bluuebunny/crossref_metadata_2025 huggingface dataset:
Manufacturing 4.0: Checking the Feasibility of a Work Cell Using Asset Administration Shell and Physics-Based Three-Dimensional Digital Twins
Authors: Nguyen Quang-Duy , Huang Yining , Keith François , Leroy Christophe , Thi Minh-Thuyen , Dhouib Saadia
Published: January 2024

Feasibility checking is a step in manufacturing system engineering for verifying the normalization and effectiveness of a manufacturing system associated with a specific configuration of resources and processes. It enables factory operators to predict problems before operational time, thus preventing equipment and machinery accidents and reducing labor waste in physically organizing the shop floor. In Industry 4.0, feasibility checking becomes even more critical since emerging challenges, such as mass personalization, require reconfiguring work cells quickly and flexibly on demand. Regarding this need, digital twin technologies have emerged as an ideal candidate for practicing feasibility checking. Indeed, they are tools used to implement digital representations of manufacturing entities that can constitute a digital environment and context. Factory operators can test a manufacturing process within a digital environment in different contexts before the execution with physical resources. This approach currently receives significant attention from the manufacturing community; however, there is still a lack of sharing experiences to implement it. Thus, this paper contributes a methodology to engineer a digital environment and context for a manufacturing work cell using AAS digital twins and physics-based 3D digital twins technologies. Technically, this methodology is a specific case of N-DTs, a general methodology for engineering heterogeneous digital twins. The product assembly line case study, also presented in this paper, is a successful experiment applying the above contributions. The two methodologies and the case study can be helpful references for both public and private sectors to deploy their feasibility-checking frameworks and deal with heterogeneous digital twins in general.
Research on Decision Analysis with CVaR for Supply Chain Finance Based on Blockchain Technology
Authors: Ma Shujian , Cai Jilong , Wang Gang , Ge Xiangxiang , Teng Ying , Jiang Hua
Published: January 2024

The application of blockchain has become a trend in the development of supply chain finance. Aiming to bridge the gap in the existing literature, this paper investigates a supply chain finance system based on blockchain technology which contains a manufacturer, a retailer and a financial institution and incorporates blockchain costs into the model. Firstly, this paper establishes a supply chain finance model based on blockchain technology and it presents a comparison with the process employed under the traditional model. Secondly, this paper establishes the revenue mathematical model of supply chain finance based on blockchain technology. Thirdly, the optimal decisions of each participant under centralized and decentralized decision-making are proved and obtained, respectively, and the influencing factors of the optimal decisions are analyzed. Finally, the conclusions are verified via simulations. This study finds that, when blockchain is used, the benefits of each participant in the chain are increased. In addition, centralized decision-making, which is more optimal in the traditional model, is also enhanced under blockchain. This paper demonstrates the superiority of blockchain-enabled supply chain finance in terms of model and revenue. This provides some suggestions for companies in the supply chain with regard to solving the problem of financing difficulties.
Influential Yield Strength of Steel Materials with Return Random Walk Gravity Centrality
Authors: Rodríguez Rocío , Curado Manuel , Rodríguez Francy D. , Vicent José F.
Published: January 2024

In complex networks, important nodes have a significant impact, both functional and structural. From the perspective of data flow pattern detection, the evaluation of the importance of a node in a network, taking into account the role it plays as a transition element in random paths between two other nodes, has important applications in many areas. Advances in complex networks and improved data generation are very important for the growth of computational materials science. The search for patterns of behavior of the elements that make up steels through complex networks can be very useful in understanding their mechanical properties. This work aims to study the influence of the connections between the elements of steel and the impact of these connections on their mechanical properties, more specifically on the yield strength. The patterns found in the results show the significance of the proposed approach for the development of new steel compositions.
Robust Portfolio Choice under the Modified Constant Elasticity of Variance
Authors: Fan Wei Li , Anel Marcos Escobar
Published: January 2024

This study investigates ambiguity aversion within the framework of a utility-maximizing investor under a modified constant-elasticity-of-volatility (M-CEV) model for the underlying asset. We derive closed-form solutions of a non-affine type for the optimal allocation and value function via a Cauchy problem. This work generalizes previous results in non-ambiguous settings by extending existing work to Hyperbolic Absolute Risk Aversion utility (HARA), correcting some typos in the literature for Constant Relative Risk Aversion utility (CRRA). Helpful details and derivations are also included in the manuscript.
Chern Flat and Chern Ricci-Flat Twisted Product Hermitian Manifolds
Authors: Li Shuwen , He Yong , Lu Weina , Yang Ruijia
Published: January 2024

Let (M1,g) and (M2,h) be two Hermitian manifolds. The twisted product Hermitian manifold (M1×M2f,G) is the product manifold M1×M2 endowed with the Hermitian metric G=g+f2h, where f is a positive smooth function on M1×M2. In this paper, the Chern curvature, Chern Ricci curvature, Chern Ricci scalar curvature and holomorphic sectional curvature of the twisted product Hermitian manifold are derived. The necessary and sufficient conditions for the compact twisted product Hermitian manifold to have constant holomorphic sectional curvature are obtained. Under the condition that the logarithm of the twisted function is pluriharmonic, it is proved that the twisted product Hermitian manifold is Chern flat or Chern Ricci-flat, if and only if M1,g and M2,h are Chern flat or Chern Ricci-flat, respectively.
Regeneration and Long-Term Stability of a Low-Power Eco-Friendly Temperature Sensor Based on a Hydrogel Nanocomposite
Authors: Landi Giovanni , Pagano Sergio , Granata Veronica , Avallone Guerino , La Notte Luca , Palma Alessandro Lorenzo , Sdringola Paolo , Puglisi Giovanni , Barone Carlo
Published: January 2024

