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As an efficient two-phase heat transfer technology, the application of loop heat pipe (LHP) technology in the aerospace industry has received more attention in recent years. This paper presents a performance study of a high capacity dual compensation chamber loop heat pipe (DCCLHP) under acceleration environment. The experimental study investigated accelerations up to 8 g in five directions, while the DCCLHP operated close to the heat transfer limit in the corresponding directions. The experimental results indicated that the effect of acceleration on the performance of the DCCLHP could be either favorable or unfavorable, depending on the direction of acceleration. The operating temperature of the DCCLHP varied between −6 °C and +14 °C under different acceleration conditions. The thermal resistance changes of the DCCLHP ranged from −25 % to 116 %. For the high capacity DCCLHP, the effect of acceleration on its performance was mainly realized by affecting the thickness of the condensate film inside the condenser, which in turn affected the condenser performance. The research findings presented in this paper might aid in the advancement of DCCLHP technology for aircraft applications.

Deep neural networks (DNN) are in high demand because of their widespread applications in natural language processing, image processing, and a lot of other domains. However, due to their computational expense, over-parameterization, and large memory requirements, DNN applications often require the use of substantial model resources. This strict requirement of latency and limited memory availability are hurdles in the device deployment of these technologies. Therefore, a common idea could be to mitigate the DNN-based models’ size without any performance degradation using different compression techniques. During the last few years, a great deal of progress has been made in the field of Natural Language Processing (NLP) using deep learning approaches. The objective of this research is to offer a thorough overview of the various pruning methods applied in the context of NLP. In this paper, we review several recent pruning-based schemes used for converting standard networks into their compact and accelerated versions. Traditionally, pruning is a technique for improving latency, reducing model size, and computational complexity which is a viable approach to deal with the above-mentioned challenges. In general, these techniques are divided into two main categories: structural and unstructured pruning methods. Structural pruning methods are further classified into filter, channel, layer, block, and movement pruning. Whereas, neuron, magnitude-based, and iterative pruning lie in the category of unstructured pruning. For each method, we discuss the related metrics and benchmarks. Then recent work on each method is discussed in detail, which provides insightful analysis of the performance, related applications, and pros and cons. Then, a comparative analysis is provided to analyze the differences among approaches. Finally, the paper concludes with possible future directions and some technical challenges.

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.

This research paper presents a comprehensive investigation into the response of a 3D finite element model when subjected to 7.62 AP projectiles. The study utilises Hetherington's armour composite equation and incorporates the Johnson-Holmquist material model to analyse the strength and failure criteria of the ceramic and Kevlar/epoxy components, respectively. The results highlight the remarkable resilience of the composite armour, demonstrating its ability to withstand projectile velocities up to 1500 m/s. However, as the ballistic velocity limit increases, the armour experiences significant damage, including projectile erosion and panel delamination. Through numerical simulations and advanced modelling techniques, the paper thoroughly explores the failure modes and energy absorption characteristics of composite armour systems under projectile impact. It investigates key parameters such as velocity, acceleration, kinetic energy, internal energy, pressure distribution, displacement, and damage progression. The analysis reveals a progressive decrease in kinetic energy as the projectile interacts with the armour, underscoring the crucial role of energy absorption in preventing projectile penetration. Moreover, the impact velocity influences the distribution of internal energy within the composite armour, with higher velocities leading to greater energy absorption up to a threshold limit. The study also determines the ballistic limit velocity (V50) using the velocity history approach and validates the findings with existing literature. Overall, the research provides valuable insights into the limitations of composite armour and offers important recommendations for designing and improving materials to achieve superior ballistic protection. It emphasises the significance of reaching the maximum ballistic limit while maintaining a lightweight armour structure by optimising the total armour thickness. This study contributes to the advancement of armour technology and enhances our understanding of the behaviour of composite materials under high-velocity impacts. It offers valuable guidance for the development of more robust armour systems suitable for various defence and protection applications.

Abstract 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.

