bluuebunny/crossref_metadata_2025_split huggingface dataset:
The choice of degrees of freedom of automatic refueling manipulator
Authors: Tao Chen , Fang Xie , Li Mahong 
Published: March 2023

Abstract
Traditional artificial gas station come on all the required 5 to 6 minutes, peak even 10 minutes or so, along with our country automobile holdings continued to increase, how to improve fuel efficiency become an important problem of gas station, according to the above problem, non-inductive refueling “AI” is put forward to cooperate with mechanical arm instead of artificial gas, this scheme can make the refueling time reduced to 3 minutes, Greatly improve refueling efficiency, and reduce labor costs. The manipulator adopts a tandem joint robot with a 2-DOF BB wrist at the wrist and a fixed base, which is driven by the servo motor of each joint as a whole. The end-effector is equipped with a cap opening device, a clamping device and an oil feeding device to open the oil tank cover, unscrew the seal plug and oil feeding tasks respectively.
Failure Analysis and Improvement of Check Valve Reverse Cut-off Seal
Authors: Li Lei-lei , Zhao Jian , Gong Sheng-bo , Liu Bao-rong , Zhang Hao , Zhou Xiao-lei , Miao Li-lei , Li Peng 
Published: March 2023

Abstract
Given the failure of reverse cut-off seal performance in the test process of the check valve, the fault location and mechanism analysis were carried out, and the improvement measures were proposed and verified by the test. It is analyzed that the main reason for the failure is the unreasonable design of the moving pair and the welding position of the check valve, which makes the sealing pair cannot fit effectively after the welding of the check valve, leading to the failure of the reverse cut-off seal. By controlling the ratio of the length of the guide surface to the diameter of the guide surface to 1.25, and controlling the distance between the welding position and the sealing pair to 10mm, the failure problem of the reverse cut-off seal of the check valve caused by the unreasonable design of the moving pair and the weld position is successfully solved. The effectiveness of the improved scheme of the check valve is verified by the test.
Research on Acceleration Segmented Compensation Strategy for Backlash of CNC Machine Tools
Authors: Zhang Qiujie , Shen Huiming , Qin Xiufeng , Lü Tianguo 
Published: March 2023

Abstract
For the problem of backlash in the semi-closed-loop linear feed servo system of CNC machine tools, which seriously affects the accuracy of machine tools, an acceleration segmentation backlash compensation strategy is proposed. In the reverse motion of the servo motor, the servo motor is controlled to compensate for the backlash error during a period of accelerated motion and a period of decelerated motion. Based on the established backlash transmission model, the parameters of the compensated motion process are calculated. In order to ensure accurate and quick compensation of the gap compensation value for the transmission gap, the backpropagation method is used to backpropagate the acceleration calculation based on whether the acceleration process time is an integer multiple of the servo interpolation period. Finally, the feasibility of the method is verified through experiments, and the results show that the method improves the positioning accuracy of machine tools.
Single Image Dehazing Based on Contrastive Learning and Transformer
Authors: Zhao Yang , Wang Yigang 
Published: March 2023

Abstract
For the single image dehazing problem, an end-to-end multi-stage dehazing algorithm is designed. The algorithm contains two distinct parts to extract features. For shallow features, texture-level information is mined by stacking pixel and channel attention mechanisms. The proposed method uses multi-head self-attention (MHSA) to capture high-level features. MHSA improves dehazing performance by mining the dependencies of a wide range of abstract information. The superiority of the transformer architecture is extended with cascaded attention mechanisms and convolutions to improve feature extraction capabilities. Multilayer perceptron (MLP) is used in the decoding stage to equalize the context information. Furthermore, a contrastive loss function that introduces multiple negative samples and correction terms is proposed. The correction term is generated according to the difference between the precise and blurred images, which can enhance the training effect when dealing with different concentrations of dehaze. The training result of this loss function assists the model in approximating clear images and staying away from blurry images. According to the experimental results compared with other methods under the same conditions, the proposed method achieves good results in both subjective visual effects and objective evaluation indicators. The proposed contrast loss function also improves the dehazing performance of the algorithm.
Research on Classification and Recognition of Industrial Stainless Steel Welded Pipe Defects Based on Convolution Neural Network
Authors: Wang Zongren , Zhu Liujuan , Hou Huaishu , Liu Luyu 
Published: March 2023