A water-processable and low-cost nanocomposite material, based on gelatin and graphene, has been used to fabricate an environmentally friendly temperature sensor. Demonstrating a temperature-dependent open-circuit voltage between 260 and 310 K, the sensor effectively detects subzero ice formation. Notably, it maintains a constant temperature sensitivity of approximately −19 mV/K over two years, showcasing long-term stability. Experimental evidence demonstrates the efficient regeneration of aged sensors by injecting a few drops of water at a temperature higher than the gelation point of the hydrogel nanocomposite. The real-time monitoring of the electrical characteristics during the hydration reveals the initiation of the regeneration process at the gelation point (~306 K), resulting in a more conductive nanocomposite. These findings, together with a fast response and low power consumption in the range of microwatts, underscore the potential of the eco-friendly sensor for diverse practical applications in temperature monitoring and environmental sensing. Furthermore, the successful regeneration process significantly enhances its sustainability and reusability, making a valuable contribution to environmentally conscious technologies.
A Comprehensive Review of Lithium-Ion Battery (LiB) Recycling Technologies and Industrial Market Trend Insights
Authors: He Bowen , Zheng Han , Tang Karl , Xi Ping , Li Muqing , Wei Laiwei , Guan Qun
Published: January 2024

Adopting EVs has been widely recognized as an efficient way to alleviate future climate change. Nonetheless, the large number of spent LiBs associated with EVs is becoming a huge concern from both environmental and energy perspectives. This review summarizes the three most popular LiB recycling technologies, the current LiB recycling market trend, and global recycling magnates’ industrial dynamics regarding this subject. We mainly focus on reviewing hydrometallurgical and direct recycling technologies to discuss the advancement of those recycling technologies and their future commercialization pathway.
Wharton’s Jelly Tissue Allograft for Connective Tissue Defects Surrounding Nerves in the Tarsal Tunnel: A Retrospective Case Series
Authors: Bruton Ronald , Gilliland Tracie L. , Shou John J. , Woods Crislyn G. , Lambert Naomi E. , Barrett Tyler C.
Published: January 2024

Caused by age or trauma, collapsed connective tissue can cause nerve entrapment and damage within the tarsal tunnel. Tarsal tunnel syndrome is relatively underdiagnosed. This study presents an intervention targeting damaged tissues surrounding the nerves and replacing the structural cushioning with a Wharton’s jelly tissue allograft. The eight patients in our study, selected from four clinical sites, had tarsal tunnel-related defects. Patient outcomes were tracked on a 90-day calendar utilizing the Numeric Pain Rating Scale (NPRS) and the Western Ontario and McMaster University Arthritis Index (WOMAC). All patients had failed standard care practices for at least six weeks. Each patient received a Wharton’s jelly tissue allograft to sites around the affected tarsal tunnel. No patients experienced adverse reactions. The percent change results calculated from the initial application to the 90-day follow-up showed an improvement of 59.43% in NPRS and a 37.58% improvement in WOMAC. This study provides evidence that WJ allograft applications are safe, minimally invasive, and efficacious for patients who have failed standard care treatments for tissue defects associated with tarsal tunnel syndrome. The limitations of this study include its small cohort size and nonblinded nature. The results of this study warrant further research to confirm the efficacy, optimal dose, protocol, and durability of Wharton’s jelly.
A Novel Sparse Array Configuration for Direction of Arrival Estimation with Increased Uniform Degrees of Freedom and Reduced Mutual Coupling
Authors: Wei Shuang , Zhu Gencun , Su Ying
Published: January 2024

Sparse arrays are widely employed in array signal processing due to their obvious advantages in array element distribution and uniform degrees of freedom (uDOFs). In this paper, a generalized augmented multi-subarray nested array (GAMSNA-I) and its variant, GAMSNA-II are proposed, with the objective of increasing uDOFs and reducing mutual coupling. Based on two subarrays of the prototype nested array (NA), GAMSNA-I is constructed by reconfiguring the dense uniform linear array (ULA) and forward-shifting the sparse ULA. GAMSNA-II is obtained by sparsifying the dense part of GAMSNA-I, ensuring constant uDOFs while further reducing mutual coupling. Subsequently, the closed-form expression for the uDOFs of GAMSNA-I with an arbitrary number of sensors is derived, and the proof is provided that the uDOFs of GAMSNA-II remain unchanged relative to that of GAMSNA-I. Compared to some existing array configurations, both GAMSNA-I and GAMSNA-II exhibit improved uDOFs, with GAMSNA-II achieving lower mutual coupling. Simulation results show the superior performance of the proposed GAMSNA-I and GAMSNA-II.
Waste Material Classification: A Short-Wave Infrared Discrete-Light-Source Approach Based on Light-Emitting Diodes
Authors: Manakkakudy Anju , De Iacovo Andrea , Maiorana Emanuele , Mitri Federica , Colace Lorenzo
Published: January 2024