Conflicts are considered as vital elements of plural democracies in agonistic political and planning theory. According to this theory, antagonisms are to be tamed and channeled into agonistic disputes. Therefore, forms of participation in planning procedures play a key role in the resolution and regulation of conflicts. The central question of this paper is the role of participatory procedures in planning in order to resolve and settle conflicts, which occur in a particularly sharp way in the context of large-scale projects. The paper presents planning conflicts and forms of participation using the case of the settlement of the Gigafactory Tesla in the German state of Brandenburg. Within the framework of an empirical case study, the approval procedure of the project and a land use plan procedure of the municipality are analysed. Both procedures are characterized by a great acceleration, early preliminary decisions and participation deficits. The result shows that in the case of the settlement of Tesla, in addition to conflicts of interest, values and location, procedural conflicts also occur, which call the acceptance of planning into question. The forms of participation practiced do not prove suitable for taming conflicts, but rather produce mistrust among opponents and reinforce antagonistic dynamics.

In the era of IoT and smart systems, an enormous amount of data will be generated from various IoT/smart devices in smart homes, smart cars, etc. Typically, this big data is collected and sent directly to the cloud infrastructure for processing, analyzing, and storing. However, traditional cloud infrastructure faces serious challenges when handling this massive amount of data, including insufficient bandwidth, high latency, unsatisfactory real-time response, high power consumption, and privacy protection issues. The edge-centric computing is emerging as a complementary solution to address the aforementioned issues of the cloud infrastructure. Furthermore, for many real-world IoT and smart systems, such as smart cars, real-time, in situ, and online data analysis and processing are crucial. With edge computing, data processing and analysis can be done closer to the source of the data (i.e., at the edge of the networks), which in turn enables real-time and in-situ data analytics and processing. As a result, edge computing will soon become the cornerstone of many IoT and smart applications. However, edge computing is still in its infancy; thus, requires novel models and techniques to support real-time and in-situ data processing and analysis. In this research work, we introduce novel and efficient computation models that are suitable for real-time processing and analysis on next-generation edge-computing platforms. Since most common edge-computing tasks are data analytics/mining, we focus on widely used data analytics techniques, including dimensionality reduction and classification techniques, specifically, principal component analysis (PCA) and support vectors machine (SVM), respectively. This is mainly because it is demonstrated that combination of PCA and SVM leads to high classification accuracy in many fields. In this paper, we introduce three different PCA+SVM models (i.e., Model 1, Model 2, and Model 3), for real-time processing and analysis (for online training and inference) on edge computing platforms. Model 1 and Model 2 are created utilizing the same SVM algorithm but with a different design/functional flows, whereas Model 3 is created with the same functional flow as Model 2 but utilizing a modified SVM algorithm. Our experimental results and analysis demonstrate that Model 3 utilizes dramatically lower number of iterations to produce the results, compared to that of other two models, while achieving acceptable performance results. Our results and analysis demonstrate that Model 3 is the most suitable computation model for real-time processing and analysis of edge computing platform.

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.

The paper presents theoretical and experimental analyses of the kinetic friction coefficient of a ball bearing in conditions of rotational motion initiated by dynamic impact force. A method has been developed and a measurement system allows the measurement of a kinetic coefficient of friction through the measurement of the angular acceleration. This paper considers the friction caused by rotational motion initiated by the force impact impulse. After the external force (impact impulse) stops acting, the motion continues, and the loaded bearing (i.e. the zone of the bearing in which the frictional resistance forces act) exhibits a broad spectrum of velocities, from the maximum value at the moment of motion initiation to the zero value when motion stops, where the whole measuring system acts as a rotary encoder. Experimental results indicate a high dependency between angular velocity and friction coefficient, similar to functional dependency. This paper proves that kinetic friction coefficient can be reliably measured using the measurements of angle change and angular velocity. Analysed method has high potential in the diagnostics of energy loss in the tribo-mechanical systems.