Abstract
For the classification and identification of industrial stainless steel welded pipe defects, a combined method of STFT and CNN based on vortex test is proposed. First, the collected original eddy current signal is STFT transformed to obtain a two-dimensional time-frequency map. Then, the two-dimensional time-frequency map was input into the two neural networks VGG-16 and GoogLeNet for model training, selecting a more accurate network model under the condition of the same learning rate. The trained network model is then classified using different learning rates. The results show that with the learning rate of 0.0001, the VGG-16 training model is better than the GoogLeNet training model, which has a certain reference significance for the classification and identification of defects in industrial stainless steel welded pipes.
Research strategy of fault diagnosis considering WOA-VMD algorithm
Authors: Huang Dayang 
Published: March 2023

Abstract
To address the problem of low accuracy of fault information extracted from motor-bearing vibration signals, a feature extraction method based on Whale Optimization Algorithm (WOA)-Variable Modal Decomposition (VMD) energy entropy is proposed, and a modified WOA-Support Vector Machine (SVM) is used for fault diagnosis. Firstly, the optimal number of modes K and penalty parameters α for the variable modal decomposition are found by WOA. WOA is used to find Then a number of modal components are obtained based on the VMD processing signal, and the energy entropy is further extracted as the feature vector after screening. Finally, to address the shortcomings of the WOA population iteration mechanism, a random variation strategy is introduced to improve the WOA-SVM for fault diagnosis of bearing signal. The results show that the WOA-VMD method can decompose the bearing fault information from the current signal and overcome the problems of modal confusion and pseudo-component of the EMD method, which is an effective method to deal with rolling bearing faults. Meanwhile, this method has been verified by experiments show can accurately extract the fault information and improve the fault identification rate of motor-bearing data with an accuracy of 99.2%.
Jetting Velocity Prediction for Piezoelectric Ejection System Based on GA-BP
Authors: Xinli  , Zhao Yongsheng , Niu Nana , Chen Kui 
Published: March 2023

Abstract
Droplet jetting velocity is one of the most important factors affecting the quality of piezoelectric ejection printing. Due to the nonlinear relationship between the two, predicting the droplet jetting velocity by conventional methods is very time-consuming and impractical. We propose a genetic algorithm (GA) combined with a back propagation neural network (BPNN) to predict the droplet jetting velocity. The network topology and the values of each parameter of the model are designed and validated to elucidate the relationship between the input parameters of the piezoelectric ejection system and the studied droplet ejection velocity. The GA-BP model was trained, tested, and tuned using a database consisting of data generated from finite element calculations, and the results showed an error of 3.34% between the predicted and finite element simulated droplet ejection velocities, which demonstrates the reliability and robustness of the method.
3D printing of inorganic scintillator-based particle detectors
Authors: Sibilieva T. , Alekseev V. , Barsuk S. , Berns S. , Boillat E. , Boiaryntseva I. , Boyarintsev A. , Carbone A. , De Roeck A. , Dolan S. , Driuk T. , Gendotti A. , Gerasymov I. , Grynyov B. , Hugon S. , Kose U. , Opolonin O. , Rubbia A. , Sgalaberna D. , Sibilyev M. , Tretyak S. , Weber T. , Wuthrich J. , Zhao X.Y. 
Published: March 2023

Abstract
Inorganic scintillators are widely used for scientific,
industrial and medical applications. The development of 3D printing
with inorganic scintillators would allow the fast creation of
detector prototypes for the registration of ionizing radiation, such
as alpha, beta and gamma particles in thin layers of active
material, and X-ray radiation. This article reports on the technical
work and scientific achievements that aimed at developing a new
inorganic scintillation filament to be used for the 3D printing of
composite scintillator materials: study and definition of the
scintillator composition; development of the methods for the
inorganic scintillator filament production and further
implementation in the available 3D printing technologies; study of
the impact of the different 3D printing modes on the material
scintillation characteristics. Also, 3D-printed scintillators can be
used to produce combined detectors for high-energy physics.
Evaluation of the timing performance of the DIET ASIC
Authors: Lang Zijian , Deng Z. , Gong H. 
Published: March 2023