Waste material classification is a challenging yet important task in waste management. The realization of low-cost waste classification systems and methods is critical to meet the ever-increasing demand for efficient waste management and recycling. In this paper, we demonstrate a simple, compact and low-cost classification system based on optical reflectance measurements in the short-wave infrared for the segregation of waste materials such as plastics, paper, glass, and aluminium. The system comprises a small set of LEDs and one single broadband photodetector. All devices are controlled through low-cost and low-power electronics, and data are gathered and managed via a computer interface. The proposed system reaches accuracy levels as high as 94.3% when considering seven distinct materials and 97.0% when excluding the most difficult to classify, thus representing a valuable proof-of-concept for future system developments.
Numerical Analysis for Appropriate Positioning of Ferrous Wear Debris Sensors with Permanent Magnet in Gearbox Systems
Authors: Hong Sung-Ho
Published: January 2024

In order to improve the measurement sensitivity of ferrous wear debris sensors with a permanent magnet, a new numerical approach to the appropriate position of the sensor is presented. Moreover, a flow guide wall is proposed as a way to concentrate flow around the ferrous particle sensors. The flow guide wall is intended to further improve measurement sensitivity by allowing the flow containing ferrous particles to flow around the sensor. Numerical analysis was performed using the multi-physics analysis method for the most representative gearbox of the sump-tank type. In condition diagnosis using ferrous wear debris sensors, the position of the sensor has a great influence. In other words, there are cases where no measurements occur, despite the presence of abnormal wear and damage due to the wrong sensor position. To determine the optimal sensor position, this study used flow analysis for the flow caused by the movement of the gear, electric and magnetic field analysis to implement the sensor, and a particle tracing technique to track particle trajectory. The new analysis method and results of this study will provide important information for selecting the optimal sensor location and for the effective application of ferrous wear debris sensors, and will contribute to the oil sensor-based condition diagnosis technology.
Optimizing Sensorless Control in PMSM Based on the SOGIFO-X Flux Observer Algorithm
Authors: Jin Rencheng , Chen Ji , Hu Peihao , Li Jianzhang
Published: January 2024

In the realm of sensorless control for a permanent magnet synchronous motor (PMSM), the flux observer algorithm is widely recognized. However, the estimation accuracy of rotor position is adversely impacted by the interference from DC bias and high-order harmonics. To address these issues, an advanced flux observation method, second-order generalized integrator flux observer extend (SOGIFO-X), is introduced in this paper. The study begins with a theoretical analysis to establish the relationship between flux observation error and rotor position error. The SOGIFO-X method, developed in this study, is compared with traditional methods such as the Low Pass Filter (LPF) and second-order generalized integrator flux observer (SOGIFO), employing mathematical rigor and Bode plot analysis. The emphasis is on the methodology and the general performance improvements SOGIFO-X offers over conventional methods. Simulations and experiments were conducted to assess the impact of SOGIFO-X on the steady-state and dynamic performances of sensorless control. Findings indicate that SOGIFO-X demonstrates significant enhancements in terms of reducing the reduced flux observation error, contributing to the advancement of position estimation accuracy and sensorless motor control technology.
SyS3DS: Systematic Sampling of Large-Scale LiDAR Point Clouds for Semantic Segmentation in Forestry Robotics
Authors: Mukhandi Habibu , Ferreira Joao Filipe , Peixoto Paulo
Published: January 2024

Recently, new semantic segmentation and object detection methods have been proposed for the direct processing of three-dimensional (3D) LiDAR sensor point clouds. LiDAR can produce highly accurate and detailed 3D maps of natural and man-made environments and is used for sensing in many contexts due to its ability to capture more information, its robustness to dynamic changes in the environment compared to an RGB camera, and its cost, which has decreased in recent years and which is an important factor for many application scenarios. The challenge with high-resolution 3D LiDAR sensors is that they can output large amounts of 3D data with up to a few million points per second, which is difficult to process in real time when applying complex algorithms and models for efficient semantic segmentation. Most existing approaches are either only suitable for relatively small point clouds or rely on computationally intensive sampling techniques to reduce their size. As a result, most of these methods do not work in real time in realistic field robotics application scenarios, making them unsuitable for practical applications. Systematic point selection is a possible solution to reduce the amount of data to be processed. Although our approach is memory and computationally efficient, it selects only a small subset of points, which may result in important features being missed. To address this problem, our proposed systematic sampling method called SyS3DS (Systematic Sampling for 3D Semantic Segmentation) incorporates a technique in which the local neighbours of each point are retained to preserve geometric details. SyS3DS is based on the graph colouring algorithm and ensures that the selected points are non-adjacent in order to obtain a subset of points that are representative of the 3D points in the scene. To take advantage of the ensemble learning method, we pass a different subset of nodes for each epoch. This leverages a new technique called auto-ensemble, where ensemble learning is proposed as a collection of different learning models instead of tuning different hyperparameters individually during training and validation. SyS3DS has been shown to process up to 1 million points in a single pass. It outperforms the state of the art in efficient semantic segmentation on large datasets such as Semantic3D. We also present a preliminary study on the validity of the performance of LiDAR-only data, i.e., intensity values from LiDAR sensors without RGB values for semi-autonomous robot perception.
A Global Positioning System Used to Monitor the Physical Performance of Elite Beach Handball Referees in a Spanish Championship
Authors: Martínez-Rodríguez Alejandro , Sánchez-Sánchez Javier , López-Fernández Jorge , Lara-Cobos Daniel , Sánchez-Sáez Juan Antonio
Published: January 2024

