bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hands-on with OWL: the Oak–Ridge Wang–Landau Monte Carlo software suite
Authors: Wai Li Ying , Chaitanya Pitike Krishna , Eisenbach Markus , Cooper Valentino R. 
Published: December 2021

Abstract
The Oak–Ridge Wang–Landau (OWL) package is an open-source scientific software specialized for large-scale, Monte Carlo simulations for the study of materials properties at finite temperature. In this paper, we discuss the main features and capabilities of OWL, followed by detailed descriptions of building and running the code. The readers will be guided through the usage and functionality of the code with a few hands-on examples. This paper is based on a tutorial on OWL given at the 32nd Center for Simulational Physics Workshop on Recent Developments in Computer Simulation Studies in Condensed Matter Physics.
Edge cloud task scheduling model based on layered excellent gene replication strategy
Authors: Zhu Leilei , Zhao Ke , Lin Huaze , Liu Dan , Li Li 
Published: December 2021

Abstract
With the development of the Internet of Things and 5G. Edge cloud technology has gradually become a research hotspot. When facing the massive and concurrent tasks of terminal users, reasonable resource scheduling strategy is a key technology. Because edge cloud needs to respond quickly to real-time tasks and ensure the stability of nodes at the same time, the optimal task scheduling strategy needs to be selected to meet the low latency requirements of edge users. In view of the above problems in resource allocation of edge cloud, this paper established a layered excellent gene replication strategy (HEGPSO model), in which the optimal replicator is added, and an evolutionary particle swarm optimization algorithm is proposed. In each iteration, the population is divided into three layers based on individual fitness. After that, the optimal replication factor is added to each layer of individuals to enhance the global search ability of the algorithm and ensure the good convergence of the algorithm. Finally, a balanced resource allocation model is established. Experiments show that the HEGPSO model proposed in this paper has high fitness and fast convergence speed, and is suitable for large-scale task access scenarios.
Group recommendation method combining short-term interest and long-term preference
Authors: Zhu Hangyu , Gao Maoting 
Published: December 2021

Abstract
Based on self-attention and outer product-based neural collaborative filtering,this paper proposed a SLAR model.The model uses the recent interaction information of each user in the group and self-attention mechanism to obtain the short-term interest vector of the group.The attention mechanism and self-attention mechanism are used to calculate the influence of each user and the influence between members during the interaction between the target group and item, so as to aggregate them into the long-term preference vector of the group, and then the sum of short-term interest and long-term preference is input into ONCF model as the embedding vector of the group to mine the interaction between the group and the project from the data, and finally complete the group recommendation. Compared with the traditional group fusion strategy on CAMR2011 data set, the experimental results show that SLGR model achieves better results.
Research on Optimization of Fuzzy Network Control System Based on New Smith Predictive Time Delay Compensation
Authors: Lu Cong , Xian Xuehui , Li Changqing 
Published: December 2021

Abstract
Aiming at the problem of network delay when the network control system transmits data, this paper adopts a new type of fuzzy control method of Smith predictor to compensate for the delay. In actual application scenarios, it is difficult to accurately match the Smith prediction model with the actual model. At the same time, the quantization factor and scale factor in the fuzzy PID controller are too dependent on experience, which makes the system’s adaptability to actual working conditions very poor. In this paper, genetic algorithm is used to optimizes fuzzy PID. According to the simulation results, when the Smith predictive model does not match the actual model, the steady-state performance and dynamic performance of the system under the fuzzy PID control optimized by the genetic algorithm are improved.
Optimal Security Protection Selection Strategy Based on Markov Model Attack Graph
Authors: Yang Jinwei , Yang Yu 
Published: December 2021

Abstract
Intrusion intent and path prediction are important for security administrators to gain insight into the possible threat behavior of attackers. Existing research has mainly focused on path prediction in ideal attack scenarios, yet the ideal attack path is not always the real path taken by an intruder. In order to accurately and comprehensively predict the path information of network intrusion, a multi-step attack path prediction method based on absorbing Markov chains is proposed. Firstly, the node state transfer probability normalization algorithm is designed by using the nil posteriority and absorption of state transfer in absorbing Markov chain, and it is proved that the complete attack graph can correspond to absorbing Markov chain, and the economic indexes of protection cost and attack benefit and the index quantification method are constructed, and the optimal security protection policy selection algorithm based on particle swarm algorithm is proposed, and finally the experimental verification of the model in protection Finally, we experimentally verify the feasibility and effectiveness of the model in protection policy decision-making, which can effectively reduce network security risks and provide more security protection guidance for timely response to network attack threats.
Coordinated intelligent manipulator based on exoskeleton
Authors: Wang Xiang , Yang Fan 
Published: December 2021

