bluuebunny/crossref_metadata_2025_split huggingface dataset:
Verb Tense Production in People With Nonfluent Aphasia Across Different Discourse Elicitation Tasks
Authors: Park Hyejin , Obermeyer Jessica , Paek Eun Jin , Zurbrugg Madeline 
Published: February 2024

Purpose:
Verb tense production is known to be impaired in people with nonfluent aphasia. Selective past tense impairment in this population has been reported, but results are inconsistent and lacking at the discourse level. In addition, language production can be affected by discourse elicitation tasks depending on the cognitive linguistic demands and instructions unique to each task. There is limited evidence regarding whether verb tense production in people with nonfluent aphasia is impacted by discourse task demands. Understanding this potential impact is important for clinicians and researchers who are interested in assessing and then identifying effective clinical goals for this population. Therefore, this study aimed to investigate the trends of verb tense production across various discourse elicitation tasks in people with nonfluent aphasia compared to people without aphasia.

Method:
Language samples for 23 people with nonfluent aphasia and 27 people without aphasia were obtained for six discourse tasks from the AphasiaBank database. We calculated ratios of past tense, present tense, future tense, imperative, and unknown verb types to compare which tense was used most frequently within and across the tasks and groups.

Results and Conclusions:
Our findings revealed evidence of verb tense production deficits and a selective past tense impairment in people with nonfluent aphasia. Discourse task effects were shown for people without aphasia but were scarce in people with nonfluent aphasia. This finding could be explained by an overall reduction of verb production and overreliance on present tense production in nonfluent aphasia. These results suggest the potential methodological implications of using different discourse tasks to evaluate verb tense production in people with nonfluent aphasia. Future studies need to evaluate discourse task effects on other aspects of verb production (e.g., moods) and specific task factors (e.g., presence or absence of visual stimulus).

Supplemental Material:

https://doi.org/10.23641/asha.25146242
Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things
Authors: Dhasaratha Chandramohan , Hasan Mohammad Kamrul , Islam Shayla , Khapre Shailesh , Abdullah Salwani , Ghazal Taher M. , Alzahrani Ahmed Ibrahim , Alalwan Nasser , Vo Nguyen , Akhtaruzzaman Md 
Published: February 2024

AbstractInternet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help healthcare providers decide about post‐COVID‐19 care and follow‐up where the data privacy is another severe concern. The authors investigate the applicability of a distributed reinforcement learning approach in a Federated Learning (FL) multi‐disciplinary reinforcement system and explores the potential benefits of incorporating Blockchain Technology (BT) in the distributed system. Intermediate dependency features and transactions are avoided by applying Blockchain‐enabled reinforcement FL for the post‐COVID‐19 patient data of IoMT applications. The proposed approach helps to improvise clinical monitoring and ensure secure communication and data privacy in a decentralised manner. The main objective is to improve the efficiency and scalability of the reinforcement FL process in a distributed environment while ensuring data privacy and security through BT for IoMT applications. Results show that proposed approach achieve comparatively high reliability and outperforms the existing approaches.
Data transmission path planning method for wireless sensor network in grounding grid area based on MM‐DPS hybrid algorithm
Authors: Xiao Xianghui , Huang Longsheng , Zhang Zhenshan , Huang Mingxian , Guan Luchang , Song Yunhao 
Published: February 2024

AbstractAt present, in order to conduct non‐destructive testing on the grounding grid of substations under the condition of continuous power supply and no excavation, researchers have applied wireless technology based on electrochemical methods to remotely monitor the corrosion state of grounding conductors online. Nevertheless, wireless signals are affected by the environment when they are transmitted underground. In the field of grounding gird wireless monitoring, how to plan the information transmission path of wireless sensor network (WSN) with high accuracy of data transfer and low energy consumption earns growing research attention. To address the problem of WSN path planning in grounding grid area, a path planning method for WSN based on the hybrid algorithm of map‐matching algorithm and double‐pole search algorithm (MM‐DPS) is proposed in this paper. The map‐matching algorithm is employed to calculate the optimal sampling node number of the data transmission path. On the basis of the optimal sampling node number, the double‐pole search algorithm is employed in seeking out each sensor node of the path, and two groups of path plans are obtained. In the simulation experiment, compared with the A‐star algorithm, the MM‐DPS algorithm shortens the data transmission path length by about 39% and reduces the energy consumption by about 57%. The research work brings a method to alleviate the problem of data transmission underground of WSN in grounding grid area. The method not only ensures the accuracy of data transmission, but also shorts the transmission distance and reduces energy consumption.
System architecture for small‐scale personalized production lines based on industrial Internet
Authors: Li Qiang , Liu Jiaming 
Published: February 2024