Beach handball is a fully developed sporting discipline on all five continents which has attracted the attention of researchers in the last decade, resulting in a proliferation of different studies focusing on players but not on referees. The main objective of this cross-sectional research was to determine the physical demands on elite male beach handball referees in four different competitions: U18 male; U18 female; senior male; and senior female. Twelve elite federated male referees (age: 30.86 ± 8 years; body height: 175.72 ± 4.51 cm; body weight: 80.18 ± 17.99 kg; fat percentage: 20.1 ± 4.41%; national or international experience) belonging to the Technical Committee of the Royal Spanish Handball Federation were recruited for this the study. The physical demands required of referees in official matches were measured by installing a GPS device. The sampling frequency used to record their speed and distance was 15 Hz. A triaxial accelerometer (100 Hz) was used to determine their acceleration. An analysis of variance (ANOVA) between competitions with post hoc comparisons using the Bonferroni adjustment was used to compare among categories. A higher distance covered in zone 1 and speeds of 0 to 6 km-h−1 were recorded. Most accelerations and decelerations occurred in zones 0 and 1 (zone 0: 0 to 1 m·s−2; zone 1: 1 to 2 m·s−2). The lack of differences (p > 0.05) between most analysed variables suggest quite similar physical demands of the four analysed competitions. These results provide relevant information to design optimal training plans oriented to the real physical demands on referees in an official competition.
Reinforcement Learning-Based Joint Beamwidth and Beam Alignment Interval Optimization in V2I Communications
Authors: Lee Jihun , Kim Hun , So Jaewoo
Published: January 2024

The directional antenna combined with beamforming is one of the attractive solutions to accommodate high data rate applications in 5G vehicle communications. However, the directional nature of beamforming requires beam alignment between the transmitter and the receiver, which incurs significant signaling overhead. Hence, we need to find the optimal parameters for directional beamforming, i.e., the antenna beamwidth and beam alignment interval, that maximize the throughput, taking the beam alignment overhead into consideration. In this paper, we propose a reinforcement learning (RL)-based beamforming scheme in a vehicle-to-infrastructure system, where we jointly determine the antenna beamwidth and the beam alignment interval, taking into account the past and future rewards. The simulation results show that the proposed RL-based joint beamforming scheme outperforms conventional beamforming schemes in terms of the average throughput and the average link stability ratio.
Mathematically Improved XGBoost Algorithm for Truck Hoisting Detection in Container Unloading
Authors: Wu Nian , Hu Wenshan , Liu Guo-Ping , Lei Zhongcheng
Published: January 2024

Truck hoisting detection constitutes a key focus in port security, for which no optimal resolution has been identified. To address the issues of high costs, susceptibility to weather conditions, and low accuracy in conventional methods for truck hoisting detection, a non-intrusive detection approach is proposed in this paper. The proposed approach utilizes a mathematical model and an extreme gradient boosting (XGBoost) model. Electrical signals, including voltage and current, collected by Hall sensors are processed by the mathematical model, which augments their physical information. Subsequently, the dataset filtered by the mathematical model is used to train the XGBoost model, enabling the XGBoost model to effectively identify abnormal hoists. Improvements were observed in the performance of the XGBoost model as utilized in this paper. Finally, experiments were conducted at several stations. The overall false positive rate did not exceed 0.7% and no false negatives occurred in the experiments. The experimental results demonstrated the excellent performance of the proposed approach, which can reduce the costs and improve the accuracy of detection in container hoisting.
Two-Stage Atomic Decomposition of Multichannel EEG and the Previously Undetectable Sleep Spindles
Authors: Durka Piotr , Dovgialo Marian , Duszyk-Bogorodzka Anna , Biegański Piotr
Published: January 2024

We propose a two-step procedure for atomic decomposition of multichannel EEGs, based upon multivariate matching pursuit and dipolar inverse solution, from which atoms representing relevant EEG structures are selected according to prior knowledge. We detect sleep spindles in 147 polysomnographic recordings from the Montreal Archive of Sleep Studies. Detection is compared with human scorers and two state-of-the-art algorithms, which find only about a third of the structures conforming to the definition of sleep spindles and detected by the proposed method. We provide arguments supporting the thesis that the previously undetectable sleep spindles share the same properties as those marked by human experts and previously applied methods, and were previously omitted only because of unfavorable local signal-to-noise ratios, obscuring their visibility to both human experts and algorithms replicating their markings. All detected EEG structures are automatically parametrized by their time and frequency centers, width duration, phase, and spatial location of an equivalent dipolar source within the brain. It allowed us, for the first time, to estimate the spatial gradient of sleep spindles frequencies, which not only confirmed quantitatively the well-known prevalence of higher frequencies in posterior regions, but also revealed a significant gradient in the sagittal plane. The software used in this study is freely available.
Allocation of Eavesdropping Attacks for Multi-System Remote State Estimation
Authors: Chang Xiaoyan , Peng Lianghong , Zhang Suzhen
Published: January 2024

