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An efficient and resilience linear prefix approach for mining maximal frequent itemset using clustering

Journal of Safety science and Resilience 2025年第1期6卷 93-104页

作者： M.Sinthuja S.Pravinthraja B K Dhanalakshmi H L Gururaj Vinayakumar Ravi G Jyothish Lal Department of ISE M.S.Ramaiah Institute of Technology BengaluruVisvesvaraya Technological UniversityBelagaviKarnataka590018India Department of CSE Presidency UniversityBengaluruIndia Department of Computer Science and Engineering BMS institute of Technology&ManagementBengaluruVisvesvaraya Technological UniversityBelagaviKarnataka590018India Department of Information Technology Manipal Institute of Technology BengaluruManipal Academy of Higher EducationManipalIndia Center for Artificial Intelligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia Center for Computational Engineering and Networking(CEN) Amrita School of EngineeringAmrita Vishwa VidyapeethamCoimbatoreIndia

The numerous volumes of data generated every day necessitate the deployment of new technologies capable of dealing with massive amounts of data *** is the case with Association Rules,a tool for unsupervised data mining that extracts information in the form of IF-THEN *** various approaches for extracting frequent itemset(prior step before mining association rules)in extremely large databases have been presented,the high computational cost and shortage of memory remain key issues to be addressed while processing enormous *** objective of this research is to discover frequent itemset by using clustering for preprocessing and adopting the linear prefix tree algorithm for mining the maximal frequent *** performance of the proposed CL-LP-MAX-tree was evaluated by comparing it with the existing FP-max *** was performed with the three different standard datasets to record evidence to prove that the proposed CL-LP-MAX-tree algorithm outperform the existing FP-max algorithm in terms of runtime and memory consumption.

关键词： Clustering Data mining Frequent itemset mining Linear prefix tree Maximal frequent itemset mining

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Deepfakes: A Review on technologies, Applications and Strategies

Deepfakes: A Review on Technologies, Applications and Strate...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Kaswan, Kuldeep Singh Malik, Kiran Dhatterwal, Jagjit Singh Naruka, Mahaveer Singh Govardhan, D. School of Computing Science and Engineering Galgotias University UP Greater Noida India Mriem Department of Computer Science and Engineering Rohtak India Koneru Lakshmaiah Education Foundation Department of Artificial Intelligence and Data Science Andhra Pradesh India G L Bajaj Institute of Technology and Management Greater Noida India Institute of Aeronautical Engineering Department of Aeronautical Engineering Hyderabad India

ISBN: (纸本)9798350357769

Deepfakes are artificial intelligence-generated multimedia, primarily videos or audio, that effectively edit or invent information by superimposing one person's likeness or voice onto that of another. They use deep learning techniques such as GAN s to generate hyper-realistic simulations that blur the line between reality and fiction. Deepfakes encompass everything from political satire to possible concerns in the fields of disinformation, privacy invasion, and cybersecurity. Understanding deepfakes is critical in an age when manipulated media may influence public opinion and undermine confidence. The primary objective of this paper is to provide a holistic overview of deepfake technology, shedding light on both its creative potential and inherent risks. Through a systematic exploration of the evolution, applications, techniques, and detection strategies, we aim to equip readers with an informed perspective on this ever-evolving field. By synthesizing existing knowledge and insights, this paper intends to contribute to the ongoing discourse surrounding deepfakes, enabling stakeholders to make informed decisions, develop effective countermeasures, and anticipate the future trajectory of this technology. Ultimately, our work strives to foster awareness and preparedness in an age where discerning the truth has never been more vital. © 2023 IEEE.

关键词： AI CNN Deepfakes GAN Machine Learning RNN

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Development of Advanced Noise Filtering Techniques for Medical Image Enhancement

Development of Advanced Noise Filtering Techniques for Medic...

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Intelligent Communication technologies and Virtual Mobile Networks (ICICV), International Conference on

作者： Sumit Kushwaha K. Amuthachenthiru Geetha. K Jonnadula Narasimharao Dileep Kumar M Sai Sudha Gadde Department of Computer Applications University Institute of Computing Chandigarh University Punjab India Department of Artificial Intelligence and Data Science Ramco Institute of Technology Rajapalayam Tamil Nadu India Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Computer Science and Engineering CMR Technical Campus Hyderabad Telangana India Faculty of Management Sciences Hensard University Bayelsa Nigeria Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Telangana India

Medical imaging modalities, including computed tomography (CT), magnetic resonance imaging (MRI), X-rays, and ultrasound, are extensively employed in the healthcare industry for diagnostic purposes. Noise, on the other hand, can disturb these approaches and lead to inaccurate diagnosis. Due to this problem, the significance of noise removal technologies has grown in the field of medical imaging, specifically for the examination and understanding of medical images and anatomical structures. To tackle these challenges, a variety of denoising techniques have been developed, such as the Weiner filter (WF), Gaussian filter, and median filter. This work employs a Deep Learning (DL) method known as Convolutional Autoencoder (CAE) to remove noise from medical images. We gather chest X-ray images for analysis and focus on common noise types that affect medical images, such as Poisson and Gaussian noise. We evaluate the effectiveness of the suggested denoising method CAE by comparing it to the commonly employed WF methodology. The Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR) are employed to assess and compare the performance of the WF and CAE in reducing Poisson and Gaussian noise. The study's findings indicate that the suggested denoising method based on CAE shows promising results in terms of improving quality.

