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Detection of cervical and adrenal cancer cells using a terahertz metamaterial absorber integrated with machine learning

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Optical and Quantum Electronics 2025年第6期57卷 1-15页

作者： Gorai, Abhik Ghosh, Prabir Sarathamani, T. Vagini, K Jayanthi Nunna, Prasanthi Kumari Roy, Bhaskar School of Electronics Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Department of Computer Science and Engineering-AI Brainware University Kolkata India Department of Computer Science with Data Analytics KPR College of Arts Science and Research Coimbatore India School of Computer Science UPES Dehradun India Department of Computer Science and Engineering(AIML) Asansol Engineering College Asansol India

A simple, compact terahertz metamaterial absorber, analyzed with machine learning, is presented for cervical and adrenal cancer detection. The metamaterial absorber, fabricated with an aluminum layer on a polyimide substrate, exhibits a high sensitivity to the subtle variations in refractive index (n) between cervical cancer cells (n = 1.393), normal cervical cells (n = 1.368), adrenal gland cancer cells (n = 1.395), and normal adrenal gland cells (n = 1.381). The absorber demonstrates four distinct absorption peaks of 99.4% at 0.82597 THz, 89% at 1.152 THz, 95% at 1.516 THz, and 99.5% at 1.91 THz, all occurring at a unity refractive index. At resonant frequencies of 0.82597 THz, 1.152 THz, 1.516 THz, and 1.91 THz, the quality factors are 30, 8, 7, and 37 respectively. Additionally, the sensitivities across the four operating bands are 955 GHz/ refractive index unit (RIU), 183 GHz/RIU, 278 GHz/RIU, and 956 GHz/RIU respectively. Moreover, a machine learning model is developed using extra tree classifier to detect the different cancer cells. In this technique a huge dataset was generated corresponding to features like different incidence angle, polarization angle and thickness of the analyte. The model has an accuracy of 97.04% on validation data.

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Corrosion inhibition of weldment by Nephelium lappaceum peel extract in 3.5% NaCl solution

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South African Journal of Chemical engineering 2022年 41卷 223-232页

作者： Gapsari, Femiana Setyarini, Putu H. Kurniawan, Fredy Ahnaf, Ahnaf Anwar, Moch.Syaiful Zuryati, Ulul Khairi Department of Mechanical Engineering Faculty of Engineering Brawijaya University MT Haryono 167 Malang 65145 Indonesia Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Arief Rahman Hakim Surabaya 60111 Indonesia Research Center for Metallurgy and Materials National Research and Innovation Agency Komplek Puspiptek Serpong Tangerang Selatan 15314 Indonesia Analytics Chemistry Laboratory Faculty of Mathematics and Natural Sciences Mataram University Majapahit 62 Mataram 83115 Indonesia

Nephelium lappaceum peel Extract (NPE) is effective to control carbon steel weldment corrosion in acidic *** study analyzes NPE performance (0 to 60 ppm) as corrosion inhibitor on weldment in 3.5% NaCl. Potentiodynamic polarization was used to investigate corrosion rate and inhibition performance. The results revealed that NPE has strong effect (83%) on heat affected zone (HAZ) and on base metal (BM) (62%) and on weld metal (WM) (71%). NPE acted as mixed type inhibitor on all weldment areas. On weldment areas, there was physisorption (WM and HAZ) following isothermal Langmuir, but on BM chemisorption might also happen. The results surface analysis, FTIR and UV Vis are in line, indicating that inhibition behavior happened due to the formation of adsorbed layer on the weldment surface. This study revealed that NPE had different performance in each region and solution temperature. © 2022 The Authors

关键词： Chemisorption Corrosion Inhibitor Physisorption

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Celebrity profiling through linguistic analysis of digital social networks

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Computational Social Networks 2021年第1期8卷 1-36页

作者： Moreno-Sandoval, Luis G. Pomares-Quimbaya, Alexandra Alvarado-Valencia, Jorge A. Center of Excellence and Appropriation in Big Data Analytics (CAOBA) Bogota Colombia Department of System Engineering Pontificia Universidad Javeriana Bogota Colombia Department of Industrial Engineering Pontificia Universidad Javeriana Bogota Colombia