In recent years, the problem of cyber–physical systems’ remote state estimations under eavesdropping attacks have been a source of concern. Aiming at the existence of eavesdroppers in multi-system CPSs, the optimal attack energy allocation problem based on a SINR (signal-to-noise ratio) remote state estimation is studied. Assume that there are N sensors, and these sensors use a shared wireless communication channel to send their state measurements to the remote estimator. Due to the limited power, eavesdroppers can only attack M channels out of N channels at most. Our goal is to use the Markov decision processes (MDP) method to maximize the eavesdropper’s state estimation error, so as to determine the eavesdropper’s optimal attack allocation. We propose a backward induction algorithm which uses MDP to obtain the optimal attack energy allocation strategy. Compared with the traditional induction algorithm, this algorithm has lower computational cost. Finally, the numerical simulation results verify the correctness of the theoretical analysis.
MESMERIC: Machine Learning-Based Trust Management Mechanism for the Internet of Vehicles
Authors: Wang Yingxun , Mahmood Adnan , Sabri Mohamad Faizrizwan Mohd , Zen Hushairi , Kho Lee Chin
Published: January 2024

The emerging yet promising paradigm of the Internet of Vehicles (IoV) has recently gained considerable attention from researchers from academia and industry. As an indispensable constituent of the futuristic smart cities, the underlying essence of the IoV is to facilitate vehicles to exchange safety-critical information with the other vehicles in their neighborhood, vulnerable pedestrians, supporting infrastructure, and the backbone network via vehicle-to-everything communication in a bid to enhance the road safety by mitigating the unwarranted road accidents via ensuring safer navigation together with guaranteeing the intelligent traffic flows. This requires that the safety-critical messages exchanged within an IoV network and the vehicles that disseminate the same are highly reliable (i.e., trustworthy); otherwise, the entire IoV network could be jeopardized. A state-of-the-art trust-based mechanism is, therefore, highly imperative for identifying and removing malicious vehicles from an IoV network. Accordingly, in this paper, a machine learning-based trust management mechanism, MESMERIC, has been proposed that takes into account the notions of direct trust (encompassing the trust attributes of interaction success rate, similarity, familiarity, and reward and punishment), indirect trust (involving confidence of a particular trustor on the neighboring nodes of a trustee, and the direct trust between the said neighboring nodes and the trustee), and context (comprising vehicle types and operating scenarios) in order to not only ascertain the trust of vehicles in an IoV network but to segregate the trustworthy vehicles from the untrustworthy ones by means of an optimal decision boundary. A comprehensive evaluation of the envisaged trust management mechanism has been carried out which demonstrates that it outperforms other state-of-the-art trust management mechanisms.
Sample Entropy Improves Assessment of Postural Control in Early-Stage Multiple Sclerosis
Authors: Cofré Lizama L. Eduardo , He Xiangyu , Kalincik Tomas , Galea Mary P. , Panisset Maya G.
Published: January 2024

Postural impairment in people with multiple sclerosis (pwMS) is an early indicator of disease progression. Common measures of disease assessment are not sensitive to early-stage MS. Sample entropy (SE) may better identify early impairments. We compared the sensitivity and specificity of SE with linear measurements, differentiating pwMS (EDSS 0–4) from healthy controls (HC). 58 pwMS (EDSS ≤ 4) and 23 HC performed quiet standing tasks, combining a hard or foam surface with eyes open or eyes closed as a condition. Sway was recorded at the sternum and lumbar spine. Linear measures, mediolateral acceleration range with eyes open, mediolateral jerk with eyes closed, and SE in the anteroposterior and mediolateral directions were calculated. A multivariate ANOVA and AUC-ROC were used to determine between-groups differences and discriminative ability, respectively. Mild MS (EDSS ≤ 2.0) discriminability was secondarily assessed. Significantly lower SE was observed under most conditions in pwMS compared to HC, except for lumbar and sternum SE when on a hard surface with eyes closed and in the anteroposterior direction, which also offered the strongest discriminability (AUC = 0.747), even for mild MS. Overall, between-groups differences were task-dependent, and SE (anteroposterior, hard surface, eyes closed) was the best pwMS classifier. SE may prove a useful tool to detect subtle MS progression and intervention effectiveness.
Reference-Free Vibration-Based Damage Identification Techniques for Bridge Structural Health Monitoring—A Critical Review and Perspective
Authors: Moravvej Mohammad , El-Badry Mamdouh
Published: January 2024

