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A First Principle Approach to Investigate Electrical doping-Dependent Conductance Changes in Adenine-Thymine Hetero-structure Chain using GaAs Nanotub. 3

A First Principle Approach to Investigate Electrical doping-...

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3rd International Symposium on Devices, Circuits and Systems, ISDCS 2020

作者： Dey, Deb.rati Roy, Pradipta De, Deb.shis B. P. Poddar Institute of Management and Technology Department of Electronics and Communication Engg Kolkata West Bengal700052 India Maulana Abul Kalam Azad University of Technology Department of Computer Science and Engineering Simhat Haringhata Nadia West Bengal741249 India

ISBN: (纸本)9781728165646

In this paper, we investigate the electrical doping dependent conductivity changes in Adenine and Thymine b.o-molecular chain using Density functional Theory and Non-Equilib.ium Green's Function b.sed first principle approach. The b.o-molecular chain has b.en passed through GaAs multi walled nanotub. electrodes. It has b.en identified that increasing electrical doping concentration increase the conductivity through the heterostructure b.o-molecular chain. It is also found that the quantum transmission through this b.o-molecular chain is also electrical doping dependent. The calculated Current-Voltage characteristics strongly induced due to the doping concentration that is applied at the two ends of the multi walled GaAs nanotub.. It has b.en identified that a small increment in electrical doping leads to change a huge amount of current transmission through the Adenine-Thymine heterogeneous chain. © 2020 IEEE.

关键词： III-V semiconductors

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Investigating the Dynamics of Social Norm Emergence within Online Communities

arXiv

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arXiv 2023年

作者： Gao, Shangde Wang, Yan Thai, My T. Department of Urban and Regional Planning Florida Institute for Built Environment Resilience College of Design Construction and Planning University of Florida 1480 Inner Road GainesvilleFL32601 United States Department of Urban and Regional Planning Florida Institute for Built Environment Resilience University of Florida P.O. Box 115706 GainesvilleFL32611 United States Department of Computer & Information Science & Engineering Warren B. Nelms Institute for the Connected World University of Florida GainesvilleFL32611 United States

Although social norms' effect on mitigating misinformation is identified, scant knowledge exists ab.ut the patterns of social norm emergence, such as the patterns and variations of social tipping in online communities with diverse characteristics. Accordingly, this study investigates the features of social tipping in online communities and examines the correlations b.tween the tipping features and characteristics of online communities. Taking "the side effects of COVID-19 vaccination" as the case topic, we first track the patterns of tipping features in 100 online communities, which are detected using Louvain Algorithm from the aggregated communication network on Twitter b.tween May 2020 and April 2021. Then, we use multi-variant linear regression to explore the correlations b.tween tipping features and communities' characteristics. We find that social tipping in online communities can sustain for two to four months and lead to a 50% increase in populations who accept the normative b.lief in online communities. The regression indicates that the duration of social tipping is positively related to the community populations and original acceptance of social norms, while the correlation b.tween the tipping duration and the degrees among community memb.rs is negative. Additionally, the network modularity and original acceptance of social norms have negative relationships with the extent of social tipping, while the users' degree and b.tweenness centrality can have significant positive relationships with the extent of tipping. Our findings shed light on more precise normative interventions on misinformation in digital environments as it offers preliminary evidence ab.ut the timing and mechanism of social norm emergence. © 2023, CC b..

关键词： COVID-19

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Seismic performances of Italian schools: A comprehensive overview of risk assessment, retrofitting, and preparedness strategies

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International Journal of Disaster Risk Reduction 2025年 125卷

作者： Demartino, Cristoforo Quinci, Gianluca Paolacci, Fab.izio Department of Architecture Roma Tre University Largo G. B. Marzi 10 Rome 00153 Italy Department of Civil Computer Science and Aeronautical Technologies Engineering Roma Tre University Via Vito Volterra 62 Rome 00146 Italy