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Prior Knowledge-Driven Hybrid Prompter Learning for RGB-Event Tracking

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Wang, Mianzhao Shi, Fan Cheng, Xu Chen, Shengyong Tianjin University of Technology Engineering Research Center of Learning-Based Intelligent System Ministry of Education Key Laboratory of Computer Vision and System School of Computer Science and Engineering Tianjin300384 China Technical University of Denmark Department of Technology Management and Economics Kongens Lyngby Denmark

Event data can asynchronously capture variations in light intensity, thereby implicitly providing valuable complementary cues for RGB-Event tracking. Existing methods typically employ a direct interaction mechanism to fuse RGB and event data. However, due to differences in imaging mechanisms, the representational disparity between these two data types is not fixed, which can lead to tracking failures in certain challenging scenarios. To address this issue, we propose a novel prior knowledge-driven hybrid prompter learning framework for RGB-Event tracking. Specifically, we develop a frame-event hybrid prompter that leverages prior tracking knowledge from the foundation model as intermediate modal support to mitigate the heterogeneity between RGB and event data. By leveraging its rich prior tracking knowledge, the intermediate modal reduces the gap between the dense RGB and sparse event data interactions, effectively guiding complementary learning between modalities. Meanwhile, to mitigate the internal learning disparities between the lightweight hybrid prompter and the deep transformer model, we introduce a pseudo-prompt learning strategy that lies between full fine-tuning and partial fine-tuning. This strategy adopts a divide-and-conquer approach to assign different learning rates to modules with distinct functions, effectively reducing the dominant influence of RGB information in complex scenarios. Extensive experiments conducted on two public RGB-Event tracking datasets show that the proposed HPL outperforms state-of-the-art tracking methods, achieving exceptional performance. © 1991-2012 IEEE.

关键词： Object detection

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Integrating HR management, Entrepreneurial Strategies, and Information Technology for Enhanced Organizational Performance

Integrating HR Management, Entrepreneurial Strategies, and I...

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Communication, Computing and Energy Efficient technologies (I3CEET), International Conference on

作者： Lalita Yadav Richa Gupta Manisha Aeri Department of Management Managemetn Education & Research Institute (MERI) New Delhi India Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

It helps improve efficiency at an organizational level with the integration of HRM, entrepreneurial skills, and IT efficiency. In this sense, the efficient management of the human capital of the organization by the HRM and the entrepreneurial strategies of the search for opportunities for the realization of real-time data, communication, and collaboration, and the automation of the trivial are essential to give strength in these attempts and to develop a competitive IT of the organization. By incorporating these three factors, an organization will have an edge by tactfully associating its human capital, business goals, and technological competencies. Such practices are necessary to support HRM practices aimed at sourcing and creating talent for entrepreneurial growth and innovative strategies. IT can also help out HRM processes in the company and make entrepreneurial strategies work in place. Over time, this type of integration can enhance overall organizational performance, maintain an innovation culture, become talent magnets, and improve the processes and supply of cheaper organic changes.

关键词： Productivity Technological innovation Entrepreneurship Organizations Real-time systems Telecommunication computing Resource management Reliability Information technology Magnets

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-Convex b-metric spaces and fixed point results

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The Journal of Analysis 2023年第3期31卷 2187-2202页

作者： Sharma, Dileep Kumar Tiwari, Jayesh Department of Mathematics Government Polytechnic College Mandsaur India Department of Technical Education Bhopal India Department of Computer Science Shri Vaishnav Institute of Management Devi Ahilya University Indore India

In this paper, we present a new series in b-metric spaces with the help of $$(\theta , \delta )$$ -convex structure and give an example to validate this new notion. We prove several fixed point results for different contractions like as Kannan-type contraction and Reich-type contraction of $$(\theta , \delta )$$ -convex structure in the reference of b-metric spaces. These results can be enlarged in many ways by extending the class of such metric spaces.

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Robust Reversible Audio Watermarking Scheme for Telemedicine and Privacy Protection

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computers, Materials & Continua 2022年第5期71卷 3035-3050页

作者： Xiaorui Zhang Xun Sun Xingming Sun Wei Sun Sunil Kumar Jha Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

The leakage of medical audio data in telemedicine seriously violates the privacy of *** order to avoid the leakage of patient information in telemedicine,a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio *** scheme decomposes the medical audio into two independent embedding domains,embeds the robust watermark and the reversible watermark into the two domains *** order to ensure the audio quality,the Hurst exponent is used to find a suitable position for watermark *** to the independence of the two embedding domains,the embedding of the second-stage reversible watermark will not affect the first-stage watermark,so the robustness of the first-stage watermark can be well *** the second stage,the correlation between the sampling points in the medical audio is used to modify the hidden bits of the histogram to reduce the modification of the medical audio and reduce the distortion caused by reversible *** experiments show that this scheme has strong robustness against signal processing operations such as MP3 compression of 48 db,additive white Gaussian noise(AWGN)of 20 db,low-pass filtering,resampling,re-quantization and other attacks,and has good imperceptibility.