Bridges are designed and built to be safe against failure and perform satisfactorily over their service life. Bridge structural health monitoring (BSHM) systems are therefore essential to ensure the safety and serviceability of such critical transportation infrastructure. Identification of structural damage at the earliest time possible is a major goal of BSHM processes. Among many developed damage identification techniques (DITs), vibration-based techniques have shown great potential to be implemented in BSHM systems. In a vibration-based DIT, the response of a bridge is measured and analyzed in either time or space domain for the purpose of detecting damage-induced changes in the extracted dynamic properties of the bridge. This approach usually requires a comparison between two structural states of the bridge—the current state and a reference (intact/undamaged) state. In most in-situ cases, however, data on the bridge structural response in the reference state are not available. Therefore, researchers have been recently working on the development of DITs that eliminate the need for a prior knowledge of the reference state. This paper thoroughly explains why and how the reference state can be excluded from the damage identification process. It then reviews the state-of-the-art reference-free vibration-based DITs and summarizes their merits and shortcomings to give guidance on their applicability to BSHM systems. Finally, some recommendations are given for further research.
Feasibility of Using a GENEActiv Accelerometer with Triaxial Acceleration and Temperature Sensors to Monitor Adherence to Shoulder Sling Wear Following Surgery
Authors: Barakat Ahmed , Manga Abdurrahmaan , Sheikh Aneesa , McWilliams Ryan , Rowlands Alex V. , Singh Harvinder
Published: January 2024

Background: Self-reported adherence to sling wear is unreliable due to recall bias. We aim to assess the feasibility and accuracy of quantifying sling wear and non-wear utilising slings pre-fitted with a GENEActiv accelerometer that houses triaxial acceleration and temperature sensors. Methods: Ten participants were asked to wear slings for 480 min (8 h) incorporating 180 min of non-wear time in durations varying from 5–120 min. GENEActiv devices were fitted in sutured inner sling pockets and participants logged sling donning and doffing times. An algorithm based on variability in acceleration in three axes and temperature change was developed to identify sling wear and non-wear and compared to participants’ logs. Results: There was no significant difference between algorithm detected non-wear duration (mean ± standard deviation = 172.0 ± 6.8 min/participant) and actual non-wear (179.7 ± 1.0 min/participant). Minute-by-minute agreement of sensor-detected wear and non-wear with participant reported wear was 97.3 ± 1.5% (range = 93.9–99.0), with mean sensitivity 94.3 ± 3.5% (range = 86.1–98.3) and specificity 99.1 ± 0.8% (range = 93.7–100). Conclusion: An algorithm based on accelerometer-assessed acceleration and temperature can accurately identify shoulder sling wear/non-wear times. This method may have potential for assessing whether sling wear adherence after shoulder surgeries have any bearing on patient functional outcomes.
Hour-Ahead Photovoltaic Power Prediction Combining BiLSTM and Bayesian Optimization Algorithm, with Bootstrap Resampling for Interval Predictions
Authors: Herrera-Casanova Reinier , Conde Arturo , Santos-Pérez Carlos
Published: January 2024

Photovoltaic (PV) power prediction plays a critical role amid the accelerating adoption of renewable energy sources. This paper introduces a bidirectional long short-term memory (BiLSTM) deep learning (DL) model designed for forecasting photovoltaic power one hour ahead. The dataset under examination originates from a small PV installation located at the Polytechnic School of the University of Alcala. To improve the quality of historical data and optimize model performance, a robust data preprocessing algorithm is implemented. The BiLSTM model is synergistically combined with a Bayesian optimization algorithm (BOA) to fine-tune its primary hyperparameters, thereby enhancing its predictive efficacy. The performance of the proposed model is evaluated across diverse meteorological and seasonal conditions. In deterministic forecasting, the findings indicate its superiority over alternative models employed in this research domain, specifically a multilayer perceptron (MLP) neural network model and a random forest (RF) ensemble model. Compared with the MLP and RF reference models, the proposed model achieves reductions in the normalized mean absolute error (nMAE) of 75.03% and 77.01%, respectively, demonstrating its effectiveness in this type of prediction. Moreover, interval prediction utilizing the bootstrap resampling method is conducted, with the acquired prediction intervals carefully adjusted to meet the desired confidence levels, thereby enhancing the robustness and flexibility of the predictions.
Concurrent Validity of Four Activity Monitors in Older Adults
Authors: Wullems Jorgen A. , Verschueren Sabine M. P. , Degens Hans , Morse Christopher I. , Onambélé-Pearson Gladys L.
Published: January 2024

Sedentary behaviour (SB) and physical activity (PA) have been shown to be independent modulators of healthy ageing. We thus investigated the impact of activity monitor placement on the accuracy of detecting SB and PA in older adults, as well as a novel random forest algorithm trained on data from older persons. Four monitor types (ActiGraph wGT3X-BT, ActivPAL3c VT, GENEActiv Original, and DynaPort MM+) were simultaneously worn on five anatomical sites during ten different activities by a sample of twenty older adults (70.0 (12.0) years; 10 women). The results indicated that collecting metabolic equivalent (MET) data for 60 s provided the most representative results, minimising variability. In addition, thigh-worn monitors, including ActivPAL, Random Forest, and Sedentary Sphere—Thigh, exhibited superior performance in classifying SB, with balanced accuracies ≥ 94.2%. Other monitors, such as ActiGraph, DynaPort MM+, and GENEActiv Sedentary Sphere—Wrist, demonstrated lower performance. ActivPAL and GENEActiv Random Forest outperformed other monitors in participant-specific balanced accuracies for SB classification. Only thigh-worn monitors achieved acceptable overall balanced accuracies (≥80.0%) for SB, standing, and medium-to-vigorous PA classifications. In conclusion, it is advisable to position accelerometers on the thigh, collect MET data for ≥60 s, and ideally utilise population-specific trained algorithms.
FPGA Implementation of Complex-Valued Neural Network for Polar-Represented Image Classification
Authors: Ahmad Maruf , Zhang Lei , Chowdhury Muhammad E. H.
Published: January 2024

