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Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases

International Journal of Mining science and technology 2023年第1期33卷 47-59页

作者： Guangjin Wang Bing Zhao Bisheng Wu Chao Zhang Wenlian Liu Faculty of Land Resources Engineering Kunming University of Science and TechnologyKunming 650093China Yunnan International Technology Transfer Center for Mineral Resources Development and Solid Waste Resource Utilization Kunming 650093China State Key Laboratory of Hydroscience and Engineering Department of Hydraulic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan 430071China China Nonferrous Metals Industry Kunming Survey and Design Research Institute Co.Ltd Kunming 650051China

Slope stability prediction research is a complex non-linear system *** carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data *** on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope *** indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and *** data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross ***,the significance of each indicator in the prediction of slope stability is discussed using the coefficient of variation *** research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope *** forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least *** and SVM models have the best accuracy and superiority in slope stability *** results provide a new approach toward slope stability prediction in geotechnical engineering.

关键词： Slope stability prediction Machine learning algorithm Dimensionality reduction visualization Random cross validation Coefficient of variation

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Composites for electric vehicles and automotive sector: A review

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Green Energy and Intelligent Transportation 2023年第1期2卷 86-108页

作者： Adil Wazeer Apurba Das Chamil Abeykoon Arijit Sinha Amit Karmakar School of Laser Science and Technology Jadavpur UniversityKolkata 700032West BengalIndia Design Head-Freight Titagarh Wagons Limited756 AnandapurKolkata 700107India North West Composites Centre and Aerospace Research Institute Department of MaterialsFaculty of Science and EngineeringUniversity of ManchesterManchesterM139PLUK Department of Metallurgical Engineering Kazi Nazrul UniversityAsansol 713340West BengalIndia Department of Mechanical Engineering Jadavpur UniversityKolkata 700032West BengalIndia

The automotive sector is undergoing a significant transformation to address critical challenges affecting consumers and the *** of the most difficult tasks is reducing the weight of vehicles in order to minimize energy consumption.A ten percent decrease in curb weight is predicted to result in a six to eight percent reduction in energy *** materials having better strength to weight ratio are one of the finest options for planning,designing and manufacturing of the lightweight *** automobile sector,employment of composite materials would reduce the weight of electric vehicles as well as influence their aerodynamic prop***,it would decrease the consumption of fuel as well by cutting down harmful emissions and particulate *** developments in such technologies are studied over the last decade by automobile establishments and academic ***-reinforced polymers,particularly those established on glass and carbon fibers,have attracted attention of the automobile sector due to their high performance and lesser *** paper reviews the applications of various types of composite materials and the fabrication techniques of such composites in electric vehicles and ***,a comprehensive data breakdown of the lightweight materials statistics and figures on market analysis of high performance composite is ***,a discussion is made on the different applications of these ***,the details presented in this study should be useful for automobile companies to align with NET ZERO global mission while sustaining their businesses.

关键词： Composites Electric vehicles Fabrication techniques Hybrid vehicles

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Development and modeling of advanced systems Na2SnBr6-based perovskite solar cells: a comprehensive study on electron transport layers

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Optics Express 2025年第10期33卷 21152-21172页

作者： Roy, Dipta Reza, M.D. Selim Ghosh, Avijit Roy, Anup Kumar Chowdhury, Bivash Ranjan Aktarujjaman, M.D. Alrafai, H.A. Hassan, Abeer A. Department of Electrical and Computer Engineering California State University at Northridge NorthridgeCA91330 United States Department of Electrical and Electronic Engineering Begum Rokeya University Rangpur5400 Bangladesh Phillip M. Drayer Department of Electrical and Computer Engineering Lamar University BeaumontTX77710 United States Department of Management Information System International American University Los AngelesCA90010 United States Department of Information Technology Management Webster University St. LouisMO63119 United States Department of Chemistry Faculty of Science King Khalid University PO Box 9004 Abha61413 Saudi Arabia

