bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of portable multi-channel isolated CNC-regulated power supply
Authors: Wang Kuantian , Li Peng , Luo Mengxia 
Published: March 2023

Abstract
In order to facilitate the testing needs of electronic engineers, a multi-channel isolation adjustable switching regulated power supply controlled by an STM32 single-chip microcomputer is designed [1]. The power supply is programmable and adjustable by a single-chip microcomputer, and the humanized display operation interface is combined with the high efficiency of switching the power supply. It can realize three channels of 30v2a isolated output, and realize one channel of 90v2a or 30v6a output through a relay automatic switching series-parallel combination, to maximize power density. The power supply has the characteristics of high integration, small volume, large power, large adjustable range, high precision, and high efficiency. It can be applied to the debugging and operation of most electronic equipment.
Automatic Identification of Integrated Circuits Based on YOLOv5
Authors: Luo Jinhui 
Published: March 2023

Abstract
For the requirements of automatic testing in the IC industry, an improved algorithm based on YOLOv5 is proposed to identify IC. Firstly, the feature enhancement of small targets is based on the structure of the feature pyramid (FPN) to improve the accuracy of small target detection. Secondly, the weight of the loss value of the wrong sample in the loss function is enhanced to improve the training efficiency of the model. Finally, through the verification of the dataset, the results show that the accuracy of target recognition of the improved model is improved to 99.8% compared with the existing model, which verifies the effectiveness of this method.
SOC Balancing Control Method for Cascaded Energy Storage System under Extreme Working Conditions
Authors: Li Yong-Qi , Ma Zhong-Dao , Chen Man , Tan Qi-Peng , Wang Wen-Jie 
Published: March 2023

Abstract
To solve the problem of an unbalanced state of charge (SOC) between the in-phase sub-modules of the cascaded H-bridge energy storage system, this paper proposed a method based on carrier phase-shifting pulse-width modulation. Different from the traditional in-phase balancing method which is achieved by adding components, by setting the parameter related to the SOC difference to adjust the amplitude of the modulation wave, the new method could solve the problem that the traditional method is not applicable under extreme SOC conditions. The new in-phase SOC balancing method could expand the scenario, and the feasibility of the method is verified by simulation.
Primary Frequency Regulation Strategy of PMSG-Based Wind Turbines Integrated Inertia Control
Authors: Ren Zhihong , Zhao Qianlin , Lu Dingwen , Yang Jianwei 
Published: March 2023

Abstract
Direct-drive permanent magnet synchronous wind turbine-generator (PMSG) generally operates in maximum power point tracking (MPPT) mode. PMSG cannot provide additional active power support when the grid frequency fluctuates.The gradual increase of wind power penetration leads to greater frequency regulation pressure, which brings hidden dangers to the power grid. This paper focuses on the grid connection of direct-drive PMSG, proposing a primary frequency regulation strategy integrated with inertia control. The proposed strategy controls the rotor kinetic energy to simulate inertia of synchronous units by adding the support power of the response frequency variation. It concludes with variable power tracking control and energy storage system control. Compared with the traditional strategy retains active power, this proposed strategy increases wind energy utilization. Adopting variable power tracking control combined with energy storage can overcome secondary frequency drop and reduce energy storage configuration capacity.
Dynamic simulation research of adaptive support mechanism of pipeline inspection robot based on ADAMS
Authors: Xiao Yihao , Wang Jirong , Yang Jiaqi , Li Jun 
Published: March 2023

Abstract
The drainage pipe contains plenty of toxic gases that are hazardous to the human body, and the narrow size of the drainage pipe makes manual inspection difficult, so it is necessary to use a robot to replace the manual inspection of the drainage pipe. For this purpose, this paper designs a pipe inspection robot that can smoothly realize the passage and inspection in the drainage pipe. With an adaptive support mechanism, the robot can move to the working position in the pipeline. The trajectory of the end of the support mechanism is planned, and the dynamics of the support mechanism are simulated by ADAMS to analyze the motor load to verify that it can cope with the complex environment of the drainage pipe.
Research on Induction Measurement of Operators Approaching Charged Bodies in Complex Operation Scenarios
Authors: Liu Lijie , Zhang Zhaoguang , Qi Chunfeng 
Published: March 2023

