bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring robot machine tool sate via neural ODE and BP-GA
Authors: Zhu Guangyi , Zeng Xi , Gong Zheng , Gao Zhuohan , Ji Renquan , Zeng Yisen , Wang Pei , Lu Congda 
Published: December 2023

Abstract
Tool wear during robotic polishing affects material removal rates and surface roughness, leading to erratic and inconsistent polishing quality. Therefore, a method that can predict the tool state is needed to replace the robot end tool in time. In this paper, based on the cutting-edge neural ordinary differential equations (Neural ODE) and BP neural network optimization based on genetic algorithm (BP-GA), we propose a method to identify the tool state during robotic machining: firstly, a new training method of Neural ODE is proposed to avoid the model from falling into poor stationary points, and then on this basis, Neural ODE is utilized to predict the changes of vibration signals during robot machining; secondly, the predicted vibration signals of the tool are processed using variable modal decomposition method to extract the eigen kurtosis index and envelope entropy of the modal function as the vibration signal eigenvectors, and compare them with the traditional vibration signal eigenvectors. Finally, the predicted tool states were identified using BP-GA, and numerical experiments yielded an F1 score of 91.76% and an accuracy of 96.55% for model identification.
A novel process control method for remote calibration based on improved multiscale permutation entropy and dynamic Hotelling’s T2 control chart
Authors: Wang Quan , Lei Min , Zhang Jun , Wang Huan , Qi Xin 
Published: December 2023

Abstract
Remote calibration (RC) is a new promising technology for electric power instrument calibration. However, due to the inevitable impact of external environmental changes and internal insulation aging during the transportation, installation, and measurement processes involved in RC, the metrological performance of relevant instruments may deteriorate. Therefore, quality control of electric power instruments during RC is of great significance. In this paper, a novel process control method for RC is proposed. First, from the physical characteristic perspective, an improved multiscale permutation entropy (IMPE) algorithm is designed to detect the complexity change point of the instrument system. Second, from the statistical characteristic perspective, a dynamic multivariable Hotelling’s T2 control chart (DMHTCC) is developed to detect the outliers within a time series measurement signal. Finally, a fusion scheme of IMPE and DMHTCC is presented to promote the validity and reliability of process control. The effectiveness of the proposed approach and its superiority over some traditional process control techniques is demonstrated through both simulative and experimental case studies.
Fast nonlinear cross-sparse filtering for rolling bearings compound fault diagnosis
Authors: Yao Shunxiang , Zhang Zongzhen , Han Baokun , Wang Jinrui , Zheng Jiansong 
Published: December 2023

Abstract
The investigation of faults in rotating machinery has been thoroughly examined. Among the different methods under exploration, sparse optimization-based techniques have arisen as a highly desirable approach. However, in real industrial environments, the collected bearing signals often contain a random impact component resulting from changes in working conditions and load mutations. When a machine malfunctions, it can readily induce and generate new faults, resulting in composite faults. To address this challenge, this paper proposes a novel multidimensional blind deconvolution method named fast nonlinear cross-sparse filtering (FNCr-SF). The FNCr-SF aims to separate weak compound faults under random impact interference. Various preprocessing techniques, including Z-score normalization and nonlinear sigmoid activation function, are employed to amplify the faint characteristics of compound faults and minimize the influence of random interference. Furthermore, the FNCr-SF method enables adaptive decomposition of fault components without the need for prior knowledge or pre-processing. This approach effectively reduces random interference and accurately detects compound faults in bearings. Experimental and simulation signals validate the effectiveness of the FNCr-SF method in compound fault detection, demonstrating its high accuracy and robustness.
Back to Michelson interferometer: a precise inspection system for industrial intricate structures defect detection
Authors: Xu Xincai , Gu Diyang , Gao Shaohua , Sun Lei , Lu Xingyu , Wang Kaiwei , Bai Jian 
Published: December 2023

