Search Results (74)

Over-the-air federated learning (Air-FL) has emerged as a promising paradigm that integrates communication and learning, which offers significant potential to enhance model training efficiency and optimize communication resource utilization. This paper addresses the challenge of interference management in multi-cell Air-FL systems, focusing on parallel multi-task scenarios where each cell independently executes distinct training tasks. We begin by analyzing the impact of aggregation errors on local model performance within each cell, aiming to minimize the cumulative optimality gap across all cells. To this end, we formulate an optimization framework that jointly optimizes device transmit power and denoising factors. Leveraging the Pareto boundary theory, we design a centralized optimization scheme that characterizes the trade-offs in system performance. Building upon this, we propose a distributed power control optimization scheme based on interference temperature (IT). This approach decomposes the globally coupled problem into locally solvable subproblems, thereby enabling each cell to adjust its transmit power independently using only local channel state information (CSI). To tackle the non-convexity inherent in these subproblems, we first transform them into convex problems and then develop an analytical solution framework grounded in Lagrangian duality theory. Coupled with a dynamic IT update mechanism, our method iteratively approximates the Pareto optimal boundary. The simulation results demonstrate that the proposed scheme outperforms baseline methods in terms of training convergence speed, cross-cell performance balance, and test accuracy. Moreover, it achieves stable convergence within a limited number of iterations, which validates its practicality and effectiveness in multi-task edge intelligence systems. Full article

As air transportation demand continues to rise, congestion in air route networks has seriously compromised the safe and efficient operation of air traffic. Few studies have examined the spatiotemporal characteristics of congestion propagation under different time lag conditions. To address this gap, this study proposes a cross-segment congestion-propagation causal time-lag analysis framework. First, to account for the interdependency across segments in air route networks, we construct a point–line congestion state assessment model and introduce the FCM-WBO algorithm for precise congestion state identification. Next, the Multi-Channel Attention DSNG-BiLSTM model is designed to estimate the causal weights of congestion propagation between segments. Finally, based on these causal weights, two indicators—CPP and CPF—are derived to analyze the spatiotemporal characteristics of congestion propagation under various time lag levels. The results indicate that our method achieves over 90% accuracy in estimating causal weights. Moreover, the propagation features differ significantly in their spatiotemporal distributions under different time lags. Spatially, congestion sources tend to spread as time lag increases. We also identify segments that are likely to become overloaded, which serve as the primary receivers of congestion. Temporally, analysis of time-lag features reveals that because of higher traffic flow during peak periods, congestion propagates 36.92% more slowly than during the early-morning hours. By analyzing congestion propagation at multiple time lags, controllers can identify potential congestion sources in advance. They can then implement targeted interventions during critical periods, thereby alleviating congestion in real time and improving route-network efficiency and safety. Full article

Polyethersulfone (PES) has been widely used to fabricate hollow-fiber ultrafiltration membranes due to its good oxidative, thermal, and hydrolytic stability. Typical PES hollow-fiber membranes with a single bore have limited strength and may break under uneven pressure and vibration during membrane backwashing. Multi-channel hollow-fiber membranes have stronger breaking force due to their larger cross-sectional area, but fabricating them remains challenging due to the difficulty in controlling the phase inversion process. This study uses the vapor-induced phase separation (VIPS) method to fabricate a seven-channel PES hollow-fiber membrane, and the air gap and air relative humidity can help in membrane morphology control. Moreover, carboxylic graphene quantum dots (CGQDs) are first used in ultrafiltration membranes to increase membrane porosity and hydrophilicity. We found that the membrane prepared with a 7.5% CGQD mass fraction, a 10 cm air gap, and 99% relative humidity had the highest flux and porosity; the membrane pore size distribution was concentrated at 72 nm, and the pure water flux could reach 464 L·m⁻² h⁻¹·bar⁻¹. In the long-term filtration performance test, the membrane can reject more than about 15% TOC and 84% turbidity at 50 L·m⁻² h⁻¹ flux, confirming its stability for water purification applications. Full article