Abstract
Aiming at the uneven distribution of the electric field and the difficulty in achieving low false alarms for operators approaching charged bodies in the complex operating environment in the power system, a mask region convolutional neural network (MR-CNN) based complex operation scene recognizer is first constructed in this paper to perform image feature extraction, target box regression, and classification training. Secondly, a simulated annealing-based mirror-image charge method is proposed to calculate the electric field distribution characteristics. The simulated annealing algorithm is used to optimize the number of charges of the mirror-image charges method to minimize the weighted sum of the calculation error and the electric field strength calculation time. Finally, the feasibility and effectiveness of the proposed algorithm are verified through simulation experiments.
Research on Fault Diagnosis of Hoist Dangerous Load Based on DBN
Authors: Shi Fahui , Wang Zheng , Ma Chi 
Published: March 2023

Abstract
At present, hoisting accidents caused by dangerous loads such as overloading, incomplete unloading, conveyance jamming, and rope loosening still occur. Therefore, this paper proposes a fault diagnosis method for dangerous loads of hoists based on the Deep Belief Network (DBN). With the stator current of the hoisting motor as the signal source, the 31-dimensional eigenvalues of the stator current of the hoisting motor in the time, frequency, and time-frequency domains are taken as the input parameters of the deep belief network. The restricted Boltzmann machine is used for unsupervised pre-training through layer-by-layer transmission and layer-by-layer training. The BP neural network, as the top-level classifier, is used for supervised fine-tuning training to finally complete the whole training process of the depth belief network. Relying on the advantages of the depth belief network, which has fast training speed and strong feature extraction ability. It makes up for the deficiency of the traditional algorithm in feature extraction and classification separation, resulting in the loss of details, and finally realizes the overload Classification of four types of dangerous loads, i.e., unloaded, blocked, and slackened. The results show that the method based on DBN has higher identification and better diagnosis effect.
Design of a prediction model based on improved BP neural network and particle swarm optimization for more accurate budget of biogas production
Authors: Wu YuChen , Zhang GuangMing 
Published: March 2023

Abstract
In order to accurately predict the daily gas production of large and medium-sized biogas projects, the improved BP neural network algorithm was used, and the PSO algorithm was introduced to optimize the parameters. According to the anaerobic fermentation mechanism and the actual engineering operation status, a prediction model was established with temperature, daily feed volume, NH3, TS concentration and pH value as input layer nodes, and daily biogas production as output layer nodes. The 116 sets of data obtained by remote data acquisition are used as training samples and test samples of the model, and the simulation is carried out by Matlab software. The results show that the PSO-LM-BP neural network has good predictive ability for the daily gas production of biogas. The established biogas daily gas production prediction model not only converges fast but also has high accuracy.
A Temperature Correction Method Based On Deep Learning
Authors: Hao Chenfei , Du Xinyu , Wang Jiarun 
Published: March 2023

Abstract
This paper presents a numerical model based on product temperature prediction deep learning error correction method, using two-dimensional convolution both short-term and long-term memory network model, using the European Centre for Medium-Range Weather Forecasts in 2018 numerical weather prediction model 2m temperature forecast products and part of China’s meteorological site data, using meteorological site temperature, wind speed, pressure, relative humidity, four elements. The spatio-temporal characteristics of the observed data were mined and combined with the model 2m temperature forecast results to train the deep learning model, and the prediction results of the short-and medium-term grid forecast products of the model 2m temperature in 2018 were interpolated to the station to correct the deviation. The results show that the Bi-Conv-LSTM model can reduce the overall root mean square error of temperature forecast from 4.35 °C to 2.75 °C, which is 44.6% lower. The Bi-Conv-LSTM model has an obvious effect on the correction of the temperature forecast error of the station, which verifies the application ability of deep learning in the field of meteorological correction.
Physical design of fusion target with edge computing
Authors: GaoyangLiu  , Peng Dongfang , Xiong Wenbin , Gao Qiang , Qu Fanyu , Tang Zhangchun , Liu Pan 
Published: March 2023