Abstract
Quality inspection of injection molding products with intricate three-dimensional structures and diffuse reflection characteristics is a very important procedure in industrial production. However, the current inspection process for these products still heavily relies on visual inspection, which introduces various issues including low efficiency, and missing or false detection. While previous studies have utilized deep-learning methods in conjunction with specific optical sensors and imaging systems to detect defects, the intricate structure of injection molding products and the small magnitude of defects pose significant challenges in defect detection. To address these challenges, this paper proposes an inspection system based on Michelson interferometer capable of detecting and characterizing defects of injection molding products. Notably, by utilizing the light intensity modulation and an improved image differencing approach, this inspection system is capable of detecting defects with a magnitude as small as 0.1 mm and achieving a remarkable detection accuracy exceeding 93% on self-made datasets without utilizing phase information. The effectiveness of our method is validated by comparison with mainstream deep-learning-based defect detection methods and visual inspection methods.
A fault diagnosis method based on feature-level fusion of multi-sensor information for rotating machinery
Authors: Gao Tianyu , Yang Jingli , Zhang Baoqin , Li Yunlu , Zhang Huiyuan 
Published: December 2023

Abstract
Traditionally, most fault diagnosis work on rotating machinery is carried out on single sensor datasets. However, the single feature source may suffer from missing or inaccurate features, which is especially sluggish for fault diagnosis tasks under noise interference. Feature-level fusion of multi-sensor information can obtain more comprehensive and abundant feature information, while improving the feature discrimination. Therefore, through feature-level fusion of multi-sensor information, a parallel multi-scale attentional convolutional neural network (PMSACNN) is proposed in this paper to achieve rotating machinery fault diagnosis. A dilated wide convolutional layer is designed to extract the short-time features of signals with noise by performing sparse sampling on them. The multi-scale structure is constructed to capture the diversity feature information of signals, and the feature-level stitching of multi-sensor information is realized by the parallel input mechanism. Feature fusion is achieved by adaptively correcting the importance of different channel features by using channel attention. The global averaging pooling operation is introduced to reduce the number of parameters and improve the efficiency of the model operation. The effectiveness of PMSACNN is verified by using the bearing dataset acquired from the mechanical comprehensive diagnosis simulation platform. The experimental results indicate that the proposed method outperforms the existing methods of this field in terms of fault diagnosis accuracy and noise immunity, which can improve the reliability and safety of rotating machinery.
Study on the regional ASF prediction method based on the ordinary kriging interpolation
Authors: Di Jianchen , Xu Jiangning , Fu Jun , Li Bao , Wu Miao 
Published: December 2023

Abstract
The eLoran system functions as a robust backup to the Global Navigation Satellite System (GNSS), providing substantial signal power, robust anti-jamming capabilities, and an easily maintainable ground system. Nonetheless, the propagation time delay of the system, primarily driven by the Additional Secondary Phase Factor (ASF), significantly influences the positioning accuracy. Compensating for ASF can effectively enhance the positioning performance. Traditional propagation delay theories frequently yield substantial discrepancies between the predicted and measured values in regions characterized by extended propagation distances and varying topographic features. To address this issue, we conducted ASF measurements within a selected test area using a limited number of measurement points. We employed the ordinary Kriging interpolation method to predict ASF values across the entire test area, and used cross-validation to validate our predictions. The results confirmed the accuracy and effectiveness of the Kriging interpolation algorithm in predicting ASF values within specific regions. The cross-validation demonstrated that the errors remained within acceptable ranges. Furthermore, we applied Ordinary Kriging, Inverse Distance Weighting, and Radial Basis Function Interpolation methods to evaluate the positioning accuracy of the test area before and after ASF correction. Compared to other methods, using the Ordinary Kriging interpolation algorithm for predicting ASF values resulted in a corrected positioning accuracy of up to 68.8 m at various test locations. This approach effectively resolves the challenge of low accuracy in theoretical calculations in complex environments. By utilizing ordinary Kriging interpolation, we required measurements of only a few ASF values within a specific region to create an ASF correction map, addressing the challenges related to inaccurate theoretical calculations in complex pathways and avoiding time-consuming and labor-intensive large-scale measurements. The results of this study offer valuable theoretical support for improving the accuracy of land-based navigation systems.
Dry sand abrasion characteristics of WC-10Ni+NiCrBSi coatings
Authors: Shi Jintian , Zhu Jiawei , Xu Xiangping , Liu Chi , Liu Kai , Qiao Yanxin , Zou Jiasheng 
Published: December 2023