This study simulates a n-i-p planar heterojunction for Na2SnBr6-based perovskite solar cells (PSCs), with Na2SnBr6 as the absorber layer, fluorine-doped tin oxide (FTO) as the substrate, and In2S3, IGZO, and SnS2 as electron transport layers (ETLs). Gold (Au) is used as the back contact. Na2SnBr6 was chosen for its low cost, non-toxicity, tunable band gap, excellent electrical properties, and stability. The SCAPS-1D simulator was employed to model the solar cell performance under AM 1.5 G light irradiation, focusing on factors like doping concentration, layer thickness, defect density, and interface defects across three device configurations: Device I (Au/Na2SnBr6/ In2S3/FTO/Al), Device II (Au/ Na2SnBr6/IGZO/FTO/Al), and Device III (Au/ Na2SnBr6/SnS2/FTO/Al). Device III achieved the highest PCE of 31.35%, FF of 85.95%, VOC of 0.7926 V, and JSC of 46.01 mA/cm22, making it a promising candidate for high-efficiency, lead-free perovskite solar cells. Devices I and II showed lower efficiencies of 27.47% and 30.98%, respectively. The study also analyzed quantum efficiency (QE), carrier dynamics, and recombination rates, highlighting the potential of Device III in advancing Na2SnBr6-based hybrid perovskite solar technologies for future solar energy applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Semiconductor doping

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A novel Cross-Layer Protocols for Resource Allocation in Mobile Networks 15

A novel Cross-Layer Protocols for Resource Allocation in Mob...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Giri, Rakesh Kumar Vittapu, Mani Sarma Dev, Anoop Shewale, Chaitali R. Majid, Mohd Aliff Abdul Kulkarni, Nandini Sunrise University Alwar Department of Computer Science and Engineering India Mallareddy Engineering College and Management Sciences Department of Computer Science and Engineering Kistapur Village Medchal Telangana Hyderabad India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura India Vishwakarma Institute of Technology Department of Information Technology Pune India University Teknology MARA Faculty of Hotel and Tourism Management Department of Foodservice Management Malaysia Symbiosis International University Department of Symbiosis School of Planning Architecture and Design Nagpur Nagpur India

ISBN: (纸本)9798350370249

Cross-layer Protocols for proper resource Allocation in Mobile Networks are a singular technique to enhance the efficiency of wireless networks. The method utilizes multiple layers of the radio protocol stack better to coordinate cell node scheduling and resource allocation. Using combining communication, routing, and scheduling functionalities in an unmarried protocol, pass-Layer Protocols for proper resource Allocation can offer a sizable will increase in the number of facts that may be transferred and the overall latency and throughput of the community. This technique can also enhance the radio interface's operation by lowering interference and encouraging collaborative communications. Eventually, by using facts and managing records from the communique and routing layers, go-Layer Protocols for proper resource Allocation can reduce the complexity of the community, even offering greater scalability. This paper affords unique cross-Layer Protocols for resource Allocation in Cellular Networks. The proposed protocol permits integrated resource allocation in the cell network environment, considering communication and computation layers. © 2024 IEEE.

关键词： Network layers

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Simple Method for Estimation of Stray Capacitance of Toroidal Inductors by Considering an Insulation between Winding and Core

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IEEJ Transactions on Industry Applications 2022年第1期142卷 33-40页

作者： Takahashi, Shotaro Wada, Keiji Department of Systems Design Engineering Faculty of Science and Technology Seikei University 3-3-1 Kichijoji Kitamachi Musashino Tokyo180-8633 Japan Graduate School of Systems Design Tokyo Metropolitan University 1-1 Minamiosawa Hachioji Tokyo192-0397 Japan

In this study, the authors propose a simple method for estimating stray capacitance of toroidal inductors. The proposed method calculates the total stray capacitance of a toroidal inductor based on the stray capacitance between the winding and the core, calculated by considering the insulation (plastic case and plastic molding) that contains the magnetic core. The frequency characteristics of the toroidal inductor can be calculated by substituting the calculated stray capacitance in the analytical model of the inductor, which takes into account the frequency dependence of the complex magnetic permeability of the magnetic material. In order to evaluate the proposed method, toroidal inductors were fabricated based on carbonyl iron dust, amorphous and nanocrystalline magnetic cores. Comparison between measured and calculated impedances clarify that the proposed method can calculate the stray capacitance of toroidal inductors with practical accuracy. 2022 The Institute of Electrical Engineers of Japan.