AbstractThe rapid development of industrial Internet has resulted in significant changes in industrial manufacturing system architecture. In this study, a system architecture suitable for small‐scale personalized production lines is proposed. The core of this architecture is a three‐layer structure comprising the Internet layer, data layer, and field control layer. The system facilitates the transmission of user‐specific product demands from the Internet to the production line, where the production equipment achieves personalized production through motion control. This system architecture for production lines integrates industrial Internet and smart manufacturing technologies, reducing the complexity of the enterprise system architecture and enhancing the flexibility of the system compared to large‐scale personalized production systems. The effectiveness of this system architecture was validated using a flexible yogurt filling production line and lays a foundation for the transformation of industrial manufacturing from the tradition system to a personalized production.
Variational Bayesian Gaussian mixture model for off‐grid DOA estimation
Authors: Guan Shanwen , Li Ji , Luo Xiaonan 
Published: February 2024

AbstractWireless signals are commonly subject to diverse and complex noise interference. The typical assumption of Gaussian white noise often oversimplifies the noise, resulting in reduced accuracy in estimating the direction of arrival (DOA), especially in complex scenarios. To tackle this issue, this paper introduces a new Bayesian model for off‐grid DOA estimation. This model utilizes Gaussian mixture model (GMM)‐based Dirichlet processes (DP) to characterize noise, allowing adaptive adjustments in the number of Gaussian mixture models. Leveraging the factor graph representation of the Bayesian model, a low‐complexity mixed messaging passing algorithm, employing generalized approximate message passing (GAMP) and mean field (MF), is proposed. Simulation results validate the efficacy of the proposed algorithm.
Modelling method for time‐varying suspension system of axial split‐phase bearingless switched reluctance motor
Authors: Wen Fuguang , Xie Kai , Zou Yu , Yuan Ye 
Published: February 2024

AbstractThe rotor of the axial split‐phase bearingless switched reluctance motor (ASPBSRM) is structured with convex poles. The magnetic flux between the stator and the rotor varies with the rotor position, resulting in time‐dependent displacement stiffness and current stiffness coefficients of the suspension force. This scenario leads to a time‐varying characteristic of the suspension system. This study analyzed the electromagnetic characteristics of the suspension force in the ASPBSRM to characterize the time‐varying suspension system accurately. The study elucidated the hinge relationship between the magnetic flux in the suspension system and the rotor position. Moreover, a mathematical model for the suspension force considering the magnetic flux multitooth hinge was constructed by leveraging the advantages of the Maxwell stress method for the localized modelling and adopting the concept of the main edge magnetic path parallel analysis. Finally, the effectiveness of the model was verified through finite element analysis.
Building the bioeconomy: A targeted assessment approach to identifying biobased technologies, challenges and opportunities
Authors: Holland Claire , Shapira Philip 
Published: February 2024

AbstractThe authors explore opportunities, challenges, and strategies to translate and responsibly scale innovative biobased technologies to build more sustainable bioeconomies. The pandemic and other recent disruptions increased exposure to issues of resilience and regional imbalance, highlighting a need for production and consumption regimes centred more on local biobased resources and dispersed production. The authors review potential biobased technology strategies and identify promising and feasible options for the United Kingdom. Initial landscape and bibliometric analysis identified 50 potential existing and emerging biobased technologies, which were assessed for their ability to fulfil requirements related to biobased production, national applicability, and economic‐, societal‐, and environmental‐benefits, leading to identification of 18 promising biobased production technologies. Further analysis and focus‐group discussion with industrial, governmental, academic, agricultural, and social stakeholders, identified three technology clusters for targeted assessment, drawing on cellulose‐, lignin‐, and seaweed feedstocks. Case studies were developed for each cluster, addressing conversations around sustainable management, use of biomass feedstocks, and associated environmental‐, social‐, and economic challenges. Cases are presented with discussion of insights and implications for policy. The approach presented is put forward as a scalable assessment method that can be useful in prompting, informing, and advancing discussion and deliberation on opportunities and challenges for biobased transformations.
Investigating the characteristics of internal discharge shock waves in gas‐insulated switchgear under varied gap configurations
Authors: Jia Chenglong , Haochu Peng , Zhao Wenbin , Tang Zhong 
Published: February 2024