Restrike frequently occurs during the positive leader development of long-air-gap discharges. At present, however, its detailed physical process and mechanism remain unclear. To investigate the physical mechanism of restrike, experiments were conducted in a 6 m rod–plate air gap under positive impulses with a wavefront time of 1 ms, and the process of restrike was observed during discharge. Our experimental results showed that significant luminescence appeared at the tip of the leader channel for a relatively long time during the discharge relaxation process before restrike occurred, and the luminescence became increasingly intense as the applied voltage increased until restrike occurred. By analyzing the composition of the charged particles inside the leader channel, we inferred that, during the relaxation process, the positive ions inside the leader channel migrate toward and concentrate in the leader channel tip as the applied electrical field increases, and the concentration of positive ions at the leader channel head distorts and enhances the local field, which then induces streamer corona discharge, leading to the luminescence of the leader channel. The observations, evidence, and discussion presented herein could provide a valuable reference for more effectively understanding the physical mechanism of restrike. Full article

Virtual reality (VR)/the metaverse is transforming into a ubiquitous technology by leveraging smart devices to provide highly immersive experiences at an affordable price. Cryptographically securing such augmented reality schemes is of paramount importance. Securely transferring the same secret key, i.e., obfuscated, between several parties is the main issue with symmetric cryptography, the workhorse of modern cryptography, because of its ease of use and quick speed. Typically, asymmetric cryptography establishes a shared secret between parties, after which the switch to symmetric encryption can be made. However, several SoTA (State-of-The-Art) security research schemes lack flexibility and scalability for industrial Internet-of-Things (IoT)-sized applications. In this paper, we present the full architecture of the PRIVocular framework. PRIVocular (i.e., PRIV(acy)-ocular) is a VR-ready hardware–software integrated system that is capable of visually transmitting user data over three versatile modes of encapsulation, encrypted—without loss of generality—using an asymmetric-key cryptosystem. These operation modes can be optical character-based or QR-tag-based. Encryption and decryption primarily depend on each mode’s success ratio of correct encoding and decoding. We investigate the most efficient means of ocular (encrypted) data transfer by considering several designs and contributing to each framework component. Our pre-prototyped framework can provide such privacy preservation (namely virtual proof of privacy (VPP)) and visually secure data transfer promptly (<1000 ms), as well as the physical distance of the smart glasses (∼50 cm). Full article

Acoustic sensing technology has attracted significant attention across various fields, including mechanical fault early warning and wireless communication, due to its high information density and advantages in remote wireless applications. However, environmental noise reduces the signal-to-noise ratio (SNR) in traditional acoustic systems. In response, this article proposes a novel Z-shaped channel gradient metamaterial (ZCGM) that leverages strong wave compression effects coupled with effective medium theory to detect weak signals in complex environments. The properties of the designed metamaterials were verified by theoretical derivation and finite element simulation of the model. Compared to conventional linear gradient acoustic metamaterials (GAMs), ZCGM demonstrates significantly superior performance in acoustic enhancement, with a lower capture frequency. Furthermore, the structure exhibits flexible tunability in its profile. In addition, the center frequency of each actual air gap is determined in this paper based on the swept frequency signal test. Based on this center frequency, a preset specific harmonic acoustic signal is used as an emission source to simulate the actual application scenario, and experiments are constructed and conducted to verify the performance of the designed metamaterials. The results consistently show that ZCGM has distinct advantages and promising application prospects in the detection, enhancement, and localization of weak acoustic signals. Full article