Abstract
A WC-10Ni/NiCrBSi coating was prepared and applied to the surface of Q235 steel through vacuum brazing. Using a self-developed dry sand abrasion test machine, the effects of the abrasive sand’s type, load, and sliding speed on the dry sand abrasion property of the coating were analysed. The wear mechanism of dry sand abrasion was also investigated. The results indicated that the coating cross-section comprised three layers: the substrate, the interface layer, and the surface layer. The hard layer served as the main distribution area of WC hard particles, which directly determined the hardness and wear resistance of the coating. WC particles, fortified by a γ-Ni solid solution, enhanced the wear resistance and hardness of the coating. In the friction and wear test, when ceramic abrasives were employed, the coating sample exhibited a loss of only 23 mg, constituting only 7.9% of that observed with quartz sand abrasives. Under low loading conditions, the wear mass loss exhibited a linear relationship with the applied load. During these low-load scenarios, the abrasive particles operated through a rolling motion, thereby entailing an abrasive wear mechanism. Conversely, when the load exceeded 0.05 MPa, the primary mode of abrasive particle motion transitioned into sliding with burial, resulting in a combination of fatigue wear and abrasive wear mechanisms. Therefore, the dry sand abrasion mechanism inherent to composite coatings can be attributed to the protective shielding role played by WC particles on the substrate. This shielding function effectively mitigates and counteracts the abrasive cutting effects induced by abrasive particles.
A semi-empirical formula for the dependence of upper critical field with component and strain in Nb3Sn
Authors: Xu Binhong , Li Yingxu , Salmi Tiina 
Published: December 2023

Abstract
We include the effects of Sn content

β

in the scaling law to generalize the upper critical field

B

c
2

(
T
,
ε
)

function of temperature and strain in Nb3Sn. The basis for this generalization comes from a theory developed by the same author [Scientific Reports 7, 1133 (2017)]. The important assumption in the current work is that, in determining the upper critical field

B

c
2

,

the contributions of strain, temperature and Sn content are independent of each other. It is followed that we write down a semi-empirical expression

B

c
2

(
T
,
ε
,
β
)

=

B

c
2

(

T

0

,

ε

0

,
β
)

s

(
ε
)

(
1
−

t

1.52

)

where the strain function

s

(
ε
)

and

t
≡
T
/

T

c

(
ε
)

are affected only by strain and temperature, respectively, and the variation of tin content

β

enters in the function

B

c
2

through

B

c
2

(

T

0

,

ε

0

,
β
)

.

This separable form of

B

c
2

(
T
,
ε
,
β
)

allows one to incorporate Sn content

β

in the scaling law in a natural way, while this variable is not considered by traditional scaling laws. In addition to this advance, one can see a more flexible function with triple variables which could be an effective tool to fit or predict experiments. As the last but most important outcome, this semi-empirical function instructs one how to understand the role of component content played in scaling behaviors of Nb3Sn, so as to reduce the off-stoichiometric composition inducing discrepancy between the results by scaling laws and experiments.
Statistical similarity matching and filtering for clinical image retrieval by machine learning approach
Authors: Alfwzan Wafa F , Alballa Tmader , Al-Dayel Ibrahim A , Selim Mahmoud M 
Published: December 2023