Abstract Since its invention, generative adversarial networks (GANs) have shown outstanding results in many applications. GANs are powerful, yet resource-hungry deep learning models. The main difference between GANs and ordinary deep learning models is the nature of their output and training instability. For example, GANs output can be a whole image versus other models detecting objects or classifying images. Thus, the architecture and numeric precision of the network affect the quality and speed of the solution. Hence, accelerating GANs is pivotal. Data transfer is considered the main source of energy consumption, that is why memory compression is a very efficient technique to accelerate and optimize GANs. Two main types of memory compression exist: lossless and lossy ones. Lossless compression techniques are general among all models; thus, we will focus in this paper on lossy techniques. Lossy compression techniques are further classified into (a) pruning, (b) knowledge distillation, (c) low-rank factorization, (d) lowering numeric precision, and (e) encoding. In this paper, we survey lossy compression techniques for CNN-based GANs. Our findings showed the superiority of knowledge distillation over pruning alone and the gaps in the research field that needs to be explored like encoding and different combination of compression techniques.

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.

Context: Vision-based measurement (VBM) systems are becoming popular as an affordable and suitable alternative for scientific and engineering applications. When cameras are used as instruments, motion blur usually emerges as a recurrent and undesirable image degradation, which in fact contains kinematic information that is usually dismissed. Method: This paper introduces an alternative approach to measure relative acceleration from a real invariant uniformly accelerated linear motion-blurred image. This is done by using homomorphic mapping to extract the characteristic Point Spread Function (PSF) of the blurred image, as well as machine learning regression. A total of 125 uniformly accelerated motion-blurred pictures were taken in a light- and distance-controlled environment, at five different accelerations ranging between 0,64 and 2,4 m/s2. This study evaluated 19 variants such as tree ensembles, Gaussian processes (GPR), and linear, support vector machine (SVM), and tree regression. Results: The best RMSE result corresponds to GPR (Matern 5/2), with 0,2547 m/s2 and a prediction speed of 530 observations per second (obs/s). Additionally, some novel deep learning methods were used to obtain the best RMSE value (0,4639 m/s2 for Inception ResNet v2, with a prediction speed of 11 obs/s. Conclusions: The proposed method (homomorphic mapping and machine learning) is a valid alternative for calculating acceleration from invariant motion blur in real-time applications when additive noise is not dominant, even surpassing the deep learning techniques evaluated.

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.

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.

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.

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.

The paper proposes a system which is electronic data storage (of qualification works of students from different countries) and provides the capability to identify and connect young scientists conducting research on a related problem area. The purpose of developing this system is to provide opportunities for knowledge exchange, research in a team on a common problem, as well as to identify scientific trends in different countries. In this paper, the preprocessing methods influence on the work of classifiers such as Logistic Regression, LSTM, BERT, LightGBM was researched. A study was conducted on the speed of classification and F1 assessment. Conclusions. Lemmatization showed to require a shorter operating time compared to steaming by almost twice and a better score by an average of 5 percent, so it was decided to use the Logistic Regression classifier with lemmatization at the stage of text preparation in the subsequent operation of the proposed ISKE.

Abstract This paper explores a series of challenges presented by Hartmut Rosa’s concept of resonance viewed in the context of the normative and political dimensions of critical theory, a tradition in which he explicitly places his work (even as he draws on a wide range of other scholarly fields and domains). First, a tension between the anthropological and sociocultural aspects of his project raises questions about whether the avowed political commitments of the project can be incorporated into its theoretical framework. Second, the variability with which resonance can present, and its fundamentally pathic nature, makes it difficult to imagine how it might serve an emancipatory interest. Beyond this, the critical diagnosis of forms of impaired or deficient resonance introduces methodological questions with moral consequences. Despite these challenges, Rosa’s project importantly calls for a renewed relation to the world, one that shares affinities with parallel developments within the humanities.

The main purpose of the paper is to determine the change in vehicle energy efficiency due to using the air conditioning system. There is a connection between the changes in vehicle energy efficiency and fuel consumption together with time needed for vehicle acceleration. The paper comprises the measurement results performed at stabilized speeds as well as during vehicle acceleration. The final part of the paper outlines the result of calculation of change in vehicle energy efficiency resulting from air conditioning unit used during New European Driving Cycle.

In this paper, the analytical solution for the determination of induction machine acceleration, i.e. acceleration-time characteristic, during no-load direct start-up is proposed. The proposed dependence is derived from the Kloss equation for torque-speed relation for the induction machine. Also, the analytical solution for the maximal value of the acceleration is derived in this paper. The results obtained using developed expressions are compared with corresponding results obtained using the developed Matlab/Simulink model for analyses of the induction machine starting the process. Therefore, very high degree of accuracy is obtained.