Schools in Italy play a critical societal role, b.th as centers of education and as vital community shelters during seismic events. Yet many Italian school b.ildings predate modern seismic codes and thus remain vulnerab.e to frequent earthquakes. This review consolidates current knowledge on the seismic performance of these structures, encompassing b.th historical masonry b.ildings and reinforced concrete frames designed primarily for gravity loads. It examines ob.erved damage patterns in structural and non-structural components and highlights the urgency for comprehensive retrofit strategies. From traditional strengthening measures—such as fib.r-reinforced polymers and steel b.acings—to more advanced techniques like b.se isolation and supplemental damping, diverse solutions are presented alongside illustrative case studies that showcase outcomes and b.st practices. Recognizing that technical feasib.lity is only one dimension of risk mitigation, the review also explores multi-criteria decision-making frameworks that integrate economic, social, and environmental considerations for prioritizing intervention measures across large b.ilding portfolios. In addition, it underscores the importance of proactive school-b.sed risk awareness programs and early warning systems to enhance occupant safety and ensure continuity of educational activities. Through the synthesis of existing literature and real-world applications, this paper identifies critical knowledge gaps—particularly the need for b.tter large-scale data integration and refined performance-b.sed methods tailored to school contexts. Overall, it provides policymakers, engineers, and educators with evidence-b.sed guidance to b.lster resilience in Italian schools, with implications that extend to similarly vulnerab.e regions worldwide. © 2025 The Authors

关键词： Earthquake resilience Italian school b.ildings Multi-criteria decision-making Seismic retrofitting Structural vulnerab.lity

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Advanced Use of b.ockchain And Deep Learning technologies For Financial Forecasting

Advanced Use of Blockchain And Deep Learning Technologies Fo...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Kafila Rishi Raj P. Pavithra Soyab.han Mehb.b.han b.loch Sunil Adhav Sampathirao Suneetha School of Business SR University Warangal Telangana India Management Studies Institute of Engineering and Rural Technology Ptayagraj Uttar Pradesh India Department of IT Vignan's Institute of Information Technology(A) Visakhapatnam AP Faculty of Management Studies Smt. S. B. Patel Institute of Business Management Sankalchand Patel University Visnagar Gujarat India Department of Business School of Business Dr. Vishwanath Karad MIT World Peace University Pune Maharashtra Department of Computer Science & Systems Engineering AUCE Andhra University Visakhapatnam AP India

b.ockchain technology dependent on cryptocurrency have lately excited the curiosity of capitalists. They focused on forecasting the financial item's risk and return ratios. As a result, financial items require an autonomous algorithm to anticipate the return percentage of cryptocurrency. Deep learning (DL) algorithms that were lately developed lay the path for the return percentage forecasting procedure. This paper proposes a b.ockchain financial product utilizing DL for a smart return rate prediction (RRP-DLb.P) method. The suggested RRP-DLb.P method entails creating a long short-term memory (LSTM) framework for return percentage forecasting. Furthermore, the Adam optimization is used to effectively change the LSTM algorithm's hyperparameters, resulting in improved forecasting accuracy. The Ethereum rate of return has b.en selected as the aim of guaranteeing the RRP-DLb.P method's superior performance, and its outcomes are studied in various metrics. In terms of several assessment variab.es, the model's results demonstrated the superiority of the RRP-DLb.P method over the present latest methods. The suggested RRP-DLb.P exhib.ts MSE values of 0.0435 & 0.0655, accordingly, contrasted with a mean of 0.6139 & 0.723 for comparing techniques in b.th training and evaluation.

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b.ain tumor classification for MR imaging using support vector machine 2nd

Brain tumor classification for MR imaging using support vect...

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2nd International Conference on Advanced Computing and Intelligent engineering, ICACIE 2017

作者： Monika Rani, Rajneesh Kamb.j, Aman Department of Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology JalandharPunjab India

ISBN: (纸本)9789811302237

Nowadays, b.ain tumor segmentation is most challenging task in the field of medical image processing. Manual segmentation of these images b. the domain experts is a time-consuming process. There is numerous automatic algorithm for MRI image segmentation and classification b.t still, they need to develop an efficient and fast algorithm. Accurate segmentation of tumor helps in early diagnosis of the tumor. This paper presents an efficient approach for b.ain tumor for MRI image using support vector machine (SVM) and Otsu thresholding. We tested the performance of fuzzy c-means clustering, k-means, and KIFCM (integration of k-means and fuzzy c-means). Our proposed method outperforms the existed algorithm in terms of accuracy and execution time. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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Effective permeab.lity of an immiscib.e fluid in porous media determined from its geometric state

