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13th International Field Exploration and development Conference, IFEdC 2023

作者： Xiao, Yue Zhou, Tuo Li, Hangyuan Kong, Xiangji Song, Lu diao, Shunong Liu, Jitong Zhong, Zhao Jin, Yulai Li, Bingrou CNPC Engineering Technology R&D Company Limited Beijing102206 China China National Oil and Gas Exploration and Development Corporation Beijing China National Engineering Research Center for Oil and Gas Drilling and Completion Technology Beijing China College of Petroleum Engineering Beijing China

ISBN: (纸本)9789819702558

The quality of drilling wellbore is crucial for oilfield companies to evaluate the construction acceptance of drilling operations, evaluate the wellbore quality before cementing operations, and smoothly implement subsequent casing and electrical logging tools. At present, the evaluation of wellbore quality only requires dispersed trajectory parameters of different well sections (well inclination angle, dog leg angle, target range), and only considers whether the trajectory parameters are within the qualified range during completion acceptance. A quantitative scoring method for wellbore quality has not yet been developed, which is not conducive to the evaluation of well quality by oilfield enterprises during drilling completion acceptance. In this paper, the key parameters such as deviation measurement interval, dogleg degree, maximum deviation and target hit are comprehensively considered. Based on the comprehensive method of mathematical statistics and Matlab programming calculation, a multi-level quantitative scoring model of well bore quality is established. The key parameters in the multi-level quantitative model of well bore quality are determined by using the main control factor analysis method of random forest algorithm. Taking the A oil field as an example, a quantitative scoring was conducted on the quality of 74 drilled wells in 2021 to evaluate the effectiveness of the operation team in controlling well quality. The analysis results showed that for the A oil field, the importance of factors affecting well quality was as follows: maximum inclination > Target radius > dog leg = survey interval. Crew 1 had better control over well quality, and the proportion of high-quality wells in 2021 decreased compared to 2020, The analysis results of the multi-level well bore quality quantification method based on random forest algorithm proposed in this paper are in line with the field work practice, which provides a theoretical basis for well bore quality quantificati

关键词： MATLAB

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How well can PPG be an alternative to ECG for acute stress detection in nonresting state?—Comprehensive evaluation using a dNN

How well can PPG be an alternative to ECG for acute stress d...

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International Conference on Affective Computing and Intelligent Interaction Workshops and demos (ACIIW)

作者： Yasuhide Hyodo Kiyoshi Yoshikawa Takanori Ishikawa Yota Komoriya Human Technology R&D Department Technology Development Laboratories Sony Corporation Tokyo Japan

Heart rate variability (HrV) analysis in a wristband photoplethysmography (PPG) device is gathering interest for emotion and stress recognition. However, motion artifacts are a critical issue, and comprehensive evaluation from HrV analysis to the model performance and interpretability should be conducted. In this study, we constructed a physiologically interpretable evaluation framework of HrV analysis and acute stress recognition using a deep neural network (dNN) in a wrist-worn PPG device compared with that in a chest-worn electrocardiography (ECG) device, considering motion artifacts, which are an important issue in wild environments. Furthermore, we developed model training and testing methods using a dNN that takes signal quality into account to achieve both accuracy (robustness against motion artifacts) and model interpretability in acute stress recognition in the wrist-worn PPG device. The results suggest that the method we developed improved the acute stress recognition performance of the wrist-worn PPG device throughout our experiments (78.4% accuracy and 77.0% F1 score). In addition, it was observed that the method for the wrist-worn PPG device demonstrated comparable performance and interpretability to the reference method for the chest-worn ECG device.

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Negative data in data Sets for Machine Learning Training

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JOUrNAL OF OrGANIC CHEMISTrY 2023年第9期88卷 5239-5241页

作者： Maloney, Michael P. Coley, Connor W. Genheden, Samuel Carson, Nessa Helquist, Paul Norrby, Per-Ola Wiest, Olaf Department of Chemistry and Biochemistry University of Notre Dame Notre Dame Indiana 46556 United States Department of Chemical Engineering and Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 United States Molecular AI Discovery Sciences R&D AstraZeneca Gothenburg Pepparedsleden 1 SE-431 83 Mölndal Sweden Early Chemical Development Pharmaceutical Sciences R&D AstraZeneca Macclesfield SK10 2NA U.K. Data Science and Modelling Pharmaceutical Sciences R&D AstraZeneca Gothenburg Pepparedsleden 1 SE-431 83 Mölndal Sweden

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The Comparison Study of Board Level drop and Set Level drop Performance

The Comparison Study of Board Level Drop and Set Level Drop ...