AbstractThe physical design of the fusion target is an important part of controlled thermonuclear fusion, and the geometric model and material selection of the target is also critical to achieving fusion ignition. We have modularised the target and introduced digital modeling, edge computing, and deep learning technologies to build a data-driven hybrid computing framework. We construct physical models and integrate them into a unified digital model of a multi-domain system; simulate and iteratively modify the physical model, and use edge computing technologies for information modeling. Edge computing is well applied to the calculation of each module of the target. Each module is both correlated and independent, and the values of the fusion ignition temperature and density achieved in the target are obtained, and the neutron products in the ignition and main fuel regions are 1016- 1017and 1019respectively. This will be an important reference value for the design of actual fusion targets.
Research on Attitude Calculation Based on MEMS Sensor
Authors: Zhang Cheng , Lin Guomin , Chen Zhen 
Published: March 2023

Abstract
According to the requirement of attitude measurement of moving carriers, the MPU9250 sensor is used to collect real-time data on moving carriers. However, the accuracy of the sensor is low, and there is a large error between the calculated attitude value and the real value. Therefore, in this paper, the adaptive complementary filtering algorithm and ellipse fitting method are adopted, which effectively reduces the error and makes the attitude angle more accurate. Based on the Euler angle and quaternion differential equation, the attitude angles
ϕ
and
θ
are obtained by correcting the gyroscope value according to the adaptive complementary filtering algorithm. Then the magnetometer in the MPU9250 sensor is processed by ellipse fitting based on the least square method, and the heading angle
ψ
of the moving carrier is calculated. Through static and dynamic experiments, it can be seen that the attitude angle obtained by adaptive complementary filtering and ellipse fitting is more accurate and stable.
An adjustable active noise control algorithm based on Bark scale
Authors: Su Haitao , Hu Chunjing , Chen Jiaxuan , Hu Hongzhi , Xu Cuifeng 
Published: March 2023

Abstract
An adjustable active noise control algorithm is proposed based on human auditory perception. Because of the FELMS algorithm, the Bark scale decomposition is used for simulating the decomposition of the human ears to the acoustic signal, and the real time response of the human ears to the noise is calculated. Residual filter is designed based on this real-time response so that the noise reduction effect is more in line with the human beings auditory perception. In the meantime, the adjustment parameter is set to adjust the amplitude-frequency response of the designed residual filter so that the noise reduction effect can be adjusted artificially under the condition of preserving the noise characteristics. Computer simulation results show that, match with the convention FXLMS algorithm, the algorithm put forward in this paper makes the residual noise, and the original noise has a similar energy change trend in Barks. This algorithm makes the noise reduction effect more aligned with the human auditory perception. It can retain the noise characteristics and artificially adjust the noise reduction effect.
Inkjet OLED printing planning based on deep reinforcement learning and reward-based TLO
Authors: Lian Zekai , Lv Cixing , Lu Wei 
Published: March 2023

Abstract
With the increasing use of OLED screens in electronic products, there is a focus on how to print OLED screens more efficiently. Deep reinforcement learning is being used to solve the OLED printing planning problem because it effectively uses historical data and is also real-time. This paper uses a modified TLO method to combine deep reinforcement learning for multi-objective optimization of OLED printing. Through experiments, the method is compared with the linear weighting method commonly used in multi-objective reinforcement learning, which is more effective in optimization.
Application of new power flow calculation in ship power system
Authors: Wang Wenxuan , WeifengShi  
Published: March 2023

Abstract
A relevant mathematical model regarding the calculation of tidal currents in ship power systems is constructed for the actual situation of ship power systems. The nodal is used to verify the applicability of its method in the ship power system. The algorithm program for the ship power system using radiation networks is prepared using MATLAB, and the accuracy of the algorithm is verified by an example. Verification of ship power flow calculation and its stability by Newton method,which will greatly help to improve the operation of the ship’s electric power system.
Multi-parameter infrared sensing method for operation state of power equipment
Authors: Song Qingwu , Fengjiang  , Li Chunpeng , Wang Yifan , Bao Zhengjun , Shao Shanrui 
Published: March 2023