Mixtures of hydrogen with common hydrocarbon fuels are considered viable for reducing carbon footprint in modern industry, power production, and transportation. The addition of hydrogen alters the kinetics and thermophysical properties of the mixtures, as well as the composition and properties of combustion products, requiring detailed research into the features of flame propagation in hydrogen-enriched hydrocarbon–air mixtures. Of particular interest are also the safety aspects of such fuels. In this paper, experimental results are presented on the premixed laminar flame propagation in channels formed by two closely spaced plates (Hele-Shaw cell), with the internal straight walls forming a diverging (diffuser) channel with the opening angles between 5 and 25 degrees. Methane–hydrogen–air mixtures with the hydrogen relative contents of 0%, 25%, and 50% and global equivalence ratio of unity were ignited by a spark near the closed narrow end of the channel. Experiments were performed with the gap width of 3.5 mm; video recordings were processed in order to determine the quantitative features of the flame front propagation (leading and trailing point coordinate, coordinates of the cusps, cell sizes and shapes). The main features of flame propagation (fast initial expansion, development of cellular flame, self-induced longitudinal oscillations) are obtained and compared to clarify the effect of hydrogen contents in the fuel and channel geometry (gap width, opening angle). Full article

In response to the typical decay and fracture defects of composite insulators, a three-dimensional electrically and thermally coupled simulation physical model was constructed based on the finite element method, and the local electric field distortion and temperature rise were analyzed. The study confirms that the insulator interface’s axial electric and thermal fields show a U-shaped curve; the interface field strength is the largest. There is an electric field gradient difference between the mandrel and the sheath, and the thermal field is concentrated at the mandrel and the interface. The field strength at the edge of the defect is the largest, the aberrant electric field at the defect shows a sawtooth shape, and the temperature rise is concentrated in the defect area. The degradation is fast in the air gap, the etching hole diameter direction, and the carbonation channel axial direction. The larger the defect volume, the larger the aberration in the electric field and temperature rise. Water vapor air gaps, breakdown holes, and carbonized channels have the most pronounced electric field and temperature changes. The functional relationship between electric field aberration, temperature rise, and defect volume is established. The results provide a basis for the protection of insulator decay-like fracture. Full article

Demand is high for small, lightweight, and power-dense machines. However, as power increases and size decreases, rejecting losses becomes more difficult. Many novel cooling systems have been developed, which have allowed machines to be made smaller while increasing power. This paper proposes a cooling system making use of soft magnetic composite (SMC) cores to improve cooling specifically in a high-speed axial-flux machine via the use of an integrated cooling channel in the SMC core. A series of experiments on a prototype machine are performed and the experimental data are used to determine a set of parameters for the FEA thermal model. Using the thermal FEA model, a comparison is completed with a traditional closed cooling system using laminated steels and an attached cooling plate.The SMC machine is then simulated at speeds up to 160 krpm and currents up to 8 A. To achieve the same coil temperature between the two designs, the laminated steel model required 4 MPa contact pressure at 10 krpm and 5 MPa contact pressure at 20 krpm. At the same time, the novel design removed approximately 20% more heat per shear air gap surface area and approximately 15% more heat per total machine surface area than the version with the attached cooling plate. Extending the operating range of the model to 160 krpm demonstrated that the maximum temperature rise remained below 180 °C. Full article

To protect important data and files, people often use air gap isolation, also known as air gap separation, to block external threats. However, internal networks may still introduce pollution due to supply chain contamination, human error, or social engineering. Although internal devices cannot directly communicate with the outside world. This paper proposes a new technology called Bit Sufi-Dance that utilizes electricity meters and optical devices to detect exfiltrated data. Most electricity meters have power indicator mechanical turntables or LED lights which can be indirectly controlled by the device’s power consumption oscillation. This allows for information encoding and the extraction of data from the air-gapped computer. It is important to note that this exfiltration channel does not require any hardware or firmware modifications and cannot be detected by existing Data Leakage Prevention (DLP) systems. The article discusses its design and implementation issues while evaluating it using different types of electricity meters. Our experiment demonstrates that data can be exfiltrated from the air-gap isolated computer through an electricity meter at a bit rate of 101 b/h. Finally, we assess this security threat and discuss defense mechanisms and preventive measures. Full article