AbstractManipulators have a wide range of applications in telemedicine, deep-sea exploration, remote explosive-removal and prosthesis for the disabled. Based on exoskeleton and voice control, a coordinated intelligent manipulator was proposed in this paper. The main design scheme, attitude angle data acquisition and data processing methods were given, and the final test results were obtained.
STI direct test method based on wavelet transform to extract envelope
Authors: Wang Wenxin , Zhu Ranran , Zhao Hongliang 
Published: December 2021

Abstract
Speech transmission index (STI for short) is an important index to evaluate the quality of speech transmission of the room, it can better reflect the degree of voice signal affected by room reverberation and noise in the transmission process.This paper presents an algorithm for directly measuring STI index, white noise is filtered by Paul Kellet filter to generate pink noise, the signal envelope is extracted by wavelet transform, which improves the extraction accuracy of signal envelope and makes the measurement of STI index more accurate.
Transmission line surface defect detection method based on uav autonomous inspection
Authors: Xie Xu 
Published: December 2021

Abstract
The existing transmission line surface defect detection methods have the problem of incomplete image data set, resulting in a low recognition success rate. A transmission line surface defect detection method based on uav autonomous inspection is designed. The safety of power grid operation is evaluated, the local linearization process is transformed into linear equation expression, the image data set is obtained by uav autonomous inspection, the transmission line state is judged, the corresponding constraint conditions are set, the type of transmission line surface defects are identified, the number of image poles and towers is matched, and the detection mode is optimized by edge detection algorithm. Experimental results: The average recognition success rate of the transmission line surface defect detection method in this paper and the other two detection methods is 59.89%, 51.89% and 52.03%, proving that the transmission line surface defect detection method integrating UAV technology inspection has a wider application space.
Deep attributed network embedding by mutual information maximization
Authors: Tao Wujun , Ye Yu , Feng Bailin 
Published: December 2021

Abstract
There is a growing body of literature that recognizes the importance of network embedding. It intends to encode the graph structure information into a low-dimensional vector for each node in the graph, which benefits the downstream tasks. Most of recent works focus on supervised learning. But they are usually not feasible in real-world datasets owing to the high cost to obtain labels. To address this issue, we design a new unsupervised attributed network embedding method, deep attributed network embedding by mutual information maximization (DMIM). Our method focuses on maximizing mutual information between the hidden representations of the global topological structure and the node attributes, which allows us to obtain the node embedding without manual labeling. To illustrate the effectiveness of our method, we carry out the node classification task using the learned node embeddings. Compared with the state-of-the-art unsupervised methods, our method achieves superior results on various datasets.
A People-Oriented Designing for Pattern Carving Intelligent Control Integrated Device
Authors: Li Yan , Fang Shuguang 
Published: December 2021

Abstract
Aiming at solving the problems of weak human-computer interaction, poor scalability, low system integration, and lack of information management capabilities of the original engraving equipment, a set of pattern engraving intelligence integrated management and control device has been developed. The device flexibly integrates the main processes of engraving machining, detection, sorting, etc, and realizes the automatic machining of multi-mode engraving tasks such as on-site touch screen delivery, remote machine vision collection, network PC communication, and mobile APP sending. It can identify and evaluate the characteristic parameters of engraved final products over non-contact machine vision; and use the SCARA robot for intelligent sorting and palletizing of engraved final products. In addition,its information management platform can realize real-time monitoring of production status and production data storage and statistical analysis. In general, the device realizes the intelligent upgrade and informatization transformation of traditional engraving equipment.
Analysis and Treatment of Electrical Fault of Ship Windlass
Authors: Wang Yanyang , Liu Chongchong , Hu Linxiang , Chen Shuai 
Published: December 2021

Abstract
This paper aims at the electrical failure of the ship anchor machine, the potential causes of the failure are summarized and summarized by analyzing the electrical principle of the anchor machine. After the on-site failure investigation, the cause of the failure is accurately located, so as to put forward a feasible plan for the use and daily maintenance of the ship anchor machine. Because of its simple structure, stable operation and easy maintenance, the anchor machine is used for anchoring and maintenance of ships. Port docking is very important for ship safety and is widely used on ships.
Study on Rheological Properties of Nanofluids
Authors: Bian Yan-qing , Wu Pu-cheng , Hao Jing , Shi Quan , Qin Guo-wei 
Published: December 2021

