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Graph neural networks (GNNs) are powerful models capable of managing intricate connections in non-Euclidean data, such as social networks, physical systems, chemical structures, and communication networks. Despite their effectiveness, the large-scale and complex nature of graph data demand substantial computational resources and high performance during both training and inference stages, presenting significant challenges, particularly in the context of embedded systems. Recent studies on GNNs have investigated both software and hardware solutions to enhance computational efficiency. Earlier studies on deep neural networks (DNNs) have indicated that methods like reconfigurable hardware and quantization are beneficial in addressing these issues. Unlike DNN research, studies on efficient computational methods for GNNs are less developed and require more exploration. This survey reviews the latest developments in quantization and FPGA-based acceleration for GNNs, showcasing the capabilities of reconfigurable systems (often FPGAs) to offer customized solutions in environments marked by significant sparsity and the necessity for dynamic load management. It also emphasizes the role of quantization in reducing both computational and memory demands through the use of fixed-point arithmetic and streamlined vector formats. This paper concentrates on low-power, resource-limited devices over general hardware accelerators and reviews research applicable to embedded systems. Additionally, it provides a detailed discussion of potential research gaps, foundational knowledge, obstacles, and prospective future directions. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of the dynamic parameters of a compact class passenger car powered by LPG/DME blends. The presented results are part of the research cycle of this vehicle, the purpose of which was to check the possibility of using DME (dimethyl ether) as an additive in the fuel mixture with LPG. In the presented part of the experimental research, the acceleration times of the vehicle under specific conditions were measured. On the basis of the obtained results, the relations between the average acceleration in the tested speed ranges, the fuel composition, and the degree of engine load were developed. The results of the analysis indicate that in the examined range of changes in the DME share in the fuel, comparable or higher acceleration values were obtained for all engine load levels. This confirms the usefulness of DME as a fuel component used to power SI engines. [ABSTRACT FROM AUTHOR]

Fully homomorphic encryption (FHE) has experienced significant development and continuous breakthroughs in theory, enabling its widespread application in various fields, like outsourcing computation and secure multi-party computing, in order to preserve privacy. Nonetheless, the application of FHE is constrained by its substantial computing overhead and storage cost. Researchers have proposed practical acceleration solutions to address these issues. This paper aims to provide a comprehensive survey for systematically comparing and analyzing the strengths and weaknesses of FHE acceleration schemes, which is currently lacking in the literature. The relevant researches conducted between 2019 and 2022 are investigated. We first provide a comprehensive summary of the latest research findings on accelerating FHE, aiming to offer valuable insights for researchers interested in FHE acceleration. Secondly, we classify existing acceleration schemes from algorithmic and hardware perspectives. We also propose evaluation metrics and conduct a detailed comparison of various methods. Finally, our study presents the future research directions of FHE acceleration, and also offers both guidance and support for practical application and theoretical research in this field. [ABSTRACT FROM AUTHOR]

Introduction: Navigation satellite systems can fail to work or work incorrectly in a number of conditions: signal shadowing, electromagnetic interference, atmospheric conditions, and technical problems. All of these factors can significantly affect the localization accuracy of autonomous driving systems. This emphasizes the need for other localization technologies, such as Lidar. Methods: The use of the Kalman filter in combination with Lidar can be very effective in various applications due to the synergy of their capabilities. The Kalman filter can improve the accuracy of lidar measurements by taking into account the noise and inaccuracies present in the measurements. Results: In this paper, we propose a parallel Kalman algorithm in three- dimensional space to speed up the computational speed of Lidar localization. At the same time, the initial localization accuracy of the latter is preserved. A distinctive feature of the proposed approach is that the Kalman localization algorithm itself is parallelized, rather than the process of building a map for navigation. The proposed algorithm allows us to obtain the result 3.8 times faster without compromising the localization accuracy, which was 3% for both cases, making it effective for real-time decision-making. Discussion: The reliability of this result is confirmed by a preliminary theoretical estimate of the acceleration rate based on Ambdahl's law. Accelerating the Kalman filter with CUDA for Lidar localization can be of significant practical value, especially in real-time and in conditions where large amounts of data from Lidar sensors need to be processed. [ABSTRACT FROM AUTHOR]

Backpacks are common devices for carrying external posterior loads. However, relatively little is known about how these external loads affect the ability to recover from balance loss. In this exploratory investigation, 16 young adults (8 female, 8 male) performed forward and backward lean-and-release balance recovery trials, while wearing a backpack that was unloaded or loaded (at 15% of individual body weight). We quantified the effects of backpack loading on balance recovery in terms of maximum recoverable lean angles, center-of-mass kinematics, and temporal-spatial stepping characteristics. Mean values of maximum lean angles were 20° and 9° in response to forward and backward perturbations, respectively. These angles significantly decreased when wearing the additional load for only backward losses of balance. During backward losses of balance, the additional load decreased peak center-of-mass velocity and increased acceleration by ∼10 and 18% respectively, which was accompanied by ∼5% faster stepping responses and steps that were ∼9% longer, 11% higher, and had an ∼10% earlier onset. Thus, wearing a backpack decreases backward balance recovery ability and changes backward recovery stepping characteristics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The acceleration and deceleration (AD) motions are the basic motion modes of robot astronauts moving in a space station. Controlling the locomotion of the robot astronaut is very challenging due to the strong nonlinearity of its complex multi-body dynamics in a gravity-free environment. However, after training, humans can move well in space stations by pushing the bulkhead, and the motion mechanism of humans is a good reference for robot astronauts. The contribution of this study is modeling the human AD motion in a microgravity environment and proposing a human-like control method for robot astronauts moving in space stations. Specifically, the movement and contact force data of the human body during AD motion were collected on an air-floating platform. Through human AD modeling analysis, the mechanism of human motion is discovered, and semi-sinusoidal primitives of contact forces are proposed for AD motion. Then, a dynamic guidance model of human AD motion is built to complete motion planning under contact constraints, which is used as the expected model for the AD control of robot astronauts. Benefiting from the force primitives, accurate and safe planning of human-like AD motion can be completed. The characteristics and mechanism of human AD motion have been analyzed from the perspective of optimization. Lastly, based on the proposed dynamic guidance model, the AD motion policy is mapped to the robot astronaut system via a system control method based on the equivalent mapping of dynamic responses (force, velocity and pose). Through comparative analysis with real human motion data and simulation results under different conditions, the proposed AD control method can achieve human-like motion efficiently and stably. Even when confronted with errors in the robot's contact velocities and inertia parameters, the method can significantly reduce the motion errors while ensuring stability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 ISA. Published by Elsevier Ltd. All rights reserved.)