Abstract
Aiming at the problems of difficult extraction and reconstruction of multi-parameter signals and poor perception effect of power equipment operation status, a multi-parameter infrared perception method of power equipment operation status is proposed. The multi-parameter (sound, light, electricity, vibration, heat, and environment) sensors of power equipment operation status are selected, the multi-parameter sensor integration framework is built based on the Internet of things technology, the multi-parameter sensors are effectively integrated, the power equipment operation status parameter signals are collected and reconstructed, the power equipment operation status perception model is built, the unsupervised classification and AR algorithm are introduced, and the reconstructed signals are fitted, to realize the infrared perception of power equipment operation status. The experimental data show that the integrity of power equipment operation state parameters and the accuracy of power equipment operation state perception obtained by the proposed method are higher, which proves that the proposed method has a good effect on power equipment operation state perception.
Study of a planar cascaded GEM TEPC with sealed chamber for the radiation detection in microdosimetry
Authors: Wang H.Y. , Hu C.C. , Ruan S.Z. , Qi H.R. , Jiao L. 
Published: March 2023

Abstract
In the field of radiation detection in microdosimetry, the
Tissue Equivalent Proportional Counters (TEPCs) are the key detector
options in determining the radiation quality. In this paper, two
different structures of TEPCs were introduced, and their electric
field uniformity and angular dependence were disscussed. A planar
cascaded GEM TEPC with sealed chamber was developed in the
laboratory and the general materials used in the detector were
tested for outgassing characteristics. The experimental results
showed that the polyether ether ketone (PEEK) had the lowest
outgassing rate among all tested materials and were selected as the
main assembly materials of the TEPC detector. The 241Am was
used as the built-in radioactive source for detector calibration,
and the detector gain characteristics were studied. The long-term
operating stability was tested at working pressure of 54.72 kPa,
with a gain consistency of better than 97.8% over 7 days
(168 hours) and relative gain variation less than 1% over 4 days
(96 hours).
Water Stress Index application to assess water scarcity of Lower Vu Gia - Thu Bon River Basin in Vietnam
Authors: Mai D T T , Vo D N , Tran N T V 
Published: March 2023

Abstract
The role of water security is the importance of sustainable development in a country. This study used the water stress index (WSI) to evaluate the status of water resources and water exploitation in the Vu Gia - Thu Bon river basin. In the study, the Vu Gia - Thu Bon river basin was divided into 15 areas to calculate the water stress index (WSI) through the following calculation: The water availability is calculated by the simulation software MIKE SHE; Demand water (domestic, industry, agriculture); Environmental water requirement (EWR) to maintain environmental stability of the river. The findings have shown that 1) There is WSI differences beetwen upper and lower Vu Gia Thu Bon; 2) In the downstream areas, WSI value is up to 4 in the dry season. WSI exceeds 1 times is during the period from April to June. Water scarcity becomes more serious than in the middle and upstream areas, especially, the exploitation area to supply water for domestic and industry in Da Nang city.
Validation of Hershfield probable maximum precipitation estimation using homogeneous region in Malaysia
Authors: Paramasivam R , Alias N E , Lokoman R M 
Published: March 2023