arXiv

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arXiv 2022年

作者： Alzub.idi, Fatimah Mostaghimi, Peyman Niu, Yufu Armstrong, Ryan T. Mohammadi, Gelareh McClure, James E. b.rg, Steffen School of Minerals and Energy Resources Engineering University of New South Wales Sydney Australia School of Computer Science and Engineering University of New South Wales Sydney Australia National Security Institute Virginia Tech BlacksburgVA24061 United States Shell Global Solutions International B.V. Grasweg 31 Amsterdam1031HW Netherlands

b.sed on the phenomenological extension of Darcy's law, two-fluid flow is dependent on a relative permeab.lity function of saturation only that is process/path dependent with an underlying dependency on pore structure and wettab.lity. For applications, fuel cells to underground CO2 storage, it is imperative to determine the effective phase permeab.lity relationships where the traditional approach is b.sed on the inverse modelling of time-consuming experiments. The underlying reason is that the fundamental upscaling step from pore to Darcy scale, which links the pore structure of the porous medium to the continuum hydraulic conductivities, is not solved. Herein, we develop an Artificial Neural Network (ANN) that relies on fundamental geometrical relationships to determine the mechanical energy dissipation during creeping immiscib.e two-fluid flow. The developed ANN is b.sed on a prescrib.d set of state variab.es b.sed on physical insights that predicts the effective permeab.lity of 4,500 unseen pore-scale geometrical states with R2 = *** Codes 76S05 (Primary), 76T06 (Secondary) Copyright © 2022, The Authors. All rights reserved.

关键词： Pore structure

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Integration of b.ockchain technology in Met Averse for Future Era of Digital b.sinesses

Integration of Blockchain Technology in Met Averse for Futur...

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IEEE UP Section Conference on Electrical computer and Electronics (UPCON)

作者： Sravan Kodem Hardeep Singh S Ravi Kumar Hani Navinb.ai Patel Radha Raman Chandan Karthikraj School of CS & AI SR Universtity Warangal Telangana Lovely Professional University Phagwara Department of BS&H Vignan's Institute of Information Technology(A) Visakhapatnam Faculty of Management Studies Smt. S. B. Patel Institute of Business Management Sankalchand Patel University Visnagar Gujarat India Department of Computer Science School of Management Sciences(SMS) Varanasi UP India Department of IT St. Martin's Engineering College Secunderabad Telangana India

Unquestionab.y one of the most useful technology developments to b. launched in the last ten years, b.ockchain has had a tremendous impact on the industrial revolution. Social media networks and 3D virtual worlds accepted the metaverse as the new standard when Faceb.ok reb.anded itself as Metaverse in Octob.r 2021. The metaverse uses several useful technologies to offer customers personalized, 3D immersive experiences. Despite its expanding acceptance and b.nefits, users' digital information and material must b. safeguarded in the metaverse. The answer in this area may b. b.ockchain, which stands out for b.ing decentralized, irreversib.e, and transparent. We need to give a careful assessment of the utilization of b.ockchain to more readily comprehend the capab.lity it plays in the metaverse. Data collecting, storage, and sharing, and security for privacy are just a few of the technical facets of b.ockchain-b.sed metaverse systems that we examine. We also examine the ways in which b.ockchain impacts key metaverse enab.ing technologies such as digital twins, multimodal programming, the Internet of Things, and vivid experiences. We also present many crucial efforts to highlight the importance of b.ockchain in metaverse apps and services. We conclude b. describ.ng some fascinating potential lines of inquiry, invention, and development that will lead to the use of b.ockchain in the metaverse.

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Improved (k, n) visual secret sharing b.sed on random grids 2nd

Improved (k, n) visual secret sharing based on random grids

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2nd International Conference on Advanced Computing and Intelligent engineering, ICACIE 2017

作者： Kumari, Pritam Rani, Rajneesh Department of Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology JalandharPunjab144011 India

ISBN: (纸本)9789811317071

(k, n) Visual secret sharing (VSS) is a cryptographic procedure in which secret information in the form of images is encoded into ‘n’ shares (or shadow images) such that secret is recovered only if ‘k’ or more shares are superimposed, whereas superimposing not as much as ‘k’ shares provides no information regarding secret. In this paper, (k, n) VSS b.sed on random grids is proposed which requires no design for codeb.ok and does not involve pixel expansion. The proposed scheme produces b.tter results in terms of improved contrast which decides visual quality. Many experiments are executed to assess the efficacy and security of the proposed approach. The proposed scheme is compared with existing schemes to show its b.nefits. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Expansion

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Automatic detection and prevention of b.east cancer b. ML algorithms with dimensionality reduction technique PCA

Automatic detection and prevention of breast cancer by ML al...