Abstract
DIET is a 64-channel SiPM readout ASIC for TOF-PET and can
measure energy and arrival time independently for each channel. With
the increasing requirements for time measurement precision, the
timing performance of the DIET chip has been fully evaluated in this
paper. The noise sources in the time processing chain, especially in
the TDC, were theoretically analysed, and a dedicated test system
was built. The time jitter of the analogue front end and the TDC
were measured and analysed. The test results show that the total
jitters of the analogue front-end and the TDC are 24 ps and 22 ps
RMS at 50 p.e. input signal, respectively. The percentages of the
contribution by INL, thermal noise, and quantization noise of the
TDC are 70%, 16.6%, and 13.4%, respectively. The DIET chip was
also tested with SiPM and LYSO detectors. A CRT resolution of
244 ps FWHM was achieved using two single
3 × 3 × 16 mm3 crystals.
A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research
Authors: Mangan Michael , Floreano Dario , Yasui Kotaro , Trimmer Barry A , Gravish Nick , Hauert Sabine , Webb Barbara , Manoonpong Poramate , Szczecinski Nicholas 
Published: March 2023

Abstract
Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevant for robot designers: Research on flying and crawling invertebrates has inspired new materials and geometries from which robot bodies (their morphologies) can be constructed, enabling a new generation of softer, smaller, and lighter robots. Research on walking insects has informed the design of new systems for controlling robot bodies (their motion control) and adapting their motion to their environment without costly computational methods. And research combining wet and computational neuroscience with robotic validation methods has revealed the structure and function of core circuits in the insect brain responsible for the navigation and swarming capabilities (their mental faculties) displayed by foraging insects. The last decade has seen significant progress in the application of principles extracted from invertebrates, as well as the application of biomimetic robots to model and better understand how animals function. This Perspectives paper on the past 10 years of the Living Machines conference outlines some of the most exciting recent advances in each of these fields before outlining lessons gleaned and the outlook for the next decade of invertebrate robotic research.
Hybrid modeling of evapotranspiration: inferring stomatal and aerodynamic resistances using combined physics-based and machine learning
Authors: ElGhawi Reda , Kraft Basil , Reimers Christian , Reichstein Markus , Körner Marco , Gentine Pierre , Winkler Alexander J 
Published: March 2023

Abstract
The process of evapotranspiration transfers liquid water from vegetation and soil surfaces to the atmosphere, the so-called latent heat flux (

Q

LE

), and modulates the Earth’s energy, water, and carbon cycle. Vegetation controls

Q

LE

by regulating leaf stomata opening (surface resistance

r

s

in the Big Leaf approach) and by altering surface roughness (aerodynamic resistance

r

a

). Estimating

r

s

and

r

a

across different vegetation types is a key challenge in predicting

Q

LE

. We propose a hybrid approach that combines mechanistic modeling and machine learning for modeling

Q

LE

. The hybrid model combines a feed-forward neural network which estimates the resistances from observations as intermediate variables and a mechanistic model in an end-to-end setting. In the hybrid modeling setup, we make use of the Penman–Monteith equation in conjunction with multi-year flux measurements across different forest and grassland sites from the FLUXNET database. This hybrid model setup is successful in predicting

Q

LE

, however, this approach leads to equifinal solutions in terms of estimated physical parameters. We follow two different strategies to constrain the hybrid model and therefore control for the equifinality that arises when the two resistances are estimated simultaneously. One strategy is to impose an a priori constraint on

r

a

based on mechanistic assumptions (theory-driven strategy), while the other strategy makes use of more observational data and adds a constraint in predicting

r

a

through multi-task learning of both latent and sensible heat flux (

Q

H

; data-driven strategy) together. Our results show that all hybrid models predict the target variables with a high degree of success, with