The self-circulating casing treatment can effectively expand the stable working range of the compressor, with little impact on its efficiency. With a single-stage transonic axial flow compressor NASA (National Aeronautics and Space Administration) Stage 35 as the research object, a multi-channel unsteady numerical calculation method was used here to design three types of self-circulating casing treatment structures: 20% Ca (axial chord length of the rotor blade tip), 60% Ca, and 178% Ca (at this time, the bleed position is at the stator channel casing) from the leading edge of the blade tip. The effects of these three bleed positions on the self-circulating stability expansion effect and compressor performance were studied separately. The calculation results indicate that the further the bleed position is from the leading edge of the blade tip, the weaker the expansion ability of the self-circulating casing treatment, and the greater the negative impact on the peak efficiency and design point efficiency of the compressor. This is because the air inlet of the self-circulating casing with an air intake position of 20% Ca is located directly above the core area of the rotor blade top blockage, which can more effectively extract low-energy fluid from the blockage area. Compared to the other two bleed positions, it has the greatest inhibitory effect on the leakage vortex in the rotor blade tip gap and has the strongest ability to improve the blockage at the rotor blade tip. Therefore, 20% Ca from the leading edge of the blade tip has the strongest stability expansion ability, achieving a stall margin improvement of 11.28%. Full article

This article provides a comprehensive overview of ice-jam flood forecasting methodologies applicable to rivers during freezing. It emphasizes the importance of understanding river ice processes and fluvial geomorphology for developing a freeze-up ice-jam flood forecasting system. The article showcases a stochastic modelling approach, which involves simulating a deterministic river ice model multiple times with varying parameters and boundary conditions. This approach has been applied to the Exploits River at Badger in Newfoundland, Canada, a river that has experienced several freeze-up ice-jam floods. The forecasting involves two approaches: predicting the extent of the ice cover during river freezing and using an ensemble method to determine backwater flood level elevations. Other examples of current ice-jam flood forecasting systems for the Kokemäenjoki River (Pori, Finland), Saint John River (Edmundston, NB, Canada), and Churchill River (Mud Lake, NL, Canada) that are operational are also presented. The text provides a detailed explanation of the processes involved in river freeze-up and ice-jam formation, as well as the methodologies used for freeze-up ice-jam flood forecasting. Ice-jam flood forecasting systems used for freeze-up were compared to those employed for spring breakup. Spring breakup and freeze-up ice-jam flood forecasting systems differ in their driving factors and methodologies. Spring breakup, driven by snowmelt runoff, typically relies on deterministic and probabilistic approaches to predict peak flows. Freeze-up, driven by cold temperatures, focuses on the complex interactions between atmospheric conditions, river flow, and ice dynamics. Both systems require air temperature forecasts, but snowpack data are more crucial for spring breakup forecasting. To account for uncertainty, both approaches may employ ensemble forecasting techniques, generating multiple forecasts using slightly different initial conditions or model parameters. The objective of this review is to provide an overview of the current state-of-the-art in ice-jam flood forecasting systems and to identify gaps and areas for improvement in existing ice-jam flood forecasting approaches, with a focus on enhancing their accuracy, reliability, and decision-making potential. In conclusion, an effective freeze-up ice-jam flood forecasting system requires real-time data collection and analysis, historical data analysis, ice jam modeling, user interface design, alert systems, and integration with other relevant systems. This combination allows operators to better understand ice jam behavior and make informed decisions about potential risks or mitigation measures to protect people and property along rivers. The key findings of this review are as follows: (i) Ice-jam flood forecasting systems are often based on simple, empirical models that rely heavily on historical data and limited real-time monitoring information. (ii) There is a need for more sophisticated modeling techniques that can better capture the complex interactions between ice cover, water levels, and channel geometry. (iii) Combining data from multiple sources such as satellite imagery, ground-based sensors, numerical models, and machine learning algorithms can significantly improve the accuracy and reliability of ice-jam flood forecasts. (iv) Effective decision-support tools are crucial for integrating ice-jam flood forecasts into emergency response and mitigation strategies. Full article