关键词： Telemedicine privacy protection audio watermarking robust reversible watermarking two-stage embedding

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Advanced Sports Performance Analysis using Deep Learning for Posture and Movement Identification

Advanced Sports Performance Analysis using Deep Learning for...

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2023 International Conference on Data science and Network Security, ICDSNS 2023

作者： Arvind, S. Hemalatha, K.L. Upendra Roy, B.P. Sandeep, Kasturi Sai Pareek, Piyush Kumar Hyderabad Institute of Technology and Management Department of Cse Hyderabad India Sri Krishna Institute of Technology Department of Information Science and Engineering Bangalore India Channabasaveshwara Institute of Technology Department of Electronics and Communication Engineering Tumkur India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaadeswaram India Nitte Meenakshi Institute of Technology Department of Ai and Ml Bengaluru India

ISBN: (纸本)9798350301595

The proposed work explains the method of detecting the area of interest (ROI), extracting pertinent information, distinguishing different postures, and categorising objects, activities, or events by employing recovered characteristics and segmented regions. Furthermore, the paper delves into the challenges of analysing human posture in three dimensions and advises using 3DPoseNet to estimate the 3D coordinates of vertices. Furthermore, the essay investigates the occlusion problem and proposes a general solution. This style involves extensive use of the torso as well as the limbs and head. Finally, the paper emphasises the creation and implementation of deep learning (DL) in motion identification, which has increased detection performance while decreasing complexity. The article emphasises the importance of developing a variety of algorithms and strategies, such as object tracking, event detection, and action identification, as well as combining methods from image processing, machine learning, and computer vision in order to analyse and interpret video data in applications such as surveillance, sports analysis, and medical imaging. Surveillance, sports analysis, and medical imaging are examples of these uses. © 2023 IEEE.

关键词： Extraction

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Peculiarities of the Formation of Students' Business Communication Skills within the Distance Learning

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education Research International 2023年第1期2023卷

作者： Nagay, Irina Khalabuzar, Oksana Alieksieieva, Hanna Antonenko, Oleksandr Ovsyannikov, Oleksandr Department of Foreign Languages and Methods of Teaching Berdyansk State Pedagogical University Berdyansk 71112 Ukraine Department of Computer Technologies in Management and Education and Computer Science Berdyansk State Pedagogical University Berdyansk 71112 Ukraine

The article deals with the problems of the formation of students' business communications skills at higher educational institutions. The authors ground the hypothesis that the implementation of nonstandard ways and forms of teaching foreign language provides the increasing of effectiveness of formation of students' business communicative skills. The goal of research work deals with the theoretical justification and presentation of nonstandard interactive means and forms of educational activity oriented on the formation of business communication skills (BCS) of students within distance learning. Due to the applied qualitative and quantitative methods of research (conducted surveys, experimental research work, data analysis, etc.), it was proved the necessity of implementation of the interactive technologies into the educational process. The authors found out that modern society requires the new generation of specialists who must be educated, professional in their fields, and able to compete within the rapidly changing paradigms of the business systems. For the further implementation by teachers, they are given samples of nonstandard forms of educational activity, certain interactive technologies, instructions, and advice on ways of increasing the effectiveness of BCS. There are described prospects of the further research activity, which will be devoted to the problem of strengthening of BCS. © 2023 Irina Nagay et al.

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A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection

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computer Systems science & Engineering 2022年第6期41卷 1043-1056页

作者： Xiaorui Zhang Wenfang Zhang Wei Sun Xingming Sun Sunil Kumar Jha Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszowVoivodeship100031Poland

In a telemedicine diagnosis system,the emergence of 3D imaging enables doctors to make clearer judgments,and its accuracy also directly affects doctors’diagnosis of the *** order to ensure the safe transmission and storage of medical data,a 3D medical watermarking algorithm based on wavelet transform is proposed in this *** proposed algorithm employs the principal component analysis(PCA)transform to reduce the data dimension,which can minimize the error between the extracted components and the original data in the mean square ***,this algorithm helps to create a bacterial foraging model based on particle swarm optimization(BF-PSO),by which the optimal wavelet coefficient is found for embedding and is used as the absolute feature of watermark embedding,thereby achieving the optimal balance between embedding capacity and imperceptibility.A series of experimental results from MATLAB software based on the standard MRI brain volume dataset demonstrate that the proposed algorithm has strong robustness and make the 3D model have small deformation after embedding the watermark.

关键词： 3-D medical watermarking robust watermarking PCA BF-PSO

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