Abstract
Clinical image retrieval plays a pivotal role in modern healthcare for diagnostics and research, but prior research has grappled with the challenge of achieving high accuracy due to limited filtering techniques. The proposed method includes statistical distance measurements for similarity comparison and a machine learning technique for image filtering. Throughout this framework, the search area for similarity matching is reduced by first filtering away irrelevant images using the probabilistic outcomes of the Support Vector Machine (SVM) classification as class predictions of search and database images. Resizing is done as part of the preprocessing. Then, using Principal Component Analysis (PCA), the preprocessed data’s textural features, visual characteristics, and low-level features are extracted. The study also suggested an adaptive similarity matching method centered on a linear integration of feature-level similarities on the individual-level level. The precision and ranking order details of the most appropriate images retrieved and predicted by SVMs are considered when calculating the feature weights. The system continually alters weights for every distinctive search to generate beneficial outcomes. The supervised and unsupervised learning strategies are studied to link low-level global image features in the generated PCA-based Eigen Space using their high-level semantic and visual classifications to reduce the semantic gap and enhance retrieval effectiveness. The ground-truth database used in experiments has 1594 unique medical images with 3 different databases. Our method significantly improves the precision and recall rates in image retrieval tasks by combining sophisticated feature extraction, data-driven algorithms, and deep learning models. Research obtained an impressive accuracy of 0.99, demonstrating the effectiveness of our approach. This novel methodology addresses the limitations of prior research and provides a robust and reliable solution for clinicians and researchers in the medical field seeking to access and analyze relevant clinical images.
High performance metal-semiconductor-metal ultraviolet photodetector based on mixed-dimensional TiO2/CsPbBr3 heterostructures
Authors: Zhang Tao , Cai Siyu , Liang Nina , Gao Yalei , Li Yuanpeng , Liu Fuchi , long Lizhen , Liu Jun 
Published: December 2023

Abstract
Zero-dimensional (0D) and one-dimensional (1D) mixed heterostructure semiconductors can bring superior electrical and optoelectronic performances due to the synergistic advantages of different dimensionalities. Here, a metal-semiconductor–metal (MSM) ultraviolet (UV) photodetector based on 1D-0D TiO2/CsPbBr3 heterostructure semiconductor is constructed, which exhibits excellent photodetection performance. A back-to-back Schottky contact is formed in the MSM (Au/TiO2/Au) structure due to the large band-energy bending resulted from the abundant surface-states at 1D-TiO2 surface. Under an applied voltage, a small saturation current flows through the device. Benefiting from the decoration of CsPbBr3 QDs, the dark current of MSM photodetectors can be further suppressed, and producing the improved on/off ratio (I
light/I
dark), photoresponsivity (R

λ
), and detectivity (D*). PL properties study suggested that an energy transfer is occurred between the 0D-CsPbBr3 and 1D-TiO2. The TiO2/CsPbBr3 heterojunctions are beneficial for photo-induced charge transfer in hetero-interface because of the type-II energy-band alignment, but not non-radiative energy transfer from 0D-CsPbBr3 to 1D-TiO2. On the whole, this study depicts a fascinating coupling architecture of mixed-dimensional materials toward implementing low-cost and high-performance optoelectronic devices.
Analytical estimations of the side lobe characteristics for the pattern factor of the continuous uniform line source in electromagnetics
Authors: Xu Xiaofei 
Published: December 2023

Abstract
This contribution proposes an interesting analytical method to estimate the side lobe characteristics for the pattern factor of the continuous uniform line source in electromagnetics. The new solutions are observed more precise than the classical analytical estimations. Detailed formulas and results are given in explicit validation of the methodology. In particular, to estimate the first side lobe direction, the error between the new method and the truly accurate one is only −0.08%, whereas for the classical analytical study is about 4.87%.
Exfoliation of graphite to turbostratic graphene
Authors: Kumar K Vijay , Islam Aminul , Kiran P Sai , Pandit Niranjan , Kumar Rahul , Indupuri Satish , Keshri Anup Kumar 
Published: December 2023