This proposed research explores a novel approach to image classification by deploying a complex-valued neural network (CVNN) on a Field-Programmable Gate Array (FPGA), specifically for classifying 2D images transformed into polar form. The aim of this research is to address the limitations of existing neural network models in terms of energy and resource efficiency, by exploring the potential of FPGA-based hardware acceleration in conjunction with advanced neural network architectures like CVNNs. The methodological innovation of this research lies in the Cartesian to polar transformation of 2D images, effectively reducing the input data volume required for neural network processing. Subsequent efforts focused on constructing a CVNN model optimized for FPGA implementation, emphasizing the enhancement of computational efficiency and overall performance. The experimental findings provide empirical evidence supporting the efficacy of the image classification system developed in this study. One of the developed models, CVNN_128, achieves an accuracy of 88.3% with an inference time of just 1.6 ms and a power consumption of 4.66 mW for the classification of the MNIST test dataset, which consists of 10,000 frames. While there is a slight concession in accuracy compared to recent FPGA implementations that achieve 94.43%, our model significantly excels in classification speed and power efficiency—surpassing existing models by more than a factor of 100. In conclusion, this paper demonstrates the substantial advantages of the FPGA implementation of CVNNs for image classification tasks, particularly in scenarios where speed, resource, and power consumption are critical.
Comparison of 10% vs. 30% Velocity Loss during Squat Training with Low Loads on Strength and Sport-Specific Performance in Young Soccer Players
Authors: Rojas-Jaramillo Andrés , León-Sánchez Gustavo , Calvo-Lluch África , González-Badillo Juan José , Rodríguez-Rosell David
Published: January 2024

The aim of this study was to compare the effects of two velocity-based resistance training (RT) programs using moderate loads (45–60% 1RM) but different magnitudes of velocity loss (VL) limits (10% vs. 30%) on the changes in physical performance in young soccer players. Twenty young soccer players were randomly allocated into two groups: VL10% (n = 10) and VL30% (n = 10). All participants were assessed before and after the 8-week RT program (twice a week) involving the following tests: 20 m running sprint (T20), countermovement jump (CMJ), kicking a ball (KB), and progressive loading test in the full squat (SQ) exercise. The RT program was conducted using only the SQ exercise and movement velocity was monitored in all repetitions. Significant ‘time × group’ interaction (p < 0.05) was observed for sprint performance, KB and 1RM in the SQ exercise in favor of VL10%. No significant changes between groups at post-test were observed. The VL10% resulted in significant (p < 0.05–0.001) intra-group changes in all variables analyzed, except for KB, whereas VL30% only showed significant (p < 0.05) performance increments in a sprint test and 1RM in the SQ exercise. The percentage of change and the intra-group’s effect size were of greater magnitude for VL10% in all variables analyzed compared to VL30%. In conclusion, our results suggest that, for non-trained young soccer players, squat training with low to moderate relative loads and 10%VL is sufficient to elicit significant increases in muscle strength and sport-specific actions compared to 30%VL in the set.
The Canine Vaginal Flora: A Large-Cohort Retrospective Study
Authors: Leps Anna Sophia , Klein Babette , Schneider Marianne , Meyer Cornelia , Šoba Alexandra , Simon Christine , Dyachenko Viktor , Siesenop Ute , Verspohl Jutta , Goericke-Pesch Sandra
Published: January 2024

Microbiological examinations are frequently performed as part of breeding management examinations in the bitch, but also in case of (suspected) reproductive tract problems. As most bacteria are opportunistic pathogens, evaluation of bacterial findings is challenging for veterinarians. Besides, breeders might request antimicrobial treatment in breeding bitches, fearing conception failure—even without medical indication. Considering the rising threat of antimicrobial resistance, gaining deeper insights into the bacterial findings from the vagina of healthy and (suspected) reproductive-diseased bitches might contribute to the knowledge of the canine aerobic vaginal flora and consequently improve the responsible use of antibiotics. We analyzed results from bacteriological cultures of 23,254 vaginal swabs sent in to three commercial laboratories in Germany between 2015 and 2021, where standard aerobic microbiological examination was carried out. We found a variety of 319 bacterial species that mostly grew in mixed cultures of two or more bacterial species. Commonly found species were Escherichia coli, beta-hemolytic Streptococci, coagulase-positive Staphylococci, Pasteurellales, and aerobic sporulators, as well as other Streptococcus spp. Our results showed a large diversity of the canine vaginal flora in healthy and (suspected) reproductive-diseased bitches. They largely support earlier findings of small studies on the physiological canine vaginal flora, emphasizing that solely the results of a bacterial evaluation should not be the base for antimicrobial treatment. Instead, bacterial findings should be evaluated with the results of a clinical gynecological examination.
Les nouveaux modes d’utilisation des établissements publics
Authors: Heurté André
Published: January 2024