AbstractGas‐insulated switchgears (GIS) are crucial components of high‐voltage power transmission and distribution systems. Internal discharges within GIS have garnered significant attention in the field of power engineering. This study investigates the characteristics of internal discharge shock waves in GIS under an air pressure of 0.3 MPa and three different discharge gap conditions: 1, 1.5, and 2 mm. High‐speed shadowing techniques are used to analyse the propagation speed, morphology, and post‐wave parameters. The study findings reveal that although the characteristics of internal discharge shock waves in GIS noticeably change with the gap size, they also exhibit a consistent trend: as the gap size increases, the initial shock wave accelerates, intensifying the discharge. Simultaneously, the rate of attenuation rises, with the shock wave becoming weaker after ≈30 µs. Furthermore, the post‐wave parameters follow a similar pattern, with an increase in gap size leading to higher parameter values but also a faster decay rate. The parameters decay more rapidly between 10 and 20 µs, slow down between 20 and 30 µs, and ultimately stabilize after around 30 µs. The results of this study hold significant theoretical and practical implications for the monitoring, diagnosis, and prevention of internal discharges in GIS.
Pseudo‐measurement‐based state estimation for railway power supply systems with renewable energy resources
Authors: Pan Zheng , Che Liang , Tu Chunming 
Published: February 2024

AbstractState estimation is critical for railway power supply systems (RPSSs). Pseudo‐measurement is commonly used in state estimation. However, the fluctuations of renewable generations and railway traction loads in RPSS may introduce data noise, which will jeopardize the accuracy of the generated pseudo‐measurements and thus impact the state estimation. Additionally, when learning the historical measurement data sequences, the traditional pseudo‐measurement model is likely to have overfitting, which will further impact the accuracy of pseudo‐measurements, thereby affecting the accuracy of state estimation. To address these issues, this paper proposes a high‐accuracy pseudo‐measurement‐based state estimation approach for RPSSs. Firstly, a denoising autoencoder‐based method is used to mitigate the impact of data noise on the accuracy of pseudo measurements, and a gated recurrent unit‐based method is used to adaptively learn the historical measurement data sequence, thereby improving the accuracy of pseudo measurements. Next, the pseudo‐measurement weights are obtained by generating pseudo‐measurement variances using the Gaussian mixture model. Finally, the pseudo measurements and real‐time measurements are integrated by weighted least squares to realize the state estimation of RPSS. The effectiveness and accuracy of the proposed method are verified by simulation on a modified IEEE 33‐node system which includes a railway traction substation and renewable generations.
Facial and mandibular landmark tracking with habitual head posture estimation using linear and fiducial markers
Authors: Saad Farhan Hasin , Farook Taseef Hasan , Ahmed Saif , Zhao Yang , Liao Zhibin , Verjans Johan W. , Dudley James 
Published: February 2024

AbstractThis study compared the accuracy of facial landmark measurements using deep learning‐based fiducial marker (FM) and arbitrary width reference (AWR) approaches. It quantitatively analysed mandibular hard and soft tissue lateral excursions and head tilting from consumer camera footage of 37 participants. A custom deep learning system recognised facial landmarks for measuring head tilt and mandibular lateral excursions. Circular fiducial markers (FM) and inter‐zygion measurements (AWR) were validated against physical measurements using electrognathography and electronic rulers. Results showed notable differences in lower and mid‐face estimations for both FM and AWR compared to physical measurements. The study also demonstrated the comparability of both approaches in assessing lateral movement, though fiducial markers exhibited variability in mid‐face and lower face parameter assessments. Regardless of the technique applied, hard tissue movement was typically seen to be 30% less than soft tissue among the participants. Additionally, a significant number of participants consistently displayed a 5 to 10° head tilt.
Skeleton extraction of hard‐pen regular script based on stroke characterization and ambiguous zone detection
Authors: Xu Zhanyang , Qin Feiyang , Xiong Ningyang , Shi Hongyan , Zhang Jiarui , Lin Wei 
Published: February 2024

AbstractThe Intelligent Evaluation System for Calligraphy Characters (IESCC) is used for teaching calligraphy, and users can learn calligraphy through the modifications given by the system. Chinese character skeleton extraction is an important step in the intelligent evaluation algorithm of calligraphic characters. The skeletons of Chinese characters extracted by traditional refinement algorithms are prone to redundant branches and deformed skeletons, which can lead to skeleton extraction results that do not conform to the topology of the original character. In this study, the focus lies on hard‐pen regular script, and skeleton repair and extraction are performed for these characters. According to the writing characteristics of regular script, the redundant burs are removed and the deformation zone of the thinned skeleton is detected, and then the idea of first splitting is used, then restructuring, to propose a skeleton extraction algorithm based on stroke characterization and ambiguous zone detection for hard‐pen regular script, referred to as SCAD. First, a thinning algorithm is used to extract the skeleton of Chinese characters and remove redundant pixels. By analyzing the stroke characteristics of regular script, the burrs are classified and different conditions are set to detect and remove the burrs. Then the ambiguous zones are detected according to the different kinds of junction points. Then, curvature, stroke width and direction deviation are used to analyze the continuity of stroke segments, and the decision function is used to classify the stroke segments. Finally, the stroke segments with optimal pairings were compensated by interpolation according to the direction trend. This concludes the skeleton extraction. Skeleton extraction is performed on 1000 sample characters, and the SCAD algorithm can extract the skeleton of Chinese characters with an accuracy of up to 98.37%. It is proved that the SCAD method proposed here is a practical and effective method to extract the skeleton of hard‐pen regular script.
Improved single‐layer powder core inductor design procedure for DC‐DC converters
Authors: Kunstbergs Noass , Hinz Hartmut , Roll Dennis , Schofield Nigel 
Published: February 2024