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International Conference on (ICEPT) Electronic Packaging technology

作者： Guosong Zhang Minyan Wu Yunpeng Shang Yonghua Zhou Tingzuo Tan Packaging Technology Development Team Samsung Semiconductor(China)R&D CO. LTD Suzhou China

ISBN: (数字)9798350353808

ISBN: (纸本)9798350353815

The IC failures induced by accidental dropping event of modern handheld electronic devices such as mobile phones may result from various failure modes such as cracking of package(PKG), solder joint, etc. Generally, the board level drop test is normally adopted to evaluate the IC failure risk instead of the set level drop test considering cost and efficiency. recently, however, the chip crack/damage failure rate in board level drop is much lower than that of mobile set level free drop. In this paper, a comprehensive study was performed to investigate the dynamic response characteristics of drop test with a customized PCB board when subjected to board level drop test and set level free drop test. The board level drop test was carried out according to JEdEC standard using a drop test apparatus, and the set level free drop test was employed by using the free drop machine. Moreover, two Finite Element models with reference to board level drop and set level free fall drop tests were developed to simulate the actual drop test scenarios based on two simplified FEA methods (Input-G method and impact velocity method, respectively). The simulation data were compared with experimental outputs to identify the FE Models in terms of accuracy of the results extracted. The dynamic key parameters of typical locations in PCB were analyzed to characterize performance difference during two kinds of drops. The measured and simulated data of corresponding locations in set level drop are all larger than those of board level drop in terms of impact acceleration intensity and duration, the strain response and the simulated chip stress. Comparing with board level drop response, a greater acceleration impact would induce a greater strain response, subsequently, the stress subjecting to chip of IC package is greater during set level free drop. Thus, we can conclude that the impact effect of set level free drop is severer than that of board level drop from experiment and simulation results, this

关键词： Accelerometers Semiconductor device measurement Tensile stress Simulation Life estimation Position measurement Strain measurement

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design and Implementation of Network Simulator for High Level Naval Ship System

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IEEE Access 2025年 13卷 90612-90625页

作者： Jang, Min-Hui Kim, Hyeong-Jin Go, Young-Keun Choi, Nak-Jung Lee, Jae-Ho Yu, Jae-Hak Lee, Jae-Min Jun, Tae-Soo Kim, dong-Seong Kumoh National Institute of Technology Dept. of IT Convergence Eng Gumi Korea Republic of NSLab Inc Technology Research Institute Gumi Korea Republic of Agency For Defense Development Maritime Technology Research Institute Jinhae Korea Republic of Naval R&D Center Hanwha Systems Boulder Gumi Korea Republic of Kumoh National Institute of Technology Dept. of Computer SW Eng Gumi Korea Republic of

Operational naval ship systems rely on advanced sensors and equipment to detect targets and manage weapon control and engagement. However, their growing complexity, driven by technological advancements and the increasing integration of clients and servers, necessitates changes in system architecture and network structure. To address these challenges, this paper presents the design and implementation of NSNS (Network Performance Evaluation Simulator for Naval Ship Combat System), a specialized simulator for advancing research on naval ship system networks. The NSNS provides a robust environment for performance analysis by leveraging the unique characteristics of naval ship combat system nodes and network properties. Its reliability was validated through comparisons with real-world system measurements, demonstrating consistent trends and acceptable error rates. This research underscores the importance of dedicated simulation tools for validating new naval network architectures and enhancing network reliability and availability in wartime scenarios. © 2013 IEEE.

关键词： Ship simulators

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Numerical Simulation research on Transient Thermal-Fluid-Chemical Coupling of Abandoned Wellbore 29th

Numerical Simulation Research on Transient Thermal-Fluid-Che...

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29th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2023

作者： Jiang, Jiwei Chen, Zhixue Chen, Yang Li, Jun Chen, Xuefeng Li, Mingyin Li, Bo CNPC Engineering Technology R&D Company Limited Beijing102206 China Middle East Branch of China Petroleum Technology and Development Corporation Beijing100028 China China University of Petroleum-Beijing Beijing102249 China Beijing Petroleum Machinery Company Limited Beijing102206 China

ISBN: (纸本)9783031449468

In the process of plugging wellbore with balanced plugging mud, hydration reaction kinetics, heat transfer and fluid mechanics interact with each other during the cement plugging stage, forming a complex physical and chemical process, which has not been fully taken into account in the current mechanical model of abandoned wellbore. Based on this, firstly, considering the hydration of cement plug during solidification stage, a transient heat-fluid-chemical coupling model of the abandoned wellbore is established. Then, the implicit finite difference method is used to discretized solve the simultaneous equations, and the characteristics of temperature distribution, hydration law of cement plug and pressure distribution of the abandoned wellbore are analyzed. The results show that the temperature of deep cement plug is almost constant after reaching the peak value under the coupling effect of thermal-fluid-chemical interaction, the temperature of shallow cement plug decreased significantly (by about 8 ℃) and the middle cement plug was followed by a reduction of about 5 ℃. The porosity and pore pressure of deep cement plug decreased rapidly, followed by the middle cement plug, and the shallow cement plug was the slowest. The hydration degree, gel strength and chemical shrinkage rate of the deep cement plug increased rapidly, followed by the middle cement plug, and the shallow cement plug was relatively slow. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Hydration

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research on defect Identification Algorithm of Power Network Telesignaling and Telemetry data Based on dynamic programming 3

Research on Defect Identification Algorithm of Power Network...