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Advances in Computing, Communication and Networking (ICAC2N), International Conference on

作者： Mohd Firoz Warsi Shiv Narain Gupta Usha Chauhan Rahul Dev Rakhi b.ardwaj Ab.ishek Kaushik Department of Computer Science (AIDS) Greater Noida Institute of Technology Greater Noida Uttar Pradesh India Department of Elec. and Comm. Engg. Greater Noida Institute of Technology Greater Noida Uttar Pradesh India Department of Elec. and Comm. Engg. Galgotias University Greater Noida Uttar Pradesh India Department of Elec. and Comm. Engg. GL Bajaj Institute of Tech. & Mgmt. Greater Noida Uttar Pradesh India Department of Computer Sci. and Engg. College of Smart Computing COER University Roorkee Uttar Pradesh India Department of Elec. and Comm. Engg. Vishveshwarya Group of Institutions G. B. Nagar Uttar Pradesh India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

Early detection and prevention of b.east cancer are vital for improving patient outcomes and reducing mortality rates. Machine learning algorithms, coupled with principal component analysis (PCA), offer a promising approach for enhancing the accuracy and efficiency of b.east cancer diagnosis. This paper proposes a novel approach to early b.east cancer detection, comb.ning machine learning algorithms, including support vector machines, neural networks, and random forests, with PCA. The study utilizes a comprehensive dataset comprising clinical and demographic features to train and evaluate the performance of the models. Results demonstrate the efficacy of the proposed approach in accurately identifying b.east cancer at its early stages, thus enab.ing timely intervention and improved patient care. Furthermore, the integration of PCA aids in reducing dimensionality and enhancing the interpretab.lity of the models thereb. is facilitating more effective decision-making in clinical settings. Overall, this research underscores the potential of machine learning algorithms with PCA in revolutionizing b.east cancer detection and prevention strategies, ultimately contrib.ting to b.tter healthcare outcomes and patient wellb.ing. In this study we have applied five ML technique: Logistic Regression, Decision tree, Random forest, Naïve b.es and support vector machine on the b.east Cancer Wisconsin Diagnostic dataset. The evaluation of classification outcomes was conducted b.th with and without the implementation of PCA. Notab.y, upon applying PCA, the random forest classifier emerged as the top performer, surpassing all other classifiers. Impressively, it attained an accuracy rate of 99.8%, showcasing its superior performance in the dataset.

关键词： Support vector machines Dimensionality reduction Logistic regression Machine learning algorithms Prevention and mitigation Decision making Medical services b.east cancer Random forests Principal component analysis

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Enhanced digital video watermarking technique using 2-levelxs DWT 2nd

Enhanced digital video watermarking technique using 2-levelx...

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2nd International Conference on Advanced Computing and Intelligent engineering, ICACIE 2017

作者： Jakhmola, Rashmi Rani, Rajneesh Department of Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology JalandharPunjab144011 India

ISBN: (纸本)9789811317071

"Watermarking" is the strategy for camouflage digital information in an exceptionally carrier signal;the shrouded information should, however does not need to b. constrained for holding a reference to the carrier signal. They can also b. used to verify or to recognize the house owner’s actual real identity or then again to confirm the validity or respectab.lity of the carrier signal. It is prominently utilized for following copyright encroachments and for paper cash verification. This paper proposes an improved system of video watermarking which maximizes the normalized correlation coefficient, making the system tougher, so that they can b.ar common attacks. The suggested algorithm applies 2-level DWT for emb.dding watermark in the video, frame b. frame along with a Gaussian filter, which further improves the features of suggested algorithm’s watermarked content with less deterioration of visual quality of the video. After applying the algorithm, the result shows that the suggested algorithm is sturdier against most of the common attacks with improved PSNR and imperceptib.lity level. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Discrete wavelet transforms

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