Digital social networks have become an essential source of information because celebrities use them to share their opinions, ideas, thoughts, and feelings. This makes digital social networks one of the preferred means for celebrities to promote themselves and attract new followers. This paper proposes a model of feature selection for the classification of celebrities profiles based on their use of a digital social network Twitter. The model includes the analysis of lexical, syntactic, symbolic, participation, and complementary information features of the posts of celebrities to estimate, based on these, their demographic and influence characteristics. The classification with these new features has an F1-score of 0.65 in Fame, 0.88 in Gender, 0.37 in Birth year, and 0.57 in Occupation. With these new features, the average accuracy improve up to 0.14 more. As a result, extracted features from linguistic cues improved the performance of predictive models of Fame and Gender and facilitate explanations of the model results. Particularly, the use of the third person singular was highly predictive in the model of Fame. © 2021, The Author(s).

关键词： Author profile Celebrity profile Demographic features Influential feature Natural Language Processing

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A quinolinyl analog of resveratrol improves neuronal damage after ischemic stroke by promoting Parkin-mediated mitophagy

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Chinese Journal of Natural Medicines 2025年第2期23卷 214-224页

作者： Qingqi Meng Yan Mi Libin Xu Yeshu Liu Dong Liang Yongping Wang Yan Wang Yueyang Liu Guoliang Chen Yue Hou Key Laboratory of Bioresource Research and Development of Liaoning Province College of Life and Health SciencesNational Frontiers Science Center for Industrial Intelligence and Systems OptimizationKey Laboratory of Data Analytics and Optimization for Smart IndustryMinistry of EducationNortheastern UniversityShenyang 110167China State Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources School of Chemistry and Pharmaceutical SciencesGuangxi Normal UniversityGuilin 541004China Shenyang Key Laboratory of Vascular Biology Science and Research CenterDepartment of PharmacologyShenyang Medical CollegeShenyang 110034China Key Laboratory of Structure-Based Drug Design&Discovery of Ministry of Education School of Pharmaceutical EngineeringShenyang Pharmaceutical UniversityShenyang 110016China

Ischemic stroke(IS)is a prevalent neurological disorder often resulting in significant disability or ***,extracted from Polygonum cuspidatum *** Zucc.(commonly known as Japanese knotweed),has been recognized for its potent neuroprotective ***,the neuroprotective efficacy of its derivative,(E)-4-(3,5-dimethoxystyryl)quinoline(RV02),against ischemic stroke remains inadequately *** study aimed to evaluate the protective effects of RV02 on neuronal ischemia-reperfusion injury both in vitro and in *** research utilized an animal model of middle cerebral artery occlusion/reperfusion and SH-SY5Y cells subjected to oxygen-glucose deprivation and reperfusion to simulate ischemic *** findings demonstrate that RV02 attenuates neuronal mitochondrial damage and scavenges reactive oxygen species(ROS)through mitophagy ***,Parkin knockdown was found to abolish RV02's ability to activate mitophagy and neuroprotection in *** results suggest that RV02 shows promise as a neuroprotective agent,with the activation of Parkin-mediated mitophagy potentially serving as the primary mechanism underlying its neuroprotective effects.

关键词： (E)-4-(3 5-dimethoxystyryl)quinoline Resveratrol Ischemic stroke Mitophagy Parkin

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ANN-based methods for solving partial differential equations: a survey

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Arab Journal of Basic and Applied Sciences 2022年第1期29卷 233-248页

作者： Pratama, Danang A. Bakar, Maharani A. Ismail, N.B. Mashuri, M. Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Terengganu Malaysia Special Interest Group Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Terengganu Malaysia Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Jenderal Soedirman Purowkerto Indonesia

Traditionally, partial differential equation (PDE) problems are solved numerically through a discretization process. Iterative methods are then used to determine the algebraic system generated by this process. Recently, scientists have emerged artificial neural networks (ANNs), which solve PDE problems without a discretization process. Therefore, in view of the interest in developing ANN in solving PDEs, scientists investigated the variations of ANN which perform better than the classical discretization approaches. In this study, we discussed three methods for solving PDEs effectively, namely Pydens, NeuroDiffEq and Nangs methods. Pydens is the modified Deep Galerkin method (DGM) on the part of the approximate functions of PDEs. Then, NeuroDiffEq is the ANN model based on the trial analytical solution (TAS). Lastly, Nangs is the ANN-based method which uses the grid points for the training data. We compared the numerical results by solving the PDEs in terms of the accuracy and efficiency of the three methods. The results showed that NeuroDiffeq and Nangs have better performance in solving high-dimensional PDEs than the Pydens, while Pydens is only suitable for low-dimensional problems. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the University of Bahrain.