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3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

作者： Huang, di Zhu, Chaoyue Qiu, Junliang Hu, Xixing Zheng, Weiyan Luo, Shaojie Zhejiang Dayou Industrial Co. Ltd. Hangzhou Science and Technology Development Branch R&d Department Hangzhou China Zhejiang Dayou Co. Ltd Marketing Department Hangzhou China

ISBN: (纸本)9798350318180

distribution networks manage numerous devices, however, their level of automation is relatively low, often resulting in false signals and relatively low data quality. Therefore, it has become extremely challenging to directly use telecontrol and telemeasurement data for defect identification. To address this issue, this paper proposes a defect identification algorithm for power grid telecontrol and telemeasurement data based on dynamic programming. Firstly, we employ data cleansing techniques to filter out erroneous data. Then, we introduce a dynamic density clustering-based method for detecting anomalies in power quality data, which can extract feature indicators of abnormal data and identify the defects in telecontrol and telemeasurement data. Next, we utilize the GrU-LightGBM network to identify defects in the telecontrol and telemeasurement data of the power grid. Finally, we compare this method with existing classification methods for defect identification in telecontrol and telemeasurement data through experiments. The experimental results demonstrate that our proposed method not only improves classification accuracy but also enhances generalization ability. © 2023 IEEE.

关键词： deep learning defect identification dynamic clustering dynamic programming

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Machine Learning-Based Predictive Modelling of Spot-Welding Process Parameters 6th

Machine Learning-Based Predictive Modelling of Spot-Welding ...

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6th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Burande, dinesh V. Kalita, Kanak Chohan, Jasgurpeet Singh Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi India Department of Mechanical Engineering University Centre for Research and Development Chandigarh University Mohali India

ISBN: (纸本)9783031362453

This research paper presents a comparative study of machine learning (ML) algorithms for the predictive modelling of spot-welding process parameters. The focus is on predicting the nugget diameter (Nd) and nugget height (NH) using four different ML algorithms (namely, linear regression, random forest regression, adaptive boosting regression, and support vector machine regression). An experimental dataset consisting of fifty data points is used in this study. Exploratory data analysis was carried out to investigate the effect of process parameters on the response variables. Performance evaluation metrics were employed to gauge the predictive accuracy of the ML models. The results indicate that the random forest regression demonstrates superior performance in predicting both Nd and NH compared to the other algorithms. This study can serve as a foundation for further research in optimizing the spot-welding process through machine learning techniques. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Forecasting

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BOE-ziSIM: A design-technology-Manufacturing Co-optimization Platform 7

BOE-ziSIM: A Design-Technology-Manufacturing Co-optimization...

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7th International Workshop on Advanced Patterning Solutions, IWAPS 2023

作者： Liu, Nan Zhang, Zhizhao Chen, Shantao dong, Lisong Wang, Hong Technology R&D Center Beijing Zhongxiangying Technology Co. Ltd Beijing China Panel Technology Development BOE Technology Group Co. Ltd. Beijing China Institute of Microelectronics of Chinese Academy of Science Beijing China Beijing Zhongxiangying Technology Co. Ltd Beijing China

ISBN: (纸本)9798350344547

Thin-film transistors (TFT) and organic light-emitting diodes (OLEd) for display applications involve new materials, structures and processes in the design and development phase, and these elements can have a significant impact on the performance of the TFT devices. The increasing need for personalized and diversified display productions brings two problems: 1. To achieve the desired performance indicators in fabrication processes, a large number of experiments are required to continuously optimize the process parameters, which not only increases economic and time costs but also limits the development speed of new productions. 2. The display production iterations are getting faster to meet the market requirement, in other words, the time left for yield improvement becomes shorter. A design-technology-Manufacturing Co-optimization platform called BOE-ziSIM is introduced in this paper, it was developed to solve the above mentioned problems, the experiment results show that the defects analysis time is reduced from hours to minutes, and the equipment adjustment time is reduced from days to minutes. © 2023 IEEE.

关键词： Thin film transistors

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Ongoing Evolution of drAM Scaling via Third dimension -Vertically Stacked drAM -

Ongoing Evolution of DRAM Scaling via Third Dimension -Verti...

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Symposium on VLSI technology

作者： J.W. Han S.H. Park M.Y. Jeong K.S. Lee K.N. Kim H.J. Kim J.C. Shin S.M. Park S.H. Shin S.W. Park J.H. Lee S.H. Kim B.C Kim M.H. Jung I.Y. Yoon H. Kim S.U. Jang K.J. Park Y.K. Kim I.G. Kim J.H Oh S.Y. Han B.S. Kim B.J. Kuh J.M. Park DRAM Technology Development Hwaseong Korea Next Generation Process Development Samsung R&D Center Hwaseong Korea

For the past decades, the density of drAM has been remarkably increased by making access transistors and capacitors smaller in size per unit area. However, shrinking devices far beyond the 10 nm process node increasingly poses process and reliability challenges. As Flash technology made a pivotal and successful innovation via 3d NANd, drAM technology may also adopt vertical stacking memory cells. Vertically stacked drAM (VS-drAM) continues to increase bit density on a die by increasing the number of layers along with reducing the size of the transistor. In this paper, the opportunities and challenges of VS-drAM are discussed.

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