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ITCC 2024 - 2024 6th international conference on Information Technology and Computer Communications, ITCC 2024

ITCC 2024 - 2024 6th International Conference on Information...

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6th international conference on Information Technology and Computer Communications, ITCC 2024

ISBN: (纸本)9798400717789

the proceedings contain 17 papers. the topics discussed include: a review of backdoor control techniques for embedded devices;design of general detection circuit for analog signal of equipment electrical and electronic system;mitigating injection and phishing attacks through input validation and phishing detection techniques;performance analysis of a hybrid self-sufficient coverless video steganography method for IoT applications;MemoRecall: a senior friendly web application for holistic intervention of early memory lapses in geriatric individuals;make applications FaaS-ready: challenges and guidelines;and research on user behavior analysis and growth strategies in digital exhibitions based on pattern recognition.

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Research on User Behavior analysis and Growth Strategies in Digital Exhibitions Based on pattern recognition 24

Research on User Behavior Analysis and Growth Strategies in ...

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6th international conference on Information Technology and Computer Communications, ITCC 2024

作者： Zhu, Liuru Sui, Qiao Wu, Zhenlin Sui, Li Liu, Huinan Xu, Yuanlong College of Teacher Education Quzhou University Quzhou China School of Media And Design Hangzhou Dianzi University Hangzhou China Huaiyin Middle School Huaian China College of Architectural Engineering Quzhou University Quzhou China Zhejiang Yuanlai Culture Media Group Co. Ltd Quzhou China

ISBN: (纸本)9798400717789

this paper explores the analysis of user behavior and the development of growth strategies in digital exhibitions using pattern recognition technology. With the rapid advancement of digitalization, particularly in response to global events like the COVID-19 pandemic, digital exhibitions have become increasingly prevalent. By applying pattern recognition, this study identifies and classifies user behavior patterns, enabling companies to better understand user needs and optimize their marketing strategies. the research highlights the significant influence of perceived value on user engagement, decision-making processes, and overall satisfaction. through a comprehensive case study of the Canton Fair’s Digital Exhibitions, the paper demonstrates how companies can leverage behavioral insights to enhance user experience, increase conversion rates, and implement effective personalized marketing strategies. the findings underscore the potential of pattern recognition technology in achieving sustainable user growth and offer actionable recommendations for its application in digital exhibitions. © 2024 Copyright held by the owner/author(s).

关键词： Marketing

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6th international conference on Computational Intelligence in pattern recognition, CIPR 2024

6th International Conference on Computational Intelligence i...

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