R
2

= 0.82–0.89 for grasslands and

R
2

= 0.70–0.80 for forest sites at the mean diurnal scale. The predicted

r

s

and

r

a

show strong physical consistency across the two regularized hybrid models, but are physically implausible in the under-constrained hybrid model. The hybrid models are robust in reproducing consistent results for energy fluxes and resistances across different scales (diurnal, seasonal, and interannual), reflecting their ability to learn the physical dependence of the target variables on the meteorological inputs. As a next step, we propose to test these heavily observation-informed parameterizations derived through hybrid modeling as a substitute for ad hoc formulations in Earth system models.
Unitary matrix integrals, symmetric polynomials, and long-range random walks
Authors: Vleeshouwers Ward L , Gritsev Vladimir 
Published: March 2023

Abstract
Unitary matrix integrals over symmetric polynomials play an important role in a wide variety of applications, including random matrix theory, gauge theory, number theory, and enumerative combinatorics. We derive novel results on such integrals and apply these and other identities to correlation functions of long-range random walks (LRRW) consisting of hard-core bosons. We generalize an identity due to Diaconis and Shahshahani which computes unitary matrix integrals over products of power sum polynomials. This allows us to derive two expressions for unitary matrix integrals over Schur polynomials, which can be directly applied to LRRW correlation functions. We then demonstrate a duality between distinct LRRW models, which we refer to as quasi-local particle-hole duality. We note a relation between the multiplication properties of power sum polynomials of degree n and fermionic particles hopping by n sites. This allows us to compute LRRW correlation functions in terms of auxiliary fermionic rather than hard-core bosonic systems. Inverting this reasoning leads to various results on long-range fermionic models as well. In principle, all results derived in this work can be implemented in experimental setups such as trapped ion systems, where LRRW models appear as an effective description. We further suggest specific correlation functions which may be applied to the benchmarking of such experimental setups.
Suitability of pressmud as an adsorption material in wastewater treatment and as a booster in soil fertility and productivity
Authors: Mohamad M , Osman N H , Rahim M K I A , Abustan I , A Zainol M R R M , Samuding K , Zakaria S N F , Abu F 
Published: March 2023

Abstract
Pressmud is one of the most abundant wastes produced by the sugarcane industry. However, it has received far too little attention as a reactive material for pollutant removal, although its beneficial effect on soil fertility and crop productivity is well established. This paper investigates the potential of pressmud to minimize heavy metal migration while boosting soil fertility and productivity. Firstly, the adsorbent was characterized by Fourier Transform Infrared Spectroscopy (FTIR) and Field-Emission Scanning Electron Microscopy (FESEM) analyses, which showed the presence of functional groups such as carbonyl, hydroxyl, and silica capable of adsorbing metal ions. The cation exchange capacity (CEC) of pressmud is very high, ranging between 44.9 and 45.2 meq/100 g. Along with removal efficiency testing and evaluating breakthrough curves, characterization and adsorption analyses (batch equilibrium and column test) were carried out. The pressmud reveals promising adsorption characteristics, including a high organic content (17.62%) and the presence of carbon, which significantly affects its excellent removal effectiveness. Based on the removal efficiency test, pressmud successfully removes metal ions at the highest value, such as zinc (Zn), at 99.7%. Meanwhile, its breakthrough curve reveals that it efficiently retained all heavy metals, as these metals do not reach 1 to 10 pore volumes (p.v.), indicating that pressmud is a good material for heavy metal adsorption and soil productivity. This possible use establishes a new cyclical flow for the material and contributes to its minimization and reuse, adhering to circular economy ideas. However, pressmud must be disposed of properly to avoid adverse effects on humans and the environment.
Water quality index analysis in Kim-Kim River: Effects of Covid-19 movement control order
Authors: Mohiyaden H A , Sidek L M , Noh S M , Selamat M K , Marufuzzaman M 
Published: March 2023