关键词： Magnetic cores

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Experimental analysis of chemical removal effect in RISA grinding of optical glass 7

Experimental analysis of chemical removal effect in RISA gri...

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7th CIRP Conference on Surface Integrity, CSI 2024

作者： Shimodo, Kodai Takamaru, Hinata Chiba, Yusuke Kato, Hidebumi Nagano, Mikinori Fukuta, Masahiko Tanaka, Katsutoshi Watanabe, Kentaro Hamazono, Kazuhisa Kakinuma, Yasuhiro Department of System Design Engineering Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan Production Headquarters Nikon Corp. 1-10-1 Asamizo-dai Minami-ku Sagamihara252-0328 Japan Nano processing System Division Shibaura Machine C0. Ltd. 2068-3 Ohoka Numazu410-0022 Japan

In the large-aperture lens manufacturing, not only high surface quality but also high productivity is required. From this perspective, Reaction-Induced-Slurry-Assisted grinding (RISA grinding), in which cerium oxide slurry is supplied instead of using general grinding fluid, has been developed to achieve high surface quality at high removal rate. However, the surface profile error becomes large due to chemical removal effect of the cerium oxide slurry. Therefore, the purpose of this study is to experimentally investigate the influence of the chemical removal effect on the surface profile error using AE signals and servo current signals in RISA grinding. First, relation between dwell time and removal depth is analyzed by conducting a basic grinding test without the workpiece rotation. The result shows that the actual removal depth increases with increase of dwell time despite applying the constant depth of cut. Then, zero-cut RISA grinding test is conducted. It is found that the removal process proceeds even though zero-cut grinding, and its removal rate varies according to the wheel feed rate. Furthermore, the amount of cerium oxide abrasives adhered to the grinding wheel can be estimated from the AE signals and servo current signals. © 2024 The Authors. Published by Elsevier B.V.

关键词： Grinding (machining)

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An Intelligent Thyroid Diagnosis system Utilizing Multiple Ensemble and Explainable Algorithms with Medical Supported Attributes

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2840-2855页

作者： Sutradhar, Ananda Al Rafi, Mustahsin Ghosh, Pronab Shamrat, F M Javed Mehedi Moniruzzaman, Md. Ahmed, Kawsar Azad, A.K.M. Bui, Francis M. Chen, Li Moni, Mohammad Ali Daffodil International University Department of Computer Science and Engineering Dhaka1216 Bangladesh Lakehead University Department of Computer Science Thunder BayONP7B 5E1 Canada University of Malaya Department of Computer System and Technology Kuala Lumpur50603 Malaysia Lakehead University Department of Software Engineering Thunder BayONP7B 5E1 Canada University of Saskatchewan Department of Electrical and Computer Engineering SaskatoonSK S7N 5A9 Canada Imam Mohammad Ibn Saud Islamic University Faculty of Science Department of Mathematics and Statistics Riyadh13318 Saudi Arabia Charles Stuart University AI and Cyber Futures Institute BathurstNSW2795 Australia

The widespread impact of thyroid disease and its diagnosis is a challenging task for healthcare experts. The conventional technique for predicting such a vital disease is complex and time-consuming. A data-driven approach may offer predictive solutions, but it relies on all relevant attributes, which are computationally expensive. Hence, we propose a novel machine learning (ML) based disease prediction system that could potentially predict it by considering three crucial steps. First, to reduce the dimension of the dataset, three feature selection techniques were employed, including feature importance (FIS), information gain selections (IGS), and least absolute shrinkage and selection operator (LAS). Moreover, recommended medical references were considered while developing a feature set having the identical attributes as high-risk factors (HRF). Second, the models, including the three stage hybrid classifier (3SHC) and the three stage hybrid artificial neural network (3SHANN), are used as classifiers on the training data set. Third, a local interpretable model-agnostic explanations (LIME) to the 3SHC with the HRF samples was applied to individually explain the predictions. Then, the overall behaviors of both gender and age categories were explored with the help of a partial dependence plot (PDP). Finally, the proposed system is validated with extensive experiments, where the 3SHC achieves an accuracy (ACC) of 99.29%, which can play a crucial role in preventing thyroid disease and alleviating stress in the healthcare sector. © 2020 IEEE.