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%.

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.

Electric vehicles have promising prospects for development. Our research method began with the stages of designing and calculating of a three-wheeled electric vehicle prototype. The prototype design was realized through fabrication of frame and body components. Furthermore, testing by providing weight variations was carried out in this research. This paper will determine the performance of the electric vehicle and the battery used. With the lightest weight (45 kg) at a slow speed (12 km/h), the lowest voltage drop was obtained, 6.36 V, while with the heaviest load (105 kg) at a higher speed (17 km/h), the highest decrease in voltage value was obtained, 8.96 V. Meanwhile, the measured electric current was still fluctuating. It was found that when deceleration occurs, the flowing current decreases, whereas when acceleration occurs, there is an increase in the value of the electric current.

The urgency of the energy transition is in conflict with delaying effects and options that are not optimally used in the complex, multi-stage German planning system. This also applies to the law and procedures of spatial planning, as well as the interaction of spatial planning with construction planning and sectoral law. Here, fundamental reform options have not yet been exhausted, despite many current legislative projects. Some procedural steps and options for legislative deviations can be eliminated altogether, the interaction of planning and decision-making levels can be made more effective, and subject-related certain hierarchical levels in the planning system could be omitted on a topic-specific basis. Based on a brief analysis of the initial situation for spatial planning, this paper first provides corresponding general considerations on such far-reaching acceleration options and their consequences. This is followed by the presentation of numerous specific spatial planning-related optimisation options.

For large infrastructures, dynamic displacement measurement in structures is an essential topic. However, limitations imposed by the installation location of the displacement sensor can lead to measurement difficulties. Accelerometers are characterized by easy installation, good stability and high sensitivity. For this regard, this paper proposes a structural dynamic displacement estimation method based on a one-dimensional convolutional neural network and acceleration data. It models the complex relationship between acceleration signals and dynamic displacement information. In order to verify the reliability of the proposed method, a finite element-based frame structure was created. Accelerations and displacements were collected for each node of the frame model under seismic response. Then, a dynamic displacement estimation dataset is constructed using the acceleration time series signal as features and the displacement signal at a certain moment as target. In addition, a typical neural network was used for a comparative study. The results indicated that the error of the neural network model in the dynamic displacement estimation task was 9.52 times higher than that of the one-dimensional convolutional neural network model. Meanwhile, the proposed modelling scheme has stronger noise immunity. In order to validate the utility of the proposed method, data from a real frame structure was collected. The test results showed that the proposed method has a mean square error of only 5.097 in the real dynamic displacement estimation task, which meets the engineering needs. Afterwards, the outputs of each layer in the dynamic displacement estimation model are visualized to emphasize the displacement calculation process of the convolutional neural network.

When designing 3D V-NAND technologies with a gate induced drain leakage (GIDL) assisted erase scheme, many experiments must be conducted to determine the optimal GIDL design targets to achieve fast erase performance and secure yield characteristics. However, only a limited amount of data can be used since V-NAND processes are time-consuming and expensive in the early stage of development. TCAD and numerical methods also require a considerable amount of time and effort to calculate bit error rate (BER), and it is impossible to explore the entire design spaces in time. In this paper, we propose a novel simulation acceleration technique for bit error rate prediction and yield optimization in 3D V-NAND technology. This acceleration framework includes a machine learning (ML)-based compact model for the lognormal variability of GIDL currents and a physics-inspired slow cell model for the read margin reduction. Using a combination of these models with efficient Monte Carlo (MC) circuit simulations, we can accurately estimate threshold voltage ( $V_{th}$ ) distributions to explore the entire design spaces using a limited amount of data. Based on the proposed technique, the predictive model achieves high accuracy in the current 176-layer V-NAND technology, and it also provides high scalability with respect to GIDL transistor geometries, temperatures, supply voltages, variabilities, and the number of stacking layers. Moreover, a contour map of bit error rate is newly introduced for the efficient design space exploration and read margin prediction. Therefore, the results indicate that the proposed framework can be further extended to large-scale experimental data and new architectures to accelerate the yield optimization in next-generation 3D V-NAND flash memory development.