Abstract
Probable maximum precipitation (PMP) is used to design major hydraulic structures, such as dams and spillways, flood protection works, and nuclear power plants. Long observation data are required for PMP estimates using the Hershfield statistical approach. In Malaysia, the PMP calculated using state boundary is commonly used, but the estimated PMP values are close to historical maximums. Homogeneous regions are regions containing stations with similar rainfall characteristics. Therefore, homogeneous region boundaries could be used for PMP estimations. In this paper, 1-day rainfall data of more than 25 years for 161 stations in Peninsular Malaysia; were analysed to estimate the PMP for 1-day duration based on an appropriate frequency factor by considering homogeneous regions. Using PMP estimates, a generalised graph was prepared to show the spatial distribution of 1-day PMP. The 1-day PMP estimates in Peninsular Malaysia by considering state boundary, varied from 146 to 1364.7 mm and by considering the homogeneous regions, the 1-day PMP estimates varied from 208.5 to 2094 mm. Hence, the PMP considering homogeneous regions is considered more accurate and safe to be used in designs.
Rapid production of organic fertilizer using subcritical water treatment on waste biomass
Authors: Huzir N M , Hussin M H , Rosly M B , Amin A N R , Asmadi A A , Md Ali A H , Balasundram V , Yen L P , Goto M , Tamunaidu P 
Published: March 2023

Abstract
Waste biomass are highly valuable and have potential to be converted to organic fertilizers or compost. This is a great alternative to replace the uses of commercial chemical fertilizers towards sustainable agriculture. However, due to its complex molecular structure and high lignin content, it hinders full decomposition of these wastes into mature compost. Therefore, subcritical water (SCW) pre-treatment was studied to enhance the hydrolytic degradation of biomass waste such as rice straw, banana peel, and chicken feathers to be converted into mature compost within a shorter time. Validation on the maturity of the treated substrates and measurements of the level of phytotoxicity in the compost were studied based on the germination index (GI) of Japanese mustard seeds. Results showed that all treated substrates provided high GI of more than 60% at its optimum concentration which indicates the significant contribution of SCW pre-treatment to produce effective mature compost.
Route selection for road vehicle real-driving emissions test using GIS
Authors: Yusof N , Abas M A , Rohana N A , Mohd Perang M R 
Published: March 2023

Abstract
The European Commission has developed a Real-Driving Emissions (RDE) test for road vehicles that complies with the urban, rural and motorway criteria to ensure the exhaust emission produced could be accurately evaluated. Therefore, careful measures are taken in selecting the best routes to ensure the testing fulfils the targeted criteria. As there is no common method exist to select the testing route, analysis on the testing route selection was implemented using Geographic Information System (GIS) platform that is capable to deal with large vector data. Thus, the proposed framework facilitates the testing route selection process which is difficult to determine without a proper spatial analysis of network data. Specific route information comprises of road categories, route speed range and route classes were collected from the Open StreetMap (OSM) database. The generated route density and the topological route network structure were used to further analyse the suitability route as the requirement of Real-Driving Emissions test. As a result, five candidates of Real-Driving Emissions test route have been selected in Malaysia as a case study using GIS platform.
Low resistance electrical contacts to few-layered MoS2 by local pressurization
Authors: Manzanares-Negro Yolanda , Quan Jiamin , Rassekh Maedeh , Moaied Mohammed , Li Xiaoqin , Ares Pablo , Palacios Juan José , Gomez-Herrero Julio , Gomez-Navarro Cristina 
Published: March 2023

Abstract
The performance of electronic and optoelectronic devices is dominated by charge carrier injection through the metal–semiconductor contacts. Therefore, creating low-resistance electrical contacts is one of the most critical challenges in the development of devices based on new materials, particularly in the case of two-dimensional semiconductors. Herein, we report a strategy to reduce the contact resistance of MoS2 via local pressurization. We fabricated electrical contacts using an atomic force microscopy tip and applied variable pressure ranging from 0 to 25 GPa. By measuring the transverse electronic transport properties, we show that MoS2 undergoes a reversible semiconducting-metallic transition under pressure. Planar devices in field effect configuration with electrical contacts performed at pressures above ∼15 GPa show up to 30-fold reduced contact resistance and up to 25-fold improved field-effect mobility when compared to those measured at low pressure. Theoretical simulations show that this enhanced performance is due to improved charge injection to the MoS2 semiconductor channel through the metallic MoS2 phase obtained by pressurization. Our results suggest a novel strategy for realizing improved contacts to MoS2 devices by local pressurization and for exploring emergent phenomena under mechano-electric modulation.