关键词： 68-XX 68W25 Artificial neural networks discretization Nangs module Neuroiffeq method partial differential equations Pydens method

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Incentivized Federated Learning and Unlearning

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IEEE Transactions on Mobile Computing 2025年

作者： Ding, Ningning Sun, Zhenyu Wei, Ermin Berry, Randall Data Science and Analytics Thrust Internet of Things Thrust Information Hub Guangzhou511453 China Northwestern University Department of Electrical and Computer Engineering EvanstonIL60208 United States Northwestern University Electrical and Computer Engineering Department Industrial Engineering and Management Sciences Department EvanstonIL60208 United States

To protect users' right to be forgotten in federated learning, federated unlearning aims at eliminating the impact of leaving users' data on the global learned model. The current research in federated unlearning mainly concentrates on developing effective and efficient unlearning techniques. However, the issue of incentivizing valuable users to remain engaged and preventing their data from being unlearned is still under-explored, yet important to the unlearned model performance. This paper focuses on the incentive issue and develops an incentive mechanism for federated learning and unlearning. We first characterize the leaving users' impact on the global model accuracy and the required communication rounds for unlearning. Building on these results, we propose a four-stage game to capture the interaction and information updates during the learning and unlearning process. A key contribution is to summarize users' multi-dimensional private information into one-dimensional metrics to guide the incentive design. Interestingly, we prove that allowing federated unlearning can result in reduced payoffs for both the server and users, compared to a scenario without unlearning. Numerical results demonstrate the necessity of unlearning incentives for retaining valuable leaving users, and also show that our proposed mechanisms decrease the server's cost by up to 53.91% compared to state-of-the-art benchmarks. © 2002-2012 IEEE.

关键词： federated learning federated unlearning incentive mechanism

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A Decision-Dependent Chance-Constrained Planning Model for Distribution Networks Under Extreme Weather Events

A Decision-Dependent Chance-Constrained Planning Model for D...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Zhou, Anping Sun, Hongbo Kitamura, Shoichi Nikovski, Daniel Dept. of Electrical and Computer Engineering Southern Methodist University DallasTX75205 United States Data Analytics Group Mitsubishi Electric Research Laboratories CambridgeMA02139 United States Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki661-8661 Japan

ISBN: (纸本)9798350396782

Extreme weather events have posed tremendous challenges to the operation of distribution networks. In this paper, we propose a decision-dependent chance-constrained model for the optimal planning of diesel generators, renewable distributed generations (RDGs), energy storage systems, and switches under contingency. A promising moment-based ambiguity set that incorporates the information of decision variables is employed to depict the uncertainty arising from RDGs. By leveraging effective approximation methods such as the Bonferroni approximation method to handle the considered joint chance constraints, the proposed model is transformed into a tractable mixed-integer second-order conic programming problem, which means it can easily be implemented. Numerical experiments are put forward on the IEEE 33-bus test system to validate the effectiveness of the developed approach. © 2023 IEEE.

关键词： Chance constraint contingency distribution network distributionally robust optimization renewable energy

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A Novel Framework for the Development of Quality-Aware Autonomic IoT Applications 2

A Novel Framework for the Development of Quality-Aware Auton...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Bisht, Ankur Singh Manjunatha, R. Karnik, M.P. Amudha, A. Raj, Nimesh Shalini, M. Graphic Era Hill University Bhimtal India Graphic Era Deemed to be University Uttarakhand Dehradun248002 India School of Sciences Data Analytics and Mathematical Sciences Karnataka Bangalore India Vishwakarma Institute of Technology Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India