Compaction is a critical step in the construction of an asphalt mixture. To effectively compact an asphalt mixture, the locking point, which identifies the effective compaction, was introduced based on the change in volumes of the asphalt mixture during gyratory compaction. However, the existing definition of the locking point is solely dependent on the volumetric properties of compacted mixtures and may not be necessarily associated with the skeleton of the mixture. In this paper, the locking point for a compacted asphalt mixture was defined and determined using dynamic responses measured by a particle sensor. Gyratory compaction and field compaction tests were carried out with particle sensors embedded to analyze the evolution of the aggregates' dynamic responses. Then, a novel dynamic response rate of the change index Rs was proposed to represent the evolution process of the asphalt mixture compaction. The Superpave gyratory compactor (SGC) results show that the acceleration and rotation angle of the particle sensors varied during compaction and did not converge in the end. The SGC compaction process can be divided into three stages: the initial compaction stage, transition stage, and plateau stage based on the rate of stress (Rs). Meanwhile, the inflection point between the transition stage and plateau stage in the compaction curve was defined as the locking point. It was found that the locking point determined by the sensors in the middle of the compacted specimens was later than that determined by the gyratory compaction. The contact interlocking initiated at the bottom of a compacted specimen and moved upward. The field compaction test results of the particle sensors showed that the contact stress also had a significant trend of convergence after being compacted by a pneumatic-tired roller, which indicates that the test stress index based on the particle sensors could be used for the evaluation of compaction quality. [ABSTRACT FROM AUTHOR]

The range-Doppler algorithm (RDA), a key technique for generating synthetic aperture radar (SAR) images, offers high-resolution images but requires significant memory resources and involves complex signal processing. Moreover, the multitude of fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT) operations in RDA necessitates high bandwidth and lacks data reuse, leading to bottlenecks. This paper introduces a synthetic aperture radar dual in-line memory module (SARDIMM), which executes RDA operations near memory via near-memory processing (NMP), thereby effectively reducing memory accesses, execution time, and energy consumption. The embedded NMP module in SARDIMM optionally supports a combination of FFT, IFFT, and matched filter operations of the RDA for range and azimuth compression. The operator within the NMP module accelerates the FFT by performing two radix-2 single butterfly operations in parallel. The NMP module was implemented and validated on a Xilinx UltraScale+ field-programmable gate array (FPGA) using Verilog-HDL. The acceleration performance of RDA for images of various sizes was evaluated through a simulator modified with gem5 and DRAMSim3 and achieved a 6.34–6.93× speedup and 41.9–48.2% energy savings. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Konbin is the property of Air Force Institute of Technology (Instytut Techniczny Wojsk Lotniczych) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Kumite is a karate sparring competition in which two players face off and perform offensive and defensive techniques. Depending on the players, there may be preliminary actions (hereinafter referred to as "pre-actions"), such as pulling the arms or legs, lowering the shoulders, etc., just before a technique is performed. Since the presence of a pre-action allows the opponent to know the timing of the technique, it is important to reduce pre-actions in order to improve the kumite. However, it is difficult for beginners and intermediate players to accurately identify their pre-actions and to improve them through practice. Therefore, this study aims to construct a practice support system that enables beginners and intermediate players to understand their pre-actions. In this paper, we focus on the forefist punch, one of kumite's punching techniques. We propose a method to estimate the presence or absence of a pre-action based on the similarity between the acceleration data of an arbitrary forefist punch and a previously prepared dataset consisting of acceleration data of the forefist punch without a pre-action. We found that the proposed method can estimate the presence or absence of a pre-action in an arbitrary forefist punch with an accuracy of 86%. We also developed KARATECH as a system to support the practice of reducing pre-actions using the proposed method. KARATECH shows the presence or absence of pre-actions through videos and graphs. The evaluation results confirmed that the group using KARATECH had a lower pre-action rate.

A sleeper, or more generally a "bearer", moves vertically under a passing train load. The extent of this motion depends on the static and dynamic load of the train, the train speed, and the support conditions at the bearer and its neighbours. Excessive motion, typically from voiding see-sawing, low support stiffness or possibly excessive stiffness, or even too little stiffness, are all of interest to maintainers. Typically, problems arise around transition zones, switches and crossings, but plain track with poor support can also be a problem. Within the last decade, low-cost micro-electro-mechanical system (MEMS) accelerometers have been used to capture the time history of vertical motion for use in condition monitoring. Existing condition monitoring systems often overlook or sometimes even ignore the possibility of problematic data, which seem to be common in monitored locations. It is essential to understand whether such "bad" data require further attention. Three problematic sites are presented, focussing on examples where the acceleration was higher than expected or the computed displacement was not as expected. Potential causes include wheel defects, hammering of the ballast by a hanging bearer, or high acceleration at some structural resonant frequency. The present paper aims to show the challenges of using MEMS accelerometers to collect data for condition monitoring and offers insights into the sort of problematic data that may be collected from real sites. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the acceleration of a fast boat using a simulation model. Mathematical equations of ship motion dynamics with two types of propeller capabilities are developed using MATLAB and Simulink as simulation tools. The equations are extended to include the acting thrust, resistance, propeller's performance curves, and the PID governor curve for the acceleration manoeuvre. The application models the dynamic differential equations representing the vessel dynamics in one degree of freedom. MATLAB code was used to develop the ship acceleration as a multibody system. Modules of hydrodynamic forces, resistance, moments, and propeller performances were implemented to simulate the ship manoeuvring process. A comparison of the results for the boat's propulsion performance with two different propellers and the characteristics of the PID governor, which controls the fuel dose in the gas turbines, was carried out. We present a summary including a comparative analysis of the results for the boat dynamics with and without the PID governor. The results obtained here confirm significant discrepancies between the results of numerical simulations with and without the PID governor. [ABSTRACT FROM AUTHOR]