New ways of using state enterprises

Although modern State enterprise is based on the principle of specialisation, its purpose confers on it a specific geographic role. Moreover, a whole host of links on the organic, financial and staff levels grow up between it and other organisations. In the Bouches du Rhône, Vaucluse and the Alpes departements, State enterprises can be divided into three categories. Most of them were set up on a unilateral basis. Others however are the resuit of a combination of interests. The Port of Fos industrial complex, which is without doubt a unique experiment, consists of a group of State-run industries. Despite the success achieved, it has so far not proved possible to co-ordinate administrative action and the priority given to industrial and commercial interests has entailed a decline in the concern shown for the interests of the population as a whole.
L’économie mixte, procédé d’administration publique dans la région Provence-Alpes-Côte d’Azur
Authors: Prats Yves
Published: January 2024

The semi-public sector ; public administration procédure in the Provence-Alpes-Cote d’Azur region

The creation of a semi-public enterprise is an administrative procedure which has been used in France since the beginning of the century ; in its broadest form it means that one or more regional public bodies own the public portion of a company’s capital. But one might well ask how long this traditional definition of a semi-public enterprise as meaning joint public and private ownership of the capital is likely to last. In fact, local semi-public companies, which is the favourite System of local authorities for carrying out their development projects, are in practice a means to enable minor communities to combine their operations and, on the rare occasions when private capital is involved, it is generally minimal.

The author directs his attention to a description of the semi-public companies in the Provence-Alpes-Côte d’Azur region, the way in which these were set up and the problems of controlling them. Quoting concrete examples, he describes the use of the semi-public company in the context of the municipality of Marseille and within the context of regional development.
Les sociétés et organismes de droit privé
Authors: Guérin Paul
Published: January 2024

Las sociedades y organismos de derecho privado

Las sociedades de economía mixta juegan un papel particularmente importante en la Región Provenzal, puesto que dependen de ella no menos que treinta y una. Su repartición geográfica testifica la localización de los centros de desarrollo de la región y es así que la mayor parte de las grandes ciudades de la región (Marsella, Aix, Martigues, Carpentras, etc.), disponen cada una de una sociedad de desarrollo. La mayor parte de estas sociedades son de construcción, pero algunas están también investidas del rol de concesionarias de obras o de servicios públicos, o sirven de marco jurídico en las intervenciones de la administración. Pero la creación de sociedades de economía mixta disimula frecuentemente la centralización de las operaciones, porque ellas ceden su propia gestión a las sociedades de obras nacionales. El fenómeno es particularmente evidente cuando se trata de entrar en participación por parte de organismos de financiamiento de estructura muy centralizada, tales como la Caja de Depósitos y Consignaciones.

Las sociedades de derecho común juegan igualmente un papel importante dentro de la gestión administrativa debiéndose mencionar entre ellas la Sociedad de Equipo y de Unificación de Terrenos que ejerce facultades de poder público, ejercidos o vigilados por dos comisarios del gobierno. Estas sociedades se ocupan con frecuencia del desarrollo del turismo y de la instalación de las aglomeraciones, siendo las más características : la Sociedad de Habitación de Alquiler Moderado de Marsella ; la Sociedad de Desarrollo del Departamento de Hautes-Alpes ; y la Sociedad de la Feria de Marsella. El autor procede a la descripción de sus aspectos lo más originales.
L’évolution du droit de la fonction publique hongroise
Authors: Garancsy Gabriella
Published: January 2024

The evolution of the right of the civil service in Hungary

Before 1945, the Right of the Civil Service formed an integral part of the administrative Right and assured the civil servants considerable advantages compared to private employees.

After a period of transition, the Work Code of 1950 standardized the rules applicable to all workers. Since the new Work Code was adopted in 1968, only questions of principles, fundamental rights and obligations of workers were codified in an unique text, the special rules applicable to civil servants being fixed by ministerial decree.

The conditions of entry, the level of qualification of the workers, their obligations as well as the termination of their service are thus the object of specific provisions applicable either as a consideration of the employing administration or as a consideration of the level of their functions.
Contrôle de gestion et organisations publiques
Authors: Gibert Patrick , Bernard François
Published: January 2024

Management control and state organizations

The introduction of an actual System of management control within administrative departments can only be envisaged as an attempt to coordinate the existing dissimilar Systems of control. These can be accused of being too meticulous and at the same time inefficient, in part ad-hoc, uncertain and incomplete and allowing too much scope for subjective judgment, yet they cannot be condemned as wholly inappropriate. The only valid solution for a government service is to institute a 3-dimensional System of overall control. The first of these dimensions is one which matches internal control, i.e. the head of an organization’s control of his organization, against some form of external control. The second is the dimension concerned with aspects of efficiency and pertinence. The third is one which starts with a System to monitor compliance with the organization’s objectives and goes on to measure performance against the objectives and standards set by a higher authority — in this case, the State. A government department’s overall System of control needs to be designed with these three dimensions in mind.