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.

Problem. Nowadays, one of the main tasks that tractor builders solve when creating new machinery is ensuring a comfortable driver's workplace. To ensure this, it is necessary to take into account the complex of ergonomic properties of the wheeled vehicle: comfort, smooth ride, vibration safety and more. Goal. That is why the purpose of this work is to determine the ergonomics of wheeled tractors when performing transportation of liquid cargo by trailer and semi-trailer tanks. According to many scientific papers, the redistribution of fluid in tractor tanks affects the dynamics of the wheeled tractor, especially when the weight of the unit is greater than the weight of the tractor. Therefore, it is advisable to study the effect of the amount of liquid in the tractor tank on the comfort level of the operator-driver. Confirmation of any theoretical studies must be accompanied by a whole series of experimental studies. Methodology. Therefore, in order to determine the ergonomic properties of wheeled tractors with units of variable weight, experimental tests were conducted on the base of a farmland. The measuring equipment consists of a mobile registration complex «VDVMM 4-001» and a radar sensor, which is designed to capture the true speed of the vehicle. Result. Based on the experiment, it was found that the standard acceleration rates, according to ISO 2631 (discomfort levels) for a single tractor and tractor with variable mass units (John Deere with MLT-16 and HTZ-150K with MLT-10), are subject to the level of “uncomfortable”. With the increase of the liquid level, both in the trailer tank and in the semi-trailer tank, it becomes “very uncomfortable”. Originality. The novelty of the work is the determination of ergonomic indicators of wheeled tractors with variable mass units and the dependence of the level of comfort on the height of the filling liquid tanks. Practical value. Therefore, based on the materials of this paper, it can be suggested that the in-depth study of the smooth running of wheeled tractors with variable mass units is feasible. In addition, the task is to reduce the external disturbance forces acting on the driver's seat.

Results of the analysis of scientific, technical and patent literature show that while having a great variety of constructive implementation of the proposed catchers there are no efficient and sufficiently reliable devices for catching conveyor belts at its reverse motion which are relatively simple in design. This is proved by practical activity of enterprises involved in extraction and processing of commercial minerals and other industries. A new design of a conveyor belt catcher that meets most requirements for the given equipment has been developed at the Institute of Mining, Ural of Branch of the Russian Academy of Sciences and then it has been tested under industrial conditions. The design makes provision for retention of the conveyor belt at its reverse motion beyond free edges from transported material. Catching devices are installed on both sides of the belt. Braking action of the belt at the reverse motion occurs due to its friction interaction with a catcher friction shoe located above the belt, and an eccentric mounted on the frame under the belt. A friction shoe is made with a concave curved surface facing the belt. The paper presents a calculation methodology of main parameters for the proposed design of catcher conveyor belts that permits to determine a force catching a conveyor belt down and for every braking period distance which has been passed by the belt, value of its compression, value of braking force, braking time and acceleration of belt motion, time and length of the distance passed by the belt to its full stop, parameters of a catcher and supporting structures, and other parameters. The paper also provides results of calculations for main design parameters of catching devices with an inclined conveyor having a belt width of 1400 mm for two catcher design versions: with location of an eccentric under the belt, and a brake shoe over the belt (option I) and with location of the eccentric over the conveyor belt, and the brake friction shoe under the belt (option II).

This paper is oriented towards the attitudes of the teachers and the gifted student parents on types of support gifted students receive in school in addition to extra classes, as well as towards parents’ attitudes on acceleration and special programs as forms of support for gifted students. Consequently, the goal of this paper is to find out: (1) teachers’ attitudes on types of support gifted students receive in school in addition to extra classes; (2) parents’ attitudes on types of support gifted students receive in school in addition to extra classes; (3) parents’ views on acceleration and special programs for the gifted students. The research involved 104 teachers and 30 parents of gifted students from multiple elementary and middle schools situated in Niš and Knjaževac. The instrument used to collect teachers’ attitudes is a mixed questionnaire, whereas the gifted student parents’ opinions and attitudes have been collected through the leading structured interview. Thus, the quantity data processing is based on the descriptive statistics, while the quality data, given in the narrative form, has been processed through the thematic content analysis, with the coding of key ideas into groups (units) with a common meaning. The findings of this research have shown that besides extra classes, schools organize other activities as well in order to encourage and stimulate giftedness in students, and the most common forms of support to the gifted students are: participation in contests and competitions, being part of extra classes and project groups, participation in cultural and social events, and rewarding. This study has also found that parents support the acceleration and special programs for gifted students, with a slight concern about separating a child from his/her peers.