Abstract
Movement Control Order (MCO) and Conditional Movement Control Order (CMCO) has been implemented throughout the country to reduce the effect of the COVID-19 outbreak. During MCO, several activities, including anthropogenic activities, are not allowed to be operated. Kim-Kim River, which receives most of the effluent from the industrial area, is chosen as a study area for investigating the impact of MCO toward its water quality trends. The results showed that the Water Quality Index (WQI) has improved from Class IV before MCO to Class III during MCO at the upstream of Kim Kim river. Overall, Kim-Kim river water quality has been developed by 19% during MCO. Although from the previous 10 years water quality trends confirm that Kim Kim River is categorised as a polluted river, with the continuation of MCO and the new norm of COVID19, the WQI are expected to be improved.
Changes in the spatial-temporal of the amount of sediment suspended in the Mekong Delta in Vietnam
Authors: Phuong D N L , Binh D V , Kantoush S A , Nguyen Q H , Vinh T L , Phuong M N T , Nguyen H T , Sumi T 
Published: March 2023

Abstract
Sediment depletion in the Vietnamese Mekong Delta (VMD) has brought threats to riverbed and riverbank dynamics. The main objective of this research is to make a relationship between turbidity and suspended sediment concentration (SSCs) and to assess temporal-spatial variations of SSCs in the VMD. In this regard, the SSCs were measured and monitored along the Tien and Hau Rivers under the Japan-ASEAN Science, Technology, and Innovation Platform (JASTIP) project and Mekong River Commission (MRC). Particularly, we installed three monitoring stations in main rivers and conducted two field surveys to collect data for assessing SSC values in the VMD. The results show that the SSCs in the delta are changeable seasonally with high values in the high-flow season and low values in the low-flow season. The Tien and Hau Rivers can be divided into two reaches. The upper reach has high SSC, decreasing seaward, whereas the lower reach has lower SSC, increasing seaward.
Analyzation of water demand projection for Johor River Basin
Authors: Yani F , Hussien N , Noor Z Z , Hafizan C 
Published: March 2023

AbstractThis paper presents the projecting or forecasting of water demand for the Johor River Basin (JRB) from the year 2020 up to 2050. The aim for this research is to quantify and analyse the demand for water in the future from each sector which is most crucial around JRB such as domestic/residential, industrial, agriculture, livestock and non-revenue water; it is a key element for water demand quantification for JRB. Recent work for this quantification is more generalizing in terms of water demand as a whole in Johor state. Meanwhile, this research are using composite approaches which involve secondary data from various local authorities and involved four different districts only around JRB. This research also covers the scope of water consumption baseline data and information of JRB with the recent report. It appears that quality of data in terms of availability and reliability is very important and must be dealt with carefully, with good judgement and good engagement with local stakeholders or authorities when it comes to decision making, therefore must be able to get a rapid and simple understanding of water demand for JRB. It is significant to this research which to accommodate with United Nations Development Program and also promote greater awareness of the Sustainable Development Goal (SDG-6) which to ensure availability and sustainable management of water and sanitation for all.
Based on physical model test and analysis of hydraulic erosion of warping dam
Authors: Zhong F Q , Huo A D , Zhao Z X 
Published: March 2023

Abstract
As a common engineering measure in “Gully consolidation and highland protection” project, warping dam plays a great role in soil and water conservation in the loess Plateau region. This paper selects the Yangjiagou small watershed in Qingyang City, Gansu Province as the research object, sets up a warping dam to simulate erosion reduction, and establishes a physical channel model with equal scale reduction, to reveal the reciprocal feeding mechanism of hydraulic erosion to the “Gully consolidation and highland protection” project. According to experimental calculations, the total erosion amount of the three erosion tests before the construction of the warping dam is 7.25kg, 8.02kg and 9.20kg, and the total erosion amount of the three erosion tests after the construction of the silt dam is 4.51kg, 5.25kg and 6.18kg. The sand interception efficiency in the three water flushing tests is 37.8%, 34.5% and 32.8%. The results show that the construction of warping dam can raise erosion base level and alleviate soil erosion effectively. And the warping dam can still play a part of its sediment reduction capacity after it has been scoured several times and partially destroyed. With the increase of use time, the effectiveness of the warping dam for blocking sand gradually decreases.