A dynamic analysis of the Makhool dam using Geo-studio software is presented in this paper for the purpose of investigating the seismic behavior of earth dams. With emphasis on the dam's height, soil characteristics, and input motion, this study examines the effect of earthquake excitation on the dam's behavior. With input from the SEEP/W program, the analysis was conducted using the QUAKE/W program. In this study, the horizontal component of motion was taken at three different values: 0.04g, 0.06g, and 0.08g. In addition to total stress in x-direction and y-direction, pore water pressure, and x-displacement, the results were presented in figures. Study findings showed that the horizontal displacement and shear strain of the dam increased with dam height, with the maximum displacement of the dam equal to 94 cm at the end of the earthquake. Besides the type of dam soil, the acceleration of the dam was also affected by the strength of the soil, since weaker soil reduced the acceleration of the dam. The pore-water pressure at the dam's base was the highest, with the horizontal movement increasing with depth. In earthquake zones, seismic evaluation is vital for dam construction, and the research provides valuable advice for designing and building earth dams. [ABSTRACT FROM AUTHOR]

Mobility in urban and interurban areas, mainly by cars, is a day-to-day activity of many people. However, some of its main drawbacks are traffic jams and accidents. Newly made vehicles have pre-installed driving evaluation systems, which can prevent accidents. However, most cars on our roads do not have driver assessment systems. In this paper, we propose an approach for recognising driving styles and enabling drivers to reach safer and more efficient driving. The system consists of two physical sensors connected to a device node with a display and a speaker. An artificial neural network (ANN) is included in the node, which analyses the data from the sensors, and then recognises the driving style. When an abnormal driving pattern is detected, the speaker will play a warning message. The prototype was assembled and tested using an interurban road, in particular on a conventional road with three driving styles. The gathered data were used to train and validate the ANN. Results, in terms of accuracy, indicate that better accuracy is obtained when the velocity, position (latitude and longitude), time, and turning speed for the 3-axis are used, offering an average accuracy of 83%. If the classification is performed considering just two driving styles, normal and aggressive, then the accuracy reaches 92%. When the geo-information and time data are included, the main novelty of this paper, the classification accuracy is improved by 13%. [ABSTRACT FROM AUTHOR]

This paper reviews the work done on science and technology of aircraft seat ejection with history, present, and futuristic interest. It is topic of interest that is receiving significant attention in the recent years due to importance of the pilot life saving during war, mishaps, and emergencies. In the early days, the ejection seats used the concept of compressed air and simple mechanical springs. The escape of the aircrew from high-speed aircraft is a serious drawback during World War (WW) II. The jumping out of aeronauts from high-speed aircraft is extremely difficult because of high blast wind pressure, turbulence around the exposed cockpit, and accelerations during the aircraft maneuvers. All these systems are dangerous and damage to the vertebra column of an aviator. As the speed of the aircraft is low, the pilot has to jump out with his parachute. However, as the speed of the aircraft increases, jumping out from the disabled aircraft with the parachute is merely a matter of luck and does not guarantee the aeronaut’s survival. Therefore, it is highly essential to use an ejection seat when damage is caused due to either the fighter or trainer plane. The ejection of the pilot is of utmost importance to the services. Hence, the lives of the pilots are crucial than saving military planes. Safeguarding the pilots from disabled aircraft plays a significant role in services such as Indian Air Force and Indian Navy since their introduction. Different policies and regulations are enforced to ensure the survival and safety of pilots. These are considered an essential area in the safety programs. Security and safety are always threat to the pilots. The novelty of this research paper is to bring about the historical developmental concepts to advanced concepts through science and technologyelated aircraft seat ejection. This paper is based on oration presented by the author on the occasion of National Science Day in Feb 2021. Therefore, an attempt is also made to highlight the important contributions made by various scientists, researchers in the frontier areas related to science and technology of ejection seat for military fighter aircraft. [ABSTRACT FROM AUTHOR]

Copyright of Raumforschung und Raumordnung is the property of Oekom Verlag GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a novel railway track monitoring approach is proposed that employs acceleration responses measured on an in-service train to detect the loss of stiffness in the track sub-layers. An Artificial Neural Network (ANN) algorithm is developed that works with the energies of the train acceleration responses. A numerical model of a half-car train coupled with a track profile is employed to simulate the train vertical acceleration. The energy of acceleration signals measured from 100 traversing trains is used to train the ANN for healthy track conditions. The energy is calculated every 15 m along the track, each of which is called a slice. In the monitoring phase, the trained ANN is used to predict the energies of a set of train crossings. The predicted energies are compared with the simulated ones and represented as the prediction error. The damage is modeled by reducing the soil stiffness at the sub-ballast layer that represents hanging sleepers. A damage indicator (DI) based on the prediction error is proposed to visualize the differences in the predicted energies for different damage cases. In addition, a sensitivity analysis is performed where the impact of signal noise, slice sizes, and the presence of multiple damaged locations on the performance of the DI is assessed. [ABSTRACT FROM AUTHOR]

The structural collapse of a street lighting pole represents an aspect that is often underestimated and unpredictable, but of relevant importance for the safety of people and things. These events are complex to evaluate since several sources of damage are involved. In addition, traditional inspection methods are ineffective, do not correctly quantify the residual life of poles, and are inefficient, requiring enormous costs associated with the vastness of elements to be investigated. An advantageous alternative is to adopt a distributed type of Structural Health Monitoring (SHM) technique based on the Internet of Things (IoT). This paper proposes the design of a low-cost system, which is also easy to integrate in current infrastructures, for monitoring the structural behavior of street lighting poles in Smart Cities. At the same time, this device collects previous structural information and offers some secondary functionalities related to its application, such as meteorological information. Furthermore, this paper intends to lay the foundations for the development of a method that is able to avoid the collapse of the poles. Specifically, the implementation phase is described in the aspects concerning low-cost devices and sensors for data acquisition and transmission and the strategies of information technologies (ITs), such as Cloud/Edge approaches, for storing, processing and presenting the achieved measurements. Finally, an experimental evaluation of the metrological performance of the sensing features of this system is reported. The main results highlight that the employment of low-cost equipment and open-source software has a double implication. On one hand, they entail advantages such as limited costs and flexibility to accommodate the specific necessities of the interested user. On the other hand, the used sensors require an indispensable metrological evaluation of their performance due to encountered issues relating to calibration, reliability and uncertainty. [ABSTRACT FROM AUTHOR]