Abstract
Based on the previous research on the rheological properties of nanofluids by many scholars at home and abroad, to solve the problem that the viscosity of conventional polymer water control agents is large and cannot meet the demand for increasing production capacity in the process of tight gas reservoir exploitation, this paper takes self-made nanofluids as the research object, tests the rheological properties of self-made nanofluids by rheological experiment, and systematically studies the effects of concentration, temperature and shear action on the viscosity of nanofluids, and the dynamic viscoelasticity and thixotropy of nanofluids were discussed. The results show that the rheological type of nanofluid belongs to power-law fluid, but it is related to the shear rate. The viscosity of nanofluids increases with the increase of concentration; when the temperature increases, the viscosity of nanofluids decreases and the fluidity increases; under the shear action, the viscosity of nanofluid changes very little and has good shear resistance; the dynamic viscoelastic test shows that the storage modulus G´ of the nanofluid is larger than the loss modulus G”, showing elastic characteristics; the thixotropy test shows that when the shear rate is accelerated, the viscosity decreases with time, and when the shear rate is slowed down, the viscosity recovers rapidly with time, which has good thixotropy. The research results provide an important theoretical basis for further research on the application of nanomaterials in tight oil and gas reservoirs.
Deep learning classification and regression models for temperature values on a simulated fibre specklegram sensor
Authors: Arango J D , Aristizabal V H , Carrasquilla J F , Gomez J A , Quijano J C , Velez F J , Herrera-Ramirez J 
Published: December 2021

Abstract
Fiber optic specklegram sensors use the modal interference pattern (or specklegram) to determine the magnitude of a disturbance. The most used interrogation methods for these sensors have focused on point measurements of intensity or correlations between specklegrams, with limitations in sensitivity and useful measurement range. To investigate alternative methods of specklegram interrogation that improve the performance of the fiber specklegram sensors, we implemented and compared two deep learning models: a classification model and a regression model. To test and train the models, we use physical-optical models and simulations by the finite element method to create a database of specklegram images, covering the temperature range between 0 °C and 100 °C. With the prediction tests, we showed that both models can cover the entire proposed temperature range and achieve an accuracy of 99.5%, for the classification model, and a mean absolute error of 2.3 °C, in the regression model. We believe that these results show that the strategies implemented can improve the metrological capabilities of this type of sensor.
Box-Jenkins stochastic models for studying air pollutants in a Latin American megacity
Authors: Pinzón-Hassan A D , Tique-Ortiz V , Zafra-Mejía C A 
Published: December 2021

Abstract
The objective of this paper is to show the development of Box-Jenkins stochastic models to study the behavior of air pollutants concentrations in the megacity of Bogotá, Colombia. Information was collected from 10 stations in the city’s air quality monitoring network over a ten-year period. The temporal relationship between air pollutants, their spatial variation, and the occurrence of extreme pollution episodes was studied using Box-Jenkins models. The results showed that the moving average term of the models developed was the main indicator of spatial distribution for the daily pollutant concentrations. In the case of atmospheric particulate matter < 10 μm, the following spatial distribution was identified in the megacity: northwestern, center-southwest, and southeast. For atmospheric particulate matter < 2.5 μm: north, center, and southwest. For ozone: northwest, center, and south. Maximum hourly particulate matter concentrations were observed between 6-10 a.m., and between 11 a.m. - 4 p.m. for ozone. Monthly, the highest particulate matter concentrations were observed in February (14.1%), January (13.5%), and March (12.2%). In the context of atmospheric physics, this study was relevant for the following findings: The usefulness of Box-Jenkins models in simulating the temporal behavior of air pollutants, and for their adequate performance in detecting urban spatial trends.
Numerical simulation to evaluate the influence of geometric parameters on the physical behavior of heat exchangers
Authors: Rojas Suárez J P , Pabón León J A , Orjuela Abril M S 
Published: December 2021

Abstract
In the present investigation, a methodology was developed by means of numerical simulation for the evaluation of the influence of the geometric parameters of the heat exchangers used in thermoelectric generation devices. The validation of the proposed methodology was carried out through experimental tests on a diesel engine test bench under four load conditions (2 Nm, 4 Nm, 6 Nm, and 8 Nm) and a constant speed of 3600 rpm. The results obtained show that the methodology proposed by means of the numerical simulation presents a high concordance with the behavior described experimentally. The deviation between the simulation predictions and the experimental results was less than 4%. Additionally, it was evidenced that the change in the geometry of the heat exchanger has a considerable impact on the parameters of heat flow and surface temperature. It was shown that a 50% reduction in fin distance causes an increase of 2% and 2.4% in the previous parameters. Through geometric modifications, the electrical power generated increased by 7.9%. In general, the methodology developed through numerical simulation allows the analysis of the physical, thermal, and hydraulic phenomena present in heat exchangers focused on use in thermoelectric devices.
Representation of gas metal arc pulsed welding process behavior on bead geometry: a study of leading variables
Authors: Lázaro Plata J L , Sánchez Rincón C S 
Published: December 2021