With the rapid development of the Internet and mobile technology, the frequency of online fraud incidents continues to increase, and the fraudulent means are increasingly diverse. Traditional anti-fraud methods can no longer effectively deal with the serious security situation at present because of their own various shortcomings. In this paper, a device identification system based on acceleration sensor is constructed which takes into consideration the imperfections of the sensor in the manufacturing process and assembley process. The system can identify the user's device by taking advantages of the data collected in a flat static state, and thus confirm the user's identity. The acceleration data of the device is first collected, and then the data in flat static state is extracted through the state discrimination algorithm. After the feature extraction process, a 20-dimensional feature vector is obtained. Finally, a device identification model combining one-class classifier and multi-class classifier is trained. The model can identify unknown devices and classify known devices. The method proposed in this paper solves the problem that the device state cannot be determined in the real world. Further on we propose a multi-layer device identification model that can identify unknown device without training threshold. Compared with the previous studies in the literature, the biggest innovation of our method is to consider the user authentication of device fingerprint in the real world.

As a new energy conversion technology, triboelectric nanogenerator (TENG) can use the coupling of triboelectrification and electrostatic induction effect to convert tiny mechanical energy into electrical energy, powering small electronic devices. In this paper, a vibration sensing triboelectric nanogenerator (V-TENG) based on a foam nickel-PDMS composite film was prepared, which can convert low frequency and small-amplitude mechanical energy into electrical energy, and the open circuit voltage of V-TENG can reach 3.6V at a vibration frequency of 4 Hz. In addition, the V-TENG can be used as a self-powered speed/acceleration sensor to detect speed changes in the range of 0.3 m/s to 1.5 m/s and acceleration changes in the range of 3 m/s2 to 13 m/s2.

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.

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.

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.

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.

Three-dimensional finite element analysis (3D-FEA) models have been used to evaluate the shock-resistance responses of various equipments, including armaments mounted on a warship caused by underwater explosion (UNDEX). This paper aims to check the possibility of using one-dimensional (1D) FEA models for the shock-resistance responses. A frigate was chosen for the evaluation of the shock-resistance responses by the UNDEX. The frigate was divided into the thirteen discrete segments along the length of the ship. The 1D Timoshenko beam elements were used to model the frigate. The explosive charge mass and the stand-off distance were determined based on the ship length and the keel shock factor (KSF), respectively. The UNDEX pressure fields were generated using the Geers-Hunter doubly asymptotic model. The pseudo-velocity shock response spectrum (PVSS) for the 1D-FEA model (1D-PVSS) was calculated using the acceleration history at a concerned equipment position where the digital recursive filtering algorithm was used. The 1D-PVSS was compared with the 3D-PVSS that was taken from a reference, and a relatively good agreement was found. In addition, the 1D-PVSS was compared with the design criteria specified by the German Federal Armed forces, which is called the BV043. The 1D-PVSS was proven to be relatively reasonable, reducing the computing cost dramatically.

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

The cardinality constrained mean–variance (CCMV) portfolio selection model aims to identify a subset of the candidate assets such that the constructed portfolio has a guaranteed expected return and minimum variance. By formulating this model as the mixed-integer quadratic program (MIQP), the exact solution can be solved by a branch-and-bound algorithm. However, computational efficiency is the central issue in the time-sensitive portfolio investment due to its NP-hardness properties. To accelerate the solution speeds to CCMV portfolio optimization problems, we develop various heuristic methods based on techniques such as continuous relaxation, l1-norm approximation, integer optimization, and relaxation of semi-definite programming (SDP). We evaluate our heuristic methods by applying them to the US equity market dataset. The experimental results show that our SDP-based method is effective in terms of the computation time and the approximation ratio. Our SDP-based method performs even better than a commercial MIQP solver when the computational time is limited. In addition, several investment companies in China have adopted our methods, gaining good returns. This paper sheds light on the computation optimization for financial investments.