In the field of structural health monitoring, vibration-based damage identification remains a formidable challenge. Key to this challenge is the establishment of a reliable association between observed vibration characteristics and the actual state of structural damage (e.g. stiffness reduction). This association not only accurately indicates the presence of damage, but also the location and severity of the damage. To solve this complex pattern identification problem, a large number of approaches, including deep learning, have emerged in recent years. In this paper, we propose a new structural damage identification method that utilizes the vibration information of the structure and a convolutional neural network based on Alex NET improvement. The method consists of calculating the acceleration response power spectral density of damaged and undamaged structures under impact loading separately, and then making a difference between the two power spectral data, and subsequently introducing these power spectral difference data into the convolutional neural network for training. The use of power spectral density analysis as a preprocessing step converts the time-domain signals into frequency-domain signals, and this conversion allows the convolutional neural network to capture and learn from the specific frequency characteristics of the data, thus facilitating the learning process of the neural network model. In this paper, the effectiveness of the method is critically evaluated through numerical simulation and experimental validation, and 3% and 5% noise are added to the numerical study to test the robustness of the method. During the convolution neural network training process, the optimal training mean squared error (MSE) is 5 × 10−6 in the case of no noise addition; the optimal training MSE is 1.3 × 10−5 in the case of noise addition. Both the results of simulations and experiments confirm the high accuracy and good robustness of the method in localizing structural damage. [ABSTRACT FROM AUTHOR]

Copyright of Perspectives on Culture / Perspektywy Kultury is the property of Jesuit University Ignatianum in Krakow and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Subway systems are a crucial component of urban public transportation, especially in terms of safety during seismic events. Soil liquefaction triggered by earthquakes is one of the key factors that can lead to underground structural damage. This study investigates the impact of deep soil liquefaction on the response of subway station structures during seismic activity, aiming to provide evidence and suggestions for earthquake-resistant measures in underground constructions. The advanced finite element software PLAXIS was utilized for dynamic numerical simulations. Non-linear dynamic analysis methods were employed to construct models of subway stations and the surrounding soil layers, including soil–structure interactions. The UBC3D-PLM liquefaction constitutive model was applied to describe the liquefaction behavior of soil layers, while the HS constitutive model was used to depict the dynamic characteristics of non-liquefied soil layers. The study examined the influence of deep soil liquefaction on the dynamic response of subway station structures under different seismic waves. The findings indicate that deep soil liquefaction significantly increases the vertical displacement and acceleration responses of subway stations compared to non-liquefied conditions. The liquefaction behavior of deep soil layers leads to increased horizontal effective stress on both sides of the structure, thereby increasing the horizontal deformation of the structure and posing a potential threat to the safety and functionality of subway stations. This research employed detailed numerical simulation methods, incorporating the non-linear characteristics of deep soil layer liquefaction, providing an analytical framework based on regulatory standards for evaluating the impact of deep soil liquefaction on the seismic responses of subway stations. Compared to traditional studies, this paper significantly enhances simulation precision and practical applicability. Results from this research indicate that deep soil layer liquefaction poses a non-negligible risk to the structural safety of subway stations during earthquakes. Therefore, the issue of deep soil liquefaction should receive increased attention in engineering design and construction, with effective prevention and mitigation measures being implemented. [ABSTRACT FROM AUTHOR]

The development of the sharing economy is accelerated using digital technologies. Such a topic is not widely discussed in the literature and requires knowledge to fill the existing gaps. The authors analyzed technology-driven variables which have the highest impact on expanding sharing activities. The research helps to examine the degree of integration of society into the process of sharing economy development. This paper aims to create a methodology that helps to evaluate the development of sharing platforms dependent on technological variables such as society's access to digital services. Two activities are foreseen to achieve the goal. The first activity includes the steps necessary for revising technological variables (the compilation of an initial list of variables, the selection of variables, normalization, and the formation of correlation matrix). The second activity is designed to form a panel regression model using several sharing platform cases. Using the developed methodology, the revision of technological variables is carried out to expand the knowledge of economic science about the intensifying processes of the digitization of society, the resulting changes in consumption, and the redistribution of conventional economic solutions in the markets for goods and services. The authors compared the technological variables which had the highest impact on sharing platforms. The study results demonstrated that among ten sharing platforms, the highest dependence on technological variables is evident in the number of visitors visiting the Uber sharing platform. [ABSTRACT FROM AUTHOR]

At an extremely high Mach number, the regenerative cooling of traditional kerosene cannot meet the requirement of the heat sink caused by aerodynamic heating and internal combustion in a scramjet propulsion system. As a supplement of traditional regenerative cooling, supercritical CO2 is regarded as an effective coolant in severe heating environments due to its excellent properties of heat and mass transportation. In this paper, the heat transfer and flow structure characteristics of regenerative cooling in a rectangular channel using supercritical CO2 are analyzed numerically using a validated model. The effect of heat flux magnitude, nonuniform heat flux, acceleration and buoyancy and flow pattern are considered to reveal the regenerative cooling mechanism of supercritical CO2 in the engine condition of a scramjet. The results indicate that the heat transfer deterioration phenomenon becomes obvious in the cooling channel loaded with relatively high heat flux. Compared with the cooling channels loaded with increased heat flux distribution, the maximum temperature increased for the channel loaded with decreased heat flux distributions. When larger acceleration is applied, a relatively lower wall temperature distribution and higher heat transfer coefficients are obtained. The wall temperature distribution becomes more uniform and the high-temperature region is weakened when the coolants in adjacent channels are arranged as a reversed flow pattern. Overall, the paper provides some references for the utilization of supercritical CO2 in regenerative cooling at an extremely high Mach number in a scramjet. [ABSTRACT FROM AUTHOR]

The electron acceleration, in a laser wakefield accelerator, controlled through plasma density inhomogeneity is studied on a basis of 2.5-dimensional particle-in-cell simulation. The acceleration requires a concordance of the density scale length and shift of the accelerated electron bunch relative to wake bubble during electron acceleration. This paper considers the excitation of a wakefield in plasma with a density equal to the density of free electrons in metals, solid-state plasma (the original idea of Prof. T. Tajima), in the context of studying the wakefield process. As is known in the wake process, as the wake bubble moves through the plasma, the self-injected electron bunch shifts along the wake bubble. Then, the self-injected bunch falls into the phase of deceleration of the wake wave. In this paper, support of the acceleration process by maintaining the position of the self-injected electron bunch using an inhomogeneous plasma is proposed. It is confirmed that the method of maintaining phase synchronization proposed in the article by using a nonuniform plasma leads to an increase in the accelerating gradient and energy of the accelerated electron bunch in comparison with the case of self-injection and acceleration in a homogeneous plasma. [ABSTRACT FROM AUTHOR]