Abstract
Gas metal arc welding is one of the most influential processes in the production and repair of structures and equipment; therefore, the need to improve the productivity and quality of welded joints has led to the development of techniques for good control of welding parameters. Also, the development of semi-automatic welding processes led to the control of one of the variables such as pulsed current; this technique is characterized by a lower heat input and lower energy expenditure, which directly influences the structural quality of the welded joint and the geometry of the weld bead. This work focused on evaluating the effects of various welding operating parameters using the central composite design tool based on the response surface methodology; next, the experimental development employed an inverter type power source for weld depositions, a commercial grade Stargold clean 96% Ar and 4% CO2 shielding gas at the rate of 15 L/min stationary arc, a 1.2 mm metal cored wire for welding deposit and a carbon steel base plate with a thickness of 6 mm. During the welding process, the torch was kept at a 90° inclination and a 16 mm stroke. To examine the adequacy of the empirical models and the significance of the regression coefficients, the variance analysis was employed. Consequently, the graphs were obtained through the determination of the model; from the statistical results obtained, it was shown that the above models were adequate to predict the weld width, bead height, and penetration within the range of variables studied. Furthermore, it was observed that the wire feed rate it has a very marked effect on weld bead geometry, followed by frequency pulse and peak current; finally, the effectiveness of employing these methodologies for the management of variables attributing to the execution of welding tasks with higher accuracy was demonstrated.
Determination of the physical-mechanical properties of a permeable block
Authors: Jaramillo H Y , Gómez-Camperos J A , Quintero-Quintero N 
Published: December 2021

Abstract
This study aims to analyze the influence of the incorporation of crushed polyethylene terephthalate as a substitute for fine aggregate in percentages of 10%, 15%, and 20% for the elaboration of concrete blocks. The methodology used is experimental quantitative approach, where the influence of the addition of crushed polyethylene terephthalate as a substitute for fine aggregate for the elaboration of concrete blocks was analyzed to identify the variation in the physical and mechanical properties of samples elaborated under different substitutions and in this way compare with the Colombian standard procedures. The results found in this study indicated that the blocks with the different percentages of polyethylene terephthalate presented a good resistance compared to the block without polyethylene terephthalate, which presented a resistance of 8 MPa. The blocks with polyethylene terephthalate at 10%, 15%, and 20% presented an average resistance of 6.36 MPa, 3.58 MPa, and 4.63 MPa, respectively. Finally, it was analyzed that the blocks with 10% aggregate are waterproof with normal density. In comparison, the blocks with 15% and 20% polyethylene terephthalate have high permeability, with the ability to drain 1 liter of water in 105 s and 38 s, respectively.
Design and first result of combined Langmuir-magnetic probe on J-TEXT tokamak
Authors: YANG Qinghu , CHEN Zhipeng , HAO Zhigang , ZHAO Yangming , XU Xin , LI Shuhao , YANG Jie , YAN Wei , JIANG Zhonghe , CHEN Zhongyong , WANG Nengchao , YANG Zhoujun , PAN Yuan , DING Yonghua 
Published: December 2021

Abstract
In order to measure boundary electrostatic and magnetic fluctuations simultaneously, a combined Langmuir-magnetic probe (CLMP) has been designed and built on joint-Texas experimental tokamak. The probe consists of 8 graphite probe pins and a 3D magnetic probe, driven by a mechanical pneumatic device. By means of simulation, the shielding effect of the graphite sleeve on the magnetic fluctuation signal is explored, and the influence of the eddy current was reduced by cutting the graphite sleeve. In the experiment, it has been verified that the mutual inductance of electromagnetic signals can be ignored, and a 70–90 kHz electromagnetic mode is observed around the last closed magnetic surface. The establishment of CLMP provides data for the exploration of the coupling of electrostatic and magnetic fluctuations.
Quantitative analysis of electrically active defects in Au/AlGaN/GaN HEMTs structure using capacitance–frequency and DLTS measurements
Authors: Bano Nargis , Hussain Ijaz , Al-Ghamdi Eman A. , Ahmad M. Saeed 
Published: December 2021

Abstract
Electrical trap states in the AlGaN-based high-electron-mobility transistor (HEMT) structures limit the performances of devices. In this study, we present a comprehensive study of the electrical trap states in AlGaN/GaN HEMT structures and examine their influence on the device performance. We performed capacitance–frequency and conductance–frequency measurements to determine the time constant and the density of the interface states. The density of the interface states was calculated to be 2 × 1010 cm−2 eV−1, and the time constant of the interface states was 1 μs. Deep-level transient spectroscopy showed the presence of one electron trap E1 (negative peak) and three hole-like traps P1, P2, and P3 (positive peaks). The thermal activation energies for E1, P1, P2, and P3 traps were calculated to be 1.19, 0.64, 0.95, and 1.32 eV, respectively. The electron trap E1 and the hole-like traps P1, P2 and P3 were observed to originate from the point defects or their complexes in the material. The hole-like traps reflected the changes created in the population of the surface states owing to the capture of the surface states; these traps originated from the point defects related to the nitrogen vacancy.