltage parameter, this platform successfully isolates single Escherichia coli (E. coli) cells onto a Petri dish for downstream cultivation and heterogeneity analysis. In addition, the dispenser microfluidic system dispenses the sorted droplets in a "one droplet, one well" manner, providing an automated method for droplet interface from the micro- to macro- platform. This dispenser system provides a platform for phenotypic screening of single colony pick and single cell analysis

A novel steepness-adjustable harmonic volume-of-fluid method for interface capturing

The algebraic volume-of-fluid (VOF) method based on the construction strategy of switching technique has received extensive attention recently. However, all the previous algebraic VOF methods were constructed by combining different methods of compressible differencing scheme (CDS) and the high resolution scheme (HRS), which would switch back and forth in most cases. Thus the final algebraic VOF method usually becomes to be complicated, and the numerical instabilities would be increased. In this paper, a novel algebraic VOF method, without the operations of switching back and forth, is constructed within a unified framework of the steepness-adjustable harmonic (SAH) scheme (He et al. (2022) [33]). A thorough validation of the present method is conducted, examining the pure advection of the interface indicator function. The results indicate that the present method can resolve the interface capturing with substantially low numerical diffusion and low numerical oscillations.