关键词： Neural networks

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Automated User Experience (UX) Testing for Mobile Application: Strengths and Limitations

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2022年第4期16卷 30-45页

作者： Abuaddous, Hayfa. Y. Saleh, Ashraf Mousa Enaizan, Odai Ghabban, Fahad Al-Badareen, Anas Bassam Faculty of Computer Sciences and Informatics Amman Arab University Amman Jordan Department of Management Information System University of Tabuk Tabuk Saudi Arabia College of Computer Science and Engineering Taibah University Medina Saudi Arabia Department of Software Engineering Aqaba University of Technology Aqaba Jordan

User Experience (UX) evaluation has a significant importance for any interactive application. Mobile device applications have additional limitations to convey good user experiences (UX) due to the usage and features of mobile devices in ubiquitous computing contexts. There are a lot of automated tools available for evaluating, such applications particularly developed for Android and iOS. Automated UX evaluation provides a number of strengths which are able to overcome the limitations of non-automated (moderated) counterparts. Automated UX evaluation is regarded as unexplored field, especially when it is adopted for the UX evaluation of complex mobile application. Despite these, automated UX evaluation tools are unexplored and should only be used in coupling with traditional UX evaluation techniques. Hence, this study aims to discuss the literature in automated UX evaluation and to highlight the UX measurements that merit further investigation. This paper presents the most fre-quently used automated UX evaluation tools for mobile applications. Therefore, the study analyzes existing automated UX tools and frameworks and identifies which UX attributes and measurements of automated UX evaluation are likely to be of use in future research. Moreover, we discuss the strengths and limitations of automated UX evaluation methods for mobile applications. Finally, the paper provides an overview of automated UX evaluation techniques and tools. It also presents the strengths and limitations for comparing various evaluation methods. © 2022,International Journal of Interactive Mobile Technologies. All Rights Reserved.

关键词： Automation

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Decision support system for truck scheduling in logistic network through cross-docking strategy 2

Decision support system for truck scheduling in logistic net...

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2nd International Conference on sciences and technology Applications, ICOSTA 2020

作者： Nurprihatin, Filscha Elvina Rembulan, Glisina Dwinoor Christianto, Kevin Hartono, Henny Department of Industrial Engineering Faculty of Technology and Design Universitas Bunda Mulia Jakarta Indonesia Department of Informatics Engineering Faculty of Technology and Design Universitas Bunda Mulia Jakarta Indonesia Department of Information System Faculty of Technology and Design Universitas Bunda Mulia Jakarta Indonesia

In recent years, companies around the world need to find new ways to reduce costs, increase productivity, improve product quality, and meet various customer demands. Each Distribution Center (DC) or warehouse is specifically designed to minimize costs in the company's supply chain. Cross-docking is a logistics technique that eliminates storing and picking up items at warehouses. Cross-docking has several advantages compared to other product distribution strategies from both an economic and an environmental point of view. Cross-docking decisions are influenced by many factors such as the level of product demand, the cost of stock-outs, and the distance from suppliers to customers. This research builds a Decision Support system (DSS) that can help companies to ensure sustainability in the supply chain. This study assumes the demand is deterministic which is indicated by Economic Order Quantity (EOQ). This system can detect the time and quantity of certain items that experience cross-docks accurately. If the customers'demand cannot be fulfilled by the warehouse, then the goods are categorized as out of stock. By knowing the time and quantity of goods at the time of the cross-dock, the warehouse manager can make operational decisions quickly and accurately related to the resources such asoperators and forklifts. © Published under licence by IOP Publishing Ltd.

关键词： Warehouses

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