Introduction: The goal of this paper is to determine what happens in one minute (on average) in kinematic parameters and metabolic power in small sided games (SSG) (3v3; 5v5) and large sided games (LSG) (10v10) and in which games kinematic parameters and metabolic power are best developed. Methods: The participants of this study were 22 professional football players, height 182.95±6.52 cm, mass 77.17±8.21 kg, body mass index (BMI) 22.97±1.47 kg/m², body fat 9.85±2.55 %, aged 27.1±5.4 yrs, who played in the Premier League of Bosnia and Herzegovina. Data total distance (TD), maximum speed (MS), number of accelerations (nAcc), number of decelerations (nDec), number of sprints (nS), high intensity distance (Z4≥19.8 km/h), sprint distance (Z5≥25.2 km/h) and movements requiring a certain metabolic power (Pmet), were collected using a 20 Hz Global positioning system (GPS) system Pro2 (GPEXE, Exelio srl, Udine, Italy), on a total of 307 individual observations. Results: The results showed that the average total distance was significantly higher in the 5v5 (135.16±18.78 m) and 10v10 (133.43±20.06 m) games (F=64.26, p<0.001) compared to the 3v3 (108.24±11.26 m). Furthermore, the values of the variables Z4 (8.32±3.38 m, F=97.59), Z5 (1.84±1.53 m, F=123.64), nS (0.13±0.10 n, F=96.14) as well as Maxspeed (27.06±1.90 km/h, F=139.33), are statistically significantly higher (p<0.001) in the 10v10 game compared to the other two game formats. The average number of nAcc (0.40±0.32 n, F=9.86, p<0.001) and nDec (0.62±0.36 n, F=6.42, p<0.001) is statistically significantly higher in the 5v5 game. The results showed that the 5v5 game is significantly more metabolically demanding Pmet (2.76±0.67W•kg-1, F=66.08, p<0.001) compared to the other two game formats. Discussion: The data presented in this paper can be used as a basis for the construction of specific exercises based on kinematic and physiological requirements, and for planning and programming microcycles in football. [ABSTRACT FROM AUTHOR]

Flapping wings may encounter or 'capture' the wake from previous half-stroke, leading to local changes in the instantaneous aerodynamic force on the wing at the start of each half-stroke. In this paper, I developed a simple approach to integrating prediction of these wake capture effects into existing analytical quasi-steady models for hovering insect flapping flight. The local wake flow field is modelled as an additional induced velocity component normal to the stroke plane of the flapping motion that is blended/switched in at the start of each half-stroke. Comparison of model results against experimental data in the literature shows satisfactory agreement in predicting the wake capture lift and drag variations for eight different test cases. Sensitivity analysis shows that the form of the translation velocity time history has a significant effect on the magnitude of wake capture forces. Profiles that retain high translational velocity right up to stroke reversal evoke a much larger effect from wake capture compared with sinusoidal. This result is significant because while constant flapping translation velocity profiles can be generated in the laboratory, the very high accelerations required near stroke reversals incur high mechanical cost that prevents practical adoption in nature or engineered flapping flight vehicles.

Introduction: The role of real-time data capture (via telematics technology) is gathering prominence as a strategy to provide feedback to young drivers about important road safety issues., Method: A naturalistic driving study was undertaken to determine whether providing personalized feedback (via a smartphone app) to young provisional drivers aged 17-20 years living in metropolitan and regional Western Australia (WA) reduced their risky driving behavior compared to a control group who did not receive feedback. Speeding over the posted speed limit, harsh decelerations (braking), harsh accelerations and overall driving performance, were recorded continuously using the smartphone app during the 11-week study. Four separate Generalised Estimating Equations (GEE) linear regression models were undertaken after accounting for relevant confounders including driving exposure to determine the difference between the intervention and control group for the 4 driving outcomes obtained from the smartphone app., Results: The study found that there was no significant change in overall driving scores between the intervention and control groups (p = 0.35). However, the overall driving score significantly improved by 0.19 points for young provisional drivers who lived in regional areas compared to those in the metropolitan area (p = 0.05) after adjusting for potential confounders. There was also no significant change in harsh braking scores (p = 0.46) and harsh acceleration scores between the intervention and control groups (p = 0.26) However, harsh acceleration scores improved by 0.37 points for females compared to males (p = 0.04). Lastly, there was no significant change in speed scores between the control and intervention groups (p = 0.72). However, the speed scores of participants who lived in regional WA improved by 0.22 points compared to those in the metropolitan area (p = 0.02). Furthermore, for every 1,000 km travelled, speed scores worsened by -0.08 points (p < 0.01) regardless of group., Conclusions: The study did not find any statistical difference in the driving outcomes examined; however the treatment effects for feedback were consistently in the expected positive direction. Young drivers in regional WA also improved their speeding scores and overall driving performance scores compared to young drivers in the metropolitan area. Females, also significantly improved their harsh deceleration scores compared to males, regardless of group allocation. These results highlight the use of smartphone telematics as an opportunity to not only enhance the safety of provisional young drivers but also provide data-informed decision making and policy development., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Switches are an essential, safety-critical part of the railway infrastructure. Compared to open tracks, their complex geometry leads to increased dynamic loading on the track superstructure from passing trains, resulting in high maintenance costs. To increase efficiency, condition monitoring methods specific to railway switches are required. A common approach to track superstructure monitoring is to measure the acceleration caused by vehicle track interaction. Local interruptions in the wheel–rail contact, caused for example by local defects or track discontinuities, appear in the data as transient impact events. In this paper, such transient events are investigated in an experimental setup of a railway switch with track-side acceleration sensors, using frequency and waveform analysis. The aim is to understand if and how the origins of these impact events can be distinguished in the data of this experiment, and what the implications for condition monitoring of local track discontinuities and defects with wayside acceleration sensors are in practice. For the same experimental configuration, individual impact events are shown to be reproducible in waveform and frequency content. Nevertheless, with this track-side sensor setup, the different types of track discontinuities and defects (squats, joints, crossing) could not be clearly distinguished using characteristic frequencies or waveforms. Other factors, such as the location of impact event origin relative to the sensor, are shown to have a much stronger influence. The experimental data suggest that filtering the data to narrow frequency bands around certain natural track frequencies could be beneficial for impact event detection in practice, but differentiating between individual impact event origins requires broadband signals. A multi-sensor setup with time-synchronized acceleration sensors distributed over the switch is recommended. [ABSTRACT FROM AUTHOR]

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To examine the effects of different peak accelerations on the stability of the accumulation slope and the effectiveness of anti-slide piles under seismic loads, this paper used the Fanlingqian landslide as the main research object and combined it with digital image correlation (DIC) technology in order to carry out a shaking table test. Then, the acceleration response, displacement field, strain field, the bending moment distribution of the 0.05–0.3 g ground motion accumulation slope, and the anti-slide pile reinforcement were studied. The results of the test show the following: the amplification coefficient of the measuring points A1–A6 of the accumulation slope reaches the maximum at a peak acceleration of 0.2 g, and its values are between 1.25 and 1.3, respectively. Finally, it shows a decreasing trend at a peak acceleration of 0.3 g, and its corresponding values are, respectively, between 1.1 and 1.2. In the anti-slip pile reinforcement test, due to the obstruction of the anti-slip pile, the damping of the soil around the pile increases. As the peak value of the seismic wave input increases, the amplification factor shows an overall decreasing trend. A1–A6 correspond to a peak acceleration of 0.3 g. The amplification factors are all close to 1. During different peak accelerations, the accumulation slope mainly experienced the earthquake-induced stage, tensile failure stage, creeping deformation stage, and overall instability stage. In the anti-slide pile reinforcement test, under the same conditions, the slope mainly experienced the earthquake-induced stage, tensile failure stage, lower sliding surface formation stage, and soil shedding stage in front of the pile. At the same time, the displacement and strain fields of each stage of the two groups of tests are compared, and it is found that the displacement and strain values of the accumulation slope test are greater than those of the anti-slide pile reinforcement test, and the horizontal displacement difference at the top of the slope is the most significant, reaching 2.3 times at the maximum. The bending moment of the anti-slide pile first increases and then decreases with the increase in acceleration, the reverse bending point of the pile appears at 5 times the pile diameter below the soil surface, and the maximum bending moment of the middle pile, corresponding to a peak acceleration of 0.05–0.3 g, is between 7.5 N·m and 47 N·m, respectively, while the maximum bending moment of the outer pile is between 6.5 N·m and 52 N·m, respectively. It is important to apply DIC image processing technology to the monitoring of landslide structure and the evaluation of slope stability in practical engineering. [ABSTRACT FROM AUTHOR]

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Comfort is an important consideration in passenger vehicles provided by a suspension system. The suspension system must be associated with the vehicle body to improve comfort for the passenger. The active suspension system (ASS) has been introduced to perform this task. Moreover, the sliding mode controller (SMC) is well known for its continuous control signals. This paper proposes the Bayesian-based proportional resonant sliding mode controller (B-PRSMC) and two degrees of the freedom-proportional resonant controller (2d-f-PR) to stabilize passenger and ride comfort. The B-PRSMC is used for examining system states under varying road disturbances based on the Bayesian theorem. After examining the system state, the system performance is controlled by the 2d-f-PR controller. The proposed method is performed on Matlab, and the results are taken regarding body acceleration, body travel and suspension deflection. The mastery of proposed method is estimated under different road profiles. The comparative analysis demonstrates that the suggested controller enhances ride and passenger comfort in varied road profiles due to the combination of B-PRSMC and 2d-f-PR controllers. [ABSTRACT FROM AUTHOR]

Due to the significant mismatch in timescales associated with morphological and hydrodynamic processes in coastal environments, modellers typically resort to various techniques for speeding up the bed evolution in morphodynamic simulations. In this paper, we propose a novel method that differs from existing ones in several aspects. For example, unlike previous approaches that apply a global measure (such as a constant acceleration factor that uniformly amplifies the bed evolution everywhere), we track and extrapolate local trends in morphological changes. The present algorithm requires the setting of four different parameters, values for which we set through an extensive calibration process. The proposed method is compared against the simple acceleration technique built into the popular software XBeach (wherein it is called morfac) for eight different beach profiles (including linear, Dean, and measured profiles). While the accuracy of both methods is generally similar, the proposed algorithm consistently shows a greater reduction in computational time relative to morfac, with our algorithm-accelerated simulations being on average 2.6 times faster than morfac. In light of these results, and considering the algorithm's potential for easy generalisation to address arbitrary coastal morphodynamic problems, we believe that this method represents an important addition to the toolbox available to the community interested in coastal modelling. [ABSTRACT FROM AUTHOR]

It is widely acknowledged that the success of deep learning is built upon large-scale training data and tremendous computing power. However, the data and computing power are not always available for many real-world applications. In this paper, we address the machine learning problem where it lacks training data and limits computing power. Specifically, we investigate domain adaptation which is able to transfer knowledge from one labeled source domain to an unlabeled target domain, so that we do not need much training data from the target domain. At the same time, we consider the situation that the running environment is confined, e.g., in edge computing the end device has very limited running resources. Technically, we present the Faster Domain Adaptation (FDA) protocol and further report two paradigms of FDA: early stopping and amid skipping. The former accelerates domain adaptation by multiple early exit points. The latter speeds up the adaptation by wisely skip several amid neural network blocks. Extensive experiments on standard benchmarks verify that our method is able to achieve the comparable and even better accuracy but employ much less computing resources. To the best of our knowledge, there are very few works which investigated accelerating knowledge adaptation in the community. This work is expected to inspire the topic for more discussion. [ABSTRACT FROM AUTHOR]

This paper proposes the design of a 360° map establishment and real-time simultaneous localization and mapping (SLAM) algorithm based on equirectangular projection. All equirectangular projection images with an aspect ratio of 2:1 are supported for input image types of the proposed system, allowing an unlimited number and arrangement of cameras. Firstly, the proposed system uses dual back-to-back fisheye cameras to capture 360° images, followed by the adoption of the perspective transformation with any yaw degree given to shrink the feature extraction area in order to reduce the computational time, as well as retain the 360° field of view. Secondly, the oriented fast and rotated brief (ORB) feature points extracted from perspective images with a GPU acceleration are used for tracking, mapping, and camera pose estimation in the system. The 360° binary map supports the functions of saving, loading, and online updating to enhance the flexibility, convenience, and stability of the 360° system. The proposed system is also implemented on an nVidia Jetson TX2 embedded platform with 1% accumulated RMS error of 250 m. The average performance of the proposed system achieves 20 frames per second (FPS) in the case with a single-fisheye camera of resolution 1024 × 768, and the system performs panoramic stitching and blending under 1416 × 708 resolution from a dual-fisheye camera at the same time.

LoRaWAN has imposed itself as a promising and suitable technology for massive machine-type communications. With the acceleration of deployment, improving the energy efficiency of LoRaWAN networks has become paramount, especially with the limitations of throughput and battery resources. However, LoRaWAN suffers from the Aloha access scheme, which leads to a high probability of collision at large scales, especially in dense environments such as cities. In this paper, we propose EE-LoRa, an algorithm to improve the energy efficiency of LoRaWAN networks with multiple gateways via spreading factor selection and power control. We proceed in two steps, where we first optimize the energy efficiency of the network, defined as the ratio between the throughput and consumed energy. Solving this problem involves determining the optimal node distribution among different spreading factors. Then, in the second step, power control is applied to minimize the transmission power at nodes without jeopardizing the reliability of communications. The simulation results show that our proposed algorithm greatly improves the energy efficiency of LoRaWAN networks compared to legacy LoRaWAN and relevant state-of-the-art algorithms.

This study contributes towards a threshold for the onset of discomfort stemming from vibration that is transmitted to the human body by means of impulsive wave slamming in dynamic shipping environments. Wave slamming is a random, violent, non-linear event. Subjective and objective data were collected from two research voyages on a slamming-prone vessel. Full-scale vertical acceleration measurements were conducted near work and accommodation areas on the vessel. A daily diary survey was used to gather human responses among passengers. In addition, instantaneous slamming vibration comfort ratings were obtained by observers on the ship Bridge during a test sequence that purposefully induced slamming. The results indicate that two different approaches converged to the same VDV 1hr comfort threshold (0.41 m/s 1.75 and 0.43 m/s 1.75 ), which corresponds to the limit where 50% of respondents indicated discomfort. A similar analysis using the r.m.s. metric converged to an identical threshold (0.03 m/s 2 ), irrespective of the accumulated time of assessment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The safety of road users is one of the priority issues taken into account in both the operation and design of vehicles. The presented work is part of a study that aims to develop a method for parametric assessment of driver behavior. The driving style of a driver depends on their skills and psychophysical characteristics, the type and performance of the vehicle used by the driver, and the type of road. This method involves the continuous measurement of the longitudinal and lateral acceleration values of a vehicle body. The paper analyzes how the type of road influences the structure of the maneuvers undertaken by the driver. The paper formulates criteria for distinguishing basic maneuvers (acceleration, braking, and turning). The structure of maneuvers was analyzed for two parameters: the extreme value of acceleration occurring during the execution of a given maneuver and the frequency of maneuvers during the passage of a given route. The analysis presented in this paper confirms that the type of road has a significant influence on the structure of the maneuvers undertaken by the driver. [ABSTRACT FROM AUTHOR]

This paper explores the non-convex composition optimization consisting of inner and outer finite-sum functions with a large number of component functions. This problem arises in important applications such as nonlinear embedding and reinforcement learning. Although existing approaches such as stochastic gradient descent (SGD) and stochastic variance reduced gradient (SVRG) descent can be applied to solve this problem, their query complexities tend to be high, especially when the number of inner component functions is large. Therefore, to significantly improve the query complexity of current approaches, we have devised the stochastic composition via variance reduction (SCVR). What's more, we analyze the query complexity under different numbers of inner function and outer function. Based on different kinds of estimation of inner component function, we also present the SCVRII algorithm, though the order of query complexities are the same with SCVR. Additionally, we propose an extension to handle the mini-batch cases, which improve the query complexity under the optimal mini-batch size. The experimental results validate our proposed algorithms and theoretical analyses. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative model for heavy-haul train–track–bridge interaction, utilizing a coupling matrix representation based on the virtual work principle. This model establishes the relationship between the wheel–rail contact surface and the bridge–rail interface concerning internal forces and geometric constraints. In this coupled system's motion equation, the degrees of freedom (DOFs) of the wheelsets in a heavy-haul train lacking primary suspension are interdependent. Additionally, the vertical and nodding DOFs of the bogie frame are linked with the rail element. A practical application, a Yellow River Bridge with a heavy-haul railway line, is used to examine the accuracy of the proposed model with regard to discrepancy between the simulated and measured displacement ranging from 1% to 11%. A comprehensive parametric analysis is conducted, exploring the impacts of track irregularities of varying wavelengths, axle load lifting, and the degradation of bridge stiffness and damping on the dynamic responses of the coupled system. The results reveal that the bridge's dynamic responses are particularly sensitive to track irregularities within the wavelength range of 1 to 20 m, especially those within 1 to 10 m. The vertical displacement of the bridge demonstrates a nearly linear increase with heavier axle loads of the heavy-haul trains and the reduction in bridge stiffness. However, there is no significant rise in vertical acceleration under these conditions. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the current aspects of former Soviet society modernization in the context of global challenges of the 21st century. The study uses Kazakhstan as an example. The primary focus of this paper is on the comparative analysis of the global dynamics of economic development trends regarding OECD and Kazakhstan. The study's methodology entails a historiographical analysis of recent works on modernization issues in contemporary societies. Modernization is seen as a part of the complicated process of the world becoming more global as the capitalist system changes. Modernization phenomena are analyzed quantitatively and phenomenologically within the framework of the research methodology. The study used a combination of quantitative and qualitative methods to analyze statistical data on economic development in Kazakhstan. The applied quantitative analysis techniques constructed a regression model of modernization prospects based on the factor of labour productivity and gross savings. Qualitative interpretations in this study were based on phenomenological and analytical approaches in the philosophical sciences. This study focused on a new theory of modernization that views it from the perspective of social acceleration and the pursuit of sustainability in the protection of traditional spirituality within the context of modernization. In practice, this model enables the exploration of various modernization trajectories. It will be useful in the creation of the corresponding state development programmes of Kazakhstan. In this way, the spiritual modernization of society will help build a work ethic, an economy based on knowledge and innovation, a social consensus, and a space where people from different backgrounds can live together. [ABSTRACT FROM AUTHOR]

In recent years, personal authentication based on attitude estimation—gait recognition authentication has become a popular research topic because of its long-range, non-invasive, non-contact, high-precision, and other advantages. However, at present, most relevant research prefers to use the acquired original data directly for iteration and learning. As a result, it takes too long to learn relevant models in the use scenarios with complicated data and heavy human traffic, such as airports and railway stations, where real-time identification cannot be completed while maintaining accuracy, and thus a scheme to improve the learning and recognition speed is needed. Therefore, in this paper, we proposed an innovative real-time MediaPipe-based gait analysis framework and a new Composite Filter Feature Selection (CFFS) method via key nodes, angles, and lengths calculating. Then, based on the proposed method, we extract the aimed features as a new dataset and verified it by 1D-CNN neural network. Furthermore, we also applied Hilbert–Huang transform to investigate these extracted gait features in the frequency domain, improving the performance of our proposed framework to achieve real time under higher recognition accuracy. The experimental results show that the innovative gait recognition framework and data processing technology can reduce the gait feature data, speed up the process of gait recognition, and still maintain the original recognition accuracy. It can also be applied to various large, enclosed spaces with the huge human flow, which has played a role in improving the safety factor, saving labor costs, and accelerating economic consumption. [ABSTRACT FROM AUTHOR]

In practical operation, pump turbines typically operate far from their designed working points, which has a significant impact on the stability of the unit's operation. In this paper, we conducted a field test to investigate the stability characteristics of prototype pump turbines at different working points. By adjusting the given power of the generator in a stepwise manner to control its working point, we obtained the statistical and spectral characteristics of pressure signals and acceleration signals. In turbine mode, the result shows that, at low, medium, and high power, the variation in pressure fluctuation characteristics is influenced by three different factors, while vibration generally reaches its maximum value at approximately 50 MW. In pump mode, variations in pressure were observed among different measurement points in the low-frequency range, and the characteristics of vibration acceleration were influenced by both the rotor–stator interaction (RSI) and the structural modal frequencies. We emphasized that the high-frequency bands have influences on the unit comparable in magnitude to those of the rotor–stator interaction, which has rarely been mentioned in previous studies. Through detailed testing and analysis of the unit's actual operation, we can gain a better understanding of its behavior and performance in the turbine and pump modes, and these results hold significant importance for ensuring the stability and reliability of the unit. [ABSTRACT FROM AUTHOR]

Human motion analysis requires information about the position and orientation of different parts of the human body over time. Widely used are optical methods such as the VICON system and sets of wired and wireless IMU sensors to estimate absolute orientation angles of extremities (Xsens). Both methods require expensive measurement devices and have disadvantages such as the limited rate of position and angle acquisition. In the paper, the adaptation of the drone flight controller was proposed as a low-cost and relatively high-performance device for the human body pose estimation and acceleration measurements. The test setup with the use of flight controllers was described and the efficiency of the flight controller sensor was compared with commercial sensors. The practical usability of sensors in human motion measurement was presented. The issues related to the dynamic response of IMU-based sensors during acceleration measurement were discussed.

Introduction: While micromobility vehicles offer new transport opportunities and may decrease fuel emissions, the extent to which these benefits outweigh the safety costs is still uncertain. For instance, e-scooterists have been reported to experience a tenfold crash risk compared to ordinary cyclists. Today, we still do not know whether the real safety problem is the vehicle, the human, or the infrastructure. In other words, the new vehicles may not necessarily be unsafe; the behavior of their riders, in combination with an infrastructure that was not designed to accommodate micromobility, may be the real issue., Method: In this paper, we compared e-scooters and Segways with bicycles in field trials to determine whether these new vehicles create different constraints for longitudinal control (e.g., in braking avoidance maneuvers)., Results: The results show that acceleration and deceleration performance changes across vehicles; specifically, e-scooters and Segways that we tested cannot brake as efficiently as bicycles. Further, bicycles are experienced as more stable, maneuverable, and safe than Segways and e-scooters. We also derived kinematic models for acceleration and braking that can be used to predict rider trajectories in active safety systems., Practical Applications: The results from this study suggest that, while new micromobility solutions may not be intrinsically unsafe, they may require some behavior and/or infrastructure adaptations to improve their safety. We also discuss how policy making, safety system design, and traffic education may use our results to support the safe integration of micromobility into the transport system., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Multimodal path queries over transportation networks are receiving increasing attention due to their widespread applications. A multimodal path query consists of finding multimodal journeys from source to destination in transportation networks, including unrestricted walking, driving, cycling, and schedule-based public transportation. Transportation networks are generally continent-sized. This characteristic highlights the need for parallel computing to accelerate multimodal path queries. Meanwhile, transportation networks are often fragmented and distributively stored on different machines. This situation calls for exploiting parallel computing power for these distributed systems. Therefore, in this paper, we study distributed multimodal path (DMP) queries over large transportation networks. We develop algorithms to explore parallel computation. When evaluating a DMP query $Q$ Q on a distributed multimodal graph $Gmult$ G m u l t , we show that the algorithms possess the following performance guarantees, irrespective of how $Gmult$ G m u l t is fragmented and distributed: (1) each machine is visited only once; (2) the total network traffic is determined by the size of $Q$ Q and the fragmentation of $Gmult$ G m u l t ; (3) the response time is decided by the largest fragment of $Gmult$ G m u l t ; and (4) the algorithm is parallel scalable. Using real-life and synthetic data, we experimentally verify that the algorithms are scalable on large graphs. [ABSTRACT FROM AUTHOR]

Proximal operators are of particular interest in optimization problems dealing with non-smooth objectives because in many practical cases they lead to optimization algorithms whose updates can be computed in closed form or very efficiently. A well-known example is the proximal operator of the vector $\ell _1$ ℓ 1 norm, which is given by the soft-thresholding operator. In this paper we study the proximal operator of the mixed $\ell _{1,\infty }$ ℓ 1 , ∞ matrix norm and show that it can be computed in closed form by applying the well-known soft-thresholding operator to each column of the matrix. However, unlike the vector $\ell _1$ ℓ 1 norm case where the threshold is constant, in the mixed $\ell _{1,\infty }$ ℓ 1 , ∞ norm case each column of the matrix might require a different threshold and all thresholds depend on the given matrix. We propose a general iterative algorithm for computing these thresholds, as well as two efficient implementations that further exploit easy to compute lower bounds for the mixed norm of the optimal solution. Experiments on large-scale synthetic and real data indicate that the proposed methods can be orders of magnitude faster than state-of-the-art methods. [ABSTRACT FROM AUTHOR]

We consider a class of nonconvex regularized optimization problems, which appear frequently in machine learning and data processing. Due to the structure of the problems, the iteratively reweighted algorithm was developed and applied to the consensus optimization. In this paper, we propose the acceleration of this scheme by adding an inertial term in each iteration. The proposed algorithms inherit the advantages of classical decentralized algorithms: they can be implemented over a connected network, in which the agents communicate with their neighbors and perform local computations. We also employ the diminishing stepsizes technique for the iteratively reweighted algorithm and consider its acceleration. In specific cases, our algorithms reduce to existing decentralized schemes and also indicate novel ones. Mathematically, we prove the convergence for both algorithms with several assumptions on the objective functions. With Kurdyka-Łojasiewicz property, convergence rates can be derived for constant stepsize case. Numerical results demonstrate the efficiency of the algorithms. [ABSTRACT FROM AUTHOR]