AbstractOne of the early design decisions for DC‐DC converters is the choice of an appropriate magnetic core material. Powder cores in particular are suitable due to their saturation flux density of up to 1.5 T. However, high DC currents constitutes a significant problem since the winding cross‐section rises with the current, which consequently increases AC losses due to skin effects. Another challenge is the reduction of winding layers to decrease proximity losses. This paper presents an improved single‐layer winding design procedure for DC‐DC converter powder cores. The procedure determines the optimum number of parallel cores and stacks. This way, the procedure enables a predefined maximum wire cross‐section for copper loss optimisation and single‐layer winding. The introduced approach defines the optimum switching frequency as a trade‐off between core loss and core volume. Finally, experimental tests with two setups validate 27 kW DC‐DC converters and hence the design procedure using Si‐IGBTs and SiC‐MOSFETs. The results demonstrate that SiC‐MOSFETs reduce core volume by a factor of 3 compared to Si‐IGBTs. Further, the SiC setup reaches high efficiencies of up to 98.53% compared to 98.17% for the Si‐based converter.
Improved design of passive damping for single phase grid‐connected LCL filtered inverter considering impedance stability
Authors: Ali Ramy , Heydari‐doostabad Hamed , Sajedi Shahab , O'Donnell Terence 
Published: February 2024

AbstractGrid‐connected inverters with an inductor–capacitor–inductor (LCL) filter usually require the implementation of damping in the filter to suppress the resonance associated with the filter and hence ensure internal stability. The value for the damping resistor is commonly chosen as one‐third of the capacitive reactance at the resonance frequency of the LCL filter. However, this commonly‐used principle does not take into account the external stability of the inverter, i.e. the potential for an interaction between the inverter output impedance and the grid impedance. This work discusses a new design for the damping resistor to assure the external stability of the voltage source inverter as well as its internal stability. The analysis shows that the proposed design can ensure the external stability of the voltage source inverter with different grid impedances as well as robustness against the variations of the filter parameters while maintaining low power losses and an acceptable attenuation rate for high‐frequency harmonics. To validate the theoretical analysis, a 1 kW, 110 V laboratory prototype is implemented. The obtained results confirm the applicability of the proposed design approach.
Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration
Authors: Abbas Ghulam , Wu Zhi , Ali Aamir 
Published: February 2024

AbstractWhile extensive research has focused on enhancing distribution networks through either maximizing Distributed Generation (DG) integration or network reconfiguration at specific times, there is a need for further investigation into concurrently optimal network reconfiguration and DG allocation. To reduce the cost of energy delivered, the cost of energy loss, and voltage deviation, this study gives a dynamic multi‐objective network reconfiguration together with siting and sizing of dispatchable and non‐dispatchable DGs. The widely used IEEE 33‐bus and a large‐scale 118‐bus radial test system are employed while considering the time sequence fluctuations in sunlight irradiation and load. To address the pointed‐out challenge of multiperiod optimal DG allocation and reconfiguration while simultaneously decreasing the cost of energy supplied, the cost of energy lost, and the voltage deviation, a novel Multi‐objective Bidirectional co‐evolutionary algorithm (BiCo) is implemented. For better exploration and exploitation, the proposed algorithm integrating the constraint domination principle evolves the population from the feasible and infeasible search space with the help of a novel angle‐based density section. Simulation results demonstrate that the proposed approach outperforms previously published Multi‐objective Evolutionary Algorithms (MOEAs) by discovering a vast collection of uniformly spaced non‐dominated solutions in a single simulation run. Further, a fuzzy set theory is applied to find the best compromise solution among obtained final non‐dominated solutions. The results establish that the Pareto solutions significantly improved the system's voltage profile, with savings of over 22% compared to the baseline case and an exceptional improvement of over 80% in voltage deviation and power loss.