Abstract
Here, we exfoliated high-quality turbostratic graphene with a clean interface at a high production rate (10 g h−1) directly from graphite using an industrial-friendly technique i.e. plasma spraying, catching note of its growing global interest. The reduction of the (002) x-ray diffraction peak and the transparent scanning electron microscope image are used to characterize the exfoliation. The thickness of exfoliated graphene layers is measured using an atomic force microscope. Turbostratic nature (twist) in graphene is identified based on the appearance of three Raman combination bands (TS1, TS2, and TS3) between 1800 cm−1 and 2300 cm−1. The twist between the layers is precisely measured using selected area electron diffraction (SAED), and the turbostratic nature is confirmed by observing a moiré pattern utilizing a high-resolution transmission electron microscope. The produced turbostratic graphene exhibited large variability in twist angles (2°–30°) with a visible moiré pattern. The high crystalline quality and clean interface between single layers of graphene were confirmed by the moiré pattern and SAED. Later, we demonstrated the mechanism underlying the twist in our exfoliated graphene, which could open the way for the production of high-quality turbostratic graphene with clean interfaces.
Use of the Afirma Xpression Atlas for cytologically indeterminate, Afirma Genomic Sequencing Classifier suspicious thyroid nodules: Clinicopathologic analysis with postoperative molecular testing
Authors: Munoz-Zuluaga Carlos A , Heymann Jonas J , Solomon James P , Patel Ami , Siddiqui Momin T , Scognamiglio Theresa , Gokozan Hamza N 
Published: December 2023

Abstract

Objectives
Afirma has recently introduced its Xpression Atlas (XA) as an adjunct to its Genomic Sequencing Classifier (GSC) for risk stratification of cytologically indeterminate thyroid nodules. We evaluated the performance of Afirma XA and associated pathologic findings for Afirma GSC suspicious nodules.

Methods
Intradepartmental records of thyroid fine-needle aspirations (FNAs) from January 2021 to December 2022 were identified and reviewed for patient and nodule characteristics, FNA findings, molecular test results, and final surgical pathology, if available.

Results
Material for Afirma GSC testing was collected in 624 thyroid FNAs, and 148 (24%) were classified as cytologically indeterminate. Afirma GSC testing was successful in 132 (89%) of those cases, of which 35 (27%) were Afirma GSC suspicious. Afirma XA testing was positive in 11 cases (11/35 [31%]). Eight (73%) patients underwent surgery that revealed 7 patients with papillary thyroid carcinoma and 1 patient with noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) (risk of malignancy: 100% [8/8]). Among the 24 patients with negative Afirma XA results, 19 (79%) underwent surgery, revealing 5 patients with malignancy and 3 patients with NIFTP (risk of malignancy: 42% [8/19]). Overall, the risk of malignancy for Afirma GSC suspicious nodules was 59% (16/27).

Conclusions
Afirma XA improved risk stratification of thyroid disease with a high risk of malignancy in Afirma GSC suspicious nodules. A negative Afirma XA result, however, should not be used as a rule-out test.
Effects of Midcheek Lift According to Dissection Plane and Range: An Anatomical Study
Authors: Kyung Hyunwoo , Park Yunsung , Oh Sang-Ha , Kim Dong Woon , Seo Young-Joon , Song Seung Han 
Published: December 2023

Abstract

Background
Midcheek lift has been performed for cosmetic or reconstructive surgery of the lower eyelid. For midcheek lift through the subciliary incision, preperiosteal and subperiosteal dissections are the most often implemented, with good clinical outcomes. However, a comparative assessment of the effects of these 2 methods had not been conducted.

Objectives
In this study we compared the effects of midcheek lift according to preperiosteal or subperiosteal plane and range of midfacial dissection.

Methods
Forty hemifaces of 20 fresh cadavers were dissected. One side of the hemiface underwent preperiosteal dissection, and the other side underwent subperiosteal dissection. After dissections of 5, 10, 15, 20, and 30 mm and all of the midcheek area from the inferior orbital rim, the length of the elevated lid-cheek junction was measured by placing upward traction on the lateral portion of the lower lid.

Results
In both methods, the length of the midcheek lift increased as the dissection progressed, and the length of the lift on the lateral side was greater than that on the medial side. The length of the pulled skin in the preperiosteal group was the greatest in most cases. However, in the full dissection cases, the midcheek lift length was not statistically different between the 2 surgical methods, especially on the lateral side.

Conclusions
Flap elevation in lower blepharoplasty surgery can be predicted based on the surgical method and dissection range. Implementing a surgical plan that takes this into account can enhance both reconstruction and aesthetic surgery outcomes in the midcheek area.