Studying air Urban Heat Islands (AUHI) in African cities is limited by building height data scarcity and sparse air temperature (T_air) networks, leading to classification confusion and gaps in T_air data. Satellite imagery used in surface UHI (SUHI) applications overcomes the gaps which befall AUHI, thus making it the primary focus of UHI studies in areas with limited T_air stations. Consequently, we used Landsat 30 m imagery to analyse SUHI patterns using Land Surface Temperature (LST) data. Local climate zones (LCZ) as a UHI study tool have been documented to not result in distinct thermal environments at the surface level per LCZ class. The goal in this study was thus to explore relationships between LCZs and LST patterns, aiming to create a building height (BH)-independent LCZ framework capable of creating distinct thermal environments to study SUHI in African cities where LiDAR data are scarce. Random forests (RF) classified LCZ in R, and the Single Channel Algorithm (SCA) extracted LST via the Google Earth Engine. Statistical analyses, including ANOVA and Tukey’s HSD, assessed thermal distinctiveness, using a 95% confidence interval and 1 °C threshold for practical significance. Semi-Automated Agglomerative Clustering (SAAC) and Automated Divisive Clustering (ADC) grouped LCZs into thermally distinct clusters based on physical characteristics and LST data internal patterns. Built LCZs (1–9) had higher mean LSTs; LCZ 8 reached 37.6 °C in Spring, with a smaller interquartile range (IQR) (34–36 °C) and standard deviation (SD) (1.85 °C), compared to natural classes (A–G) with LCZ 11 (A–B) at 14.9 °C/LST, 17–25 °C/IQR, and 4.2 °C SD. Compact LCZs (2, 3) and open LCZs (5, 6), as well as similar LCZs in composition and density, did not show distinct thermal environments even with building height included. The SAAC and ADC clustered the 14 LCZs into six thermally distinct clusters, with the smallest LST difference being 1.19 °C, above the 1 °C threshold. This clustering approach provides an optimal LCZ framework for SUHI studies, transferable to different urban areas without relying on BH, making it more suitable than the full LCZ typology, particularly for the African context. This clustered framework ensures a thermal distinction between clusters large enough to have practical significance, which is more useful in urban planning than statistical significance. Full article

Even though the streamer process can be identified in nanoseconds and microseconds through experimental measurements, the breakdown time of air discharge is still unknown. The instability of electrons is suspected to be an attachment-instability phenomenon of the channel conductivity. We investigated breakdown time across milliseconds to better understand how the oxygen excitations of the 200–400 nm range influence a high-conductivity channel even with a weaker applied voltage. Experiments were performed with positive impulse voltages ranging from +42 to +75 kV in the step of +6 kV at a 3 cm gap between needle-to-plane electrodes in a horizontal configuration. A spectrometer with an integration time of 70 ms was used to capture the spectra during voltage discharge. The shortest breakdown time was found at +60 kV with 77 ns compared to +66, +72, and +75 kV. We conclude that the shorter breakdown time at +60 kV is primarily due to the oxygen-excited state in O IV at 262.999 nm. This state helps maintain electron flow by preventing electron loss, with a decay time of 2.5 µs, while releasing Joule heat at a temperature of 26,003 K, which optimizes conductivity. This process occurs before the recombination of the O I line at 777.417 nm, which has a significantly shorter decay time of 27 ns. Full article

To protect critical computing systems from network attacks, modern enterprises typically employ physical isolation measures to disconnect them from open networks such as the Internet. However, attackers can still infiltrate these closed networks through internal employees or supply chain vulnerabilities. This presents the primary challenge that attackers face: how to effectively manage and manipulate infected devices that are isolated from the external network. In this paper, we propose a new covert communication technology called HydraulicBridge, which demonstrates how air gap networks can communicate through covert water pressure-fluctuation channels. Specifically, we demonstrate how water pressure from water pipes can be used to communicate with infected hosts within an air gap network. Additionally, we provide experimental results demonstrating the feasibility of covert channels and test the communication speed in the experimental environment. Finally, we offer a forensic analysis and propose various methods for detecting and blocking this channel. We believe that this study provides a comprehensive introduction to previously unseen attack vectors that security experts should be aware of. Full article