ISBN: (纸本)9798350388916

A tremendous quantity of data is being generated via the Internet of Things (IoT). While our knowledge of how to assess the quality of this data at the network and device levels is expanding, there are still significant obstacles to overcome when it comes to interpreting and assessing the quality at the informational and application levels. If you want to know what aspects impact the overall system quality, this post will go over some of the problems with IoT systems and how to fix them at various OSI levels. Using two digital health apps made possible by the internet of things (IoT), the authors look at how semantics may be used to measure the system's data quality and how to integrate multimodal information to clinical decision support. Important data quality issues arise from the fact that the Internet of Things (IoT) ecosystem generates massive amounts of data collected from a variety of heterogeneous sources. The reason for this is that the whole operation of the internet of things system is badly affected by low data quality standards. data quality has been the subject of much research outside of the Internet of Things (IoT) domain, and the idea is backed by massive standardization efforts. However, data quality management inside the IoT has received little attention. An essential idea with many existing applications for issue solving, data quality (DQ) is used in the creation and execution of information, handling data, decision making, as well as engineering systems. But the ways DQ is now integrated into data management pipelines aren't flexible enough to accommodate all kinds of uses, which limits its use in the IoT space. A generic framework is introduced in this research that allows for the implementation of DQ assessment in a wide range of Internet of Things applications. A knowledge graph serves as the foundation of the framework, making it easy to incorporate into new uses. The study's findings highlight many gaps in the current state of IoT quality a

关键词： data quality

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Image Processing: Unlocking the Secrets of Visual Information 2

Image Processing: Unlocking the Secrets of Visual Informatio...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Lavanya, D. Bhushan, Kavi Kant, Gur Sharan Sountharraj, A.C. Srivastav, Akanksha Begum, M. Sharmila Sri Venkateswara College of Engineering Computer Science and Engineering Department Andhra Pradesh Tirupati India Ccs University Sir Chhotu Ram Institute of Engg. & Technology Department of Computer Science U.P Meerut India Dr. Ngp Art's and Science College Department of Computer Science with Data Analytics Coimbatore-48 India Tula's Institute Department of Computer Science and Engineering Dehradun India Maharaja Institute of Technology Department of Computer Science Mysore India

ISBN: (纸本)9798350384277

In the age of image processing, the hidden ability can be encoded with visual information that is not only observed but also painstakingly carried out;in this way, the complex secrets that are encoded in each pixel have been made clear. Image processing is the magic that has increased the amount of clarity, significance, and utility while transforming stationary arrays of images into dynamic narratives. The image's quality is typically influenced by several variables, such as temperature, light, and noise. Due to its persistent presence in various digital photographs, noise plays a crucial function in the image. Throughout the image coding, transmission, and development procedure, noise consequences could arise. The field of noise removal in image processing has grown to be quite interesting and vibrant. Recently, there has been a notable advancement regarding the filtering of various noise types for image processing in digital format. This research paper aims to discuss image processing and denoising various noises in images to improve overall quality. In terms of methodology systematic qualitative research has been conducted that helps the research gather information from a wide range of sources. Moreover, this paper finds that image processing has significant potential in this digital age. By denoising images, this phenomenon can be applied in different applications in every sector. © 2024 IEEE.

关键词： Image denoising

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A Review and Bibliometric Analysis of the Current Studies for the 6G Networks

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Computer Modeling in engineering & Sciences 2024年第9期140卷 2165-2206页

作者： Qusay M.Salih Md.Arafatur Rahman Ahmad Firdaus Mohammed Rajih Jassim Hasan Kahtan Jasni Mohamad Zain Ahmed Hussein Ali Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)PekanPahang26600Malaysia Department of Medical Equipment Technology Engineering Al Salam University CollegeBaghdadIraq School of Mathematics and Computer Science University of WolverhamptonWolverhampton01902UK Department of Production Engineering and Metallurgy University of TechnologyBaghdadIraq Cardiff School of Technologies Cardiff Metropolitan UniversityCardiffCF52YBUK Institute for Big Data Analytics and Artificial Intelligence(IBDAAI) Kompleks Al-KhawarizmiUniversiti Teknologi MARAShah AlamSelangor40450Malaysia Department Computer Science Al-Salam University CollegeBaghdadIraq

The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already *** realize its full potential over the next decade,6G will undoubtedly necessitate additional improvements that integrate existing solutions with cutting-edge ***,the studies about 6G are mainly limited and scattered,whereas no bibliometric study covers the 6G ***,this study aims to review,examine,and summarize existing studies and research activities in *** study has examined the Scopus database through a bibliometric analysis of more than 1,000 papers published between 2017 and ***,we applied the bibliometric analysis methods by including(1)document type,(2)subject area,(3)author,and(4)country of *** study’s results reflect the research 6G community’s trends,highlight important research challenges,and elucidate potential directions for future research in this interesting area.

关键词： 6G bibliometric wireless networks review

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