This paper introduces a mobile robot system that follows a human target, in particular, a robot system designed to follow a smartphone user. The proposed system integrates a global following method based on Wi-Fi radio intensity maps and a local following method based on matching walking states.“ Global following ”means that the robot follows the global trajectory of the human target. Because it is important to keep following when the target is lost in a crowded environment, we propose a global following system that uses Wi-Fi radio intensity and occupancy grid maps. This paper presents some experimental results for a robot being called to follow a human target using a Wi-Fi radio intensity map. “ Local following ”means that the robot always keeps close to the human target and keeps tracking the target without losing it. The human target is detected by cross-correlating the signals indicating the target ’s walking motion, including vertical acceleration data measured by the target user’s smartphone and the horizontal velocity of the legs measured by an LRF installed in the robot. The results show that the system produces a higher cross-correlation coefficient for the human target than for other pedestrians in the vicinity. The paper introduces a method for calculating the cross-correlation coefficients online and presents experimental results which show that the target can be identified from an online calculation of the cross-correlation coefficients.

Connected vehicle (CV) technologies are changing the form of traditional traffic models. In the CV driving environment, abundant and accurate information is available to vehicles, promoting the development of control strategies and models. Under these circumstances, this paper proposes a bidirectional vehicles information structure (BDVIS) by making use of the acceleration information of one preceding vehicle and one following vehicle to improve the car-following models. Then, we deduced the derived multiple vehicles information structure (DMVIS), including historical movement information of multiple vehicles, without the acceleration information. Next, the paper embeds the four kinds of basic car-following models into the framework to investigate the stability condition of two structures under the small perturbation of traffic flow and explored traffic response properties with different proportions of forward-looking or backward-looking terms. Under the open boundary condition, simulations on a single lane are conducted to validate the theoretical analysis. The results indicated that BDVIS and the DMVIS perform better than the original car-following model in improving the traffic flow stability, but that they have their own advantages for differently positioned vehicles in the platoon. Moreover, increasing the proportions of the preceding and following vehicles presents a benefit to stability, but if traffic is stable, an increase in any of the parameters would extend the influence time, which reveals that neither β1 or β2 is the biggest the best for the traffic.

In this paper, the authors consider the processes of dynamic interaction between the boiling particles of the dispersed phase of the emulsion leading to the large droplet breakup. Differences in the consideration of forces that determine the breaking of non-boiling and boiling droplets have been indicated in the study. They have been determined by the possibility of using the model to define the processes of displacement, deformation, or fragmentation of the inclusion of the dispersed phase under the influence of a set of neighboring particles. The dynamics of bubbles in a compressible liquid with consideration for interfacial heat and mass transfer has also been analyzed in the paper. The effect of standard and system parameters on the intensity of cavitation processes is considered. Physical transformations during the cavitation treatment of liquid are caused not only by shock waves and radiated pressure pulses but also by extreme thermal effects. At the stage of ultimate bubble compression, vapor inside the bubble and the liquid in its vicinity transform into the supercritical fluid state. The model analyzes microflow features in the inter-bubble space and quantitatively calculates local values of the velocity and pressure fields, as well as dynamic effects.

Nowadays, more automated or robotic twin-crane systems (RTCSs) are employed in ports and factories to improve material handling efficiency. In a twin-crane system, cranes must travel with a minimum safety distance between them to prevent interference. The crane trajectory prediction is critical to interference handling and crane scheduling. Current trajectory predictions lack accuracy because many details are simplified. To enhance accuracy and lessen the trajectory prediction time, a trajectory prediction approach with details (crane acceleration/deceleration, different crane velocities when loading/unloading, and trolley movement) is proposed in this paper. Simulations on different details and their combinations are conducted on a container terminal case study. According to the simulation results, the accuracy of the trajectory prediction can be improved by 20%. The proposed trajectory prediction approach is helpful for building a digital twin of RTCSs and enhancing crane scheduling.

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.

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.

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.

This Perspective paper explores recent moves seen in many countries toward accelerating the speed at which biomedical innovation can be delivered to the clinic. It discusses the drivers behind this and the rationale for it, illustrating this briefly in the field of regenerative medicine. It argues that the process reconfigures present/future relations, especially in terms of the relationship between different forms of evidence and risk calculations. The regulatory/innovation relationship is, as a result, being rewritten. Paradoxically, the moves toward acceleration are less to do with the arrival of a more streamlined evaluation system that selects for scientifically robust technologies ready for “the market.” In contrast, it reflects the growing complexity of innovation itself: whereas Latour (1987) had argued that “science-in the-making” was backstage in contrast to “ready-made science,” the former is now very visible. This in turn has generated two other parallel processes—“regulation-in-the-making” and “risk-in-the-making.” Such shifts can be seen in the field of regenerative medicine. The paper asks how best to engage with the move toward acceleration and thereby the future oversight of innovation.

During various marine container handling operations, performed mainly in larger-scale container terminals, containers get damaged regularly. Our previous studies showed that each physical impact results in some form of physical deformation of the backbone structure. Even at low accelerations, the spreaders of the quay cranes impact the containers with enough force to substantially bend the metal parts of the corners of the containers, when additional hooking procedures are required. This means that the first time resulted in the metal rods hitting the metal frame with an average 15-ton mass at the average speed of 1.7 m/s. The metal rods of the hooking mechanisms’ impact areas of the containers are structurally important, and each impact surely damages the containers, diminishing their total operational time. We have already proposed the Impacts Detection Methodology (IDM) and its application system, tested in Klaipeda City port, and it proved to be efficient in real-time operations, detecting concurrent impacts with each new handling cycle. In this paper, we provide a summarisation of a larger number of detections using the IDM, and as a result of this analysis, we have detected that more impact events happen when containers are taken from the upper parts of the ship, in comparison to the ones taken from the shafts. Results suggest that more critical events occur due to operator actions and experiences working with the machinery, yet the same operators tend to make fewer impact mistakes taking the containers from the shafts as the vertical cell guides tend to direct the movements and lower the levels of the natural sway of the spreader inside closed environments. This surely damages the metal infrastructure of the shafts, as seen in our previous study, but minimizes the chances of secondary impacts occurring during hooking.

. The problem of analytical synthesis of the control acceleration for an unmanned aerial vehicle (UAV) during its flight along a complex trajectory, consisting of sequentially located horizontal flight sections, located at different heights relative to the earth's surface has been solved in the paper. The problem has been solved as an analytical definition of the optimal control of a linear non-stationary system for a specified minimized quality functional. The mathematical model of the system is presented in the form of differential equations of UAV motion in the vertical plane of a fixed coordinate system related to the earth's surface. A feature of the proposed methodology for solving the problem is the substantiation of the original form of the minimized functional and parameters included in the law of variation of the control acceleration obtained by known methods. As the components of the quality functional, the values of coordinates and velocity of the UAV are considered and they are specified at the corresponding points in space through which the UAV path must pass, in order to obtain the optimal curvature of the trajectory. The derived mathematical dependences make it possible to implement them on board of an aircraft and, ultimately, solve the problem of ensuring the minimum energy consumption when controlling an object (UAV). Computer simulation of the analytically obtained results in the form of the UAV flight trajectory and the processes of changing its acceleration and speed have shown the efficiency of the proposed technique and the prospects of its use at the initial stage of the synthesis of the UAV control system.

As the aerospace industry has grown rapidly over the years, aviators and astronauts have been exposed to some abnormal physiological changes arising from the dynamics of the aerospace environment. The vestibular system, encoding linear and angular movements of the head, is one of the main affected systems in which those abnormal changes can occur during flight. Despite the intricate and solid organization, vestibular units are such delicate structures that they can easily be deceived by aerial dynamics and gravity changes. Therefore, it is of vital importance for the continuity of flight safety to be aware of the detrimental alterations and impairments regarding the vestibular system and its reflex pathways. The aim of this paper was to present a review about how a healthy vestibular system is negatively affected within the aerospace environment and how some vestibular disorders become exaggerated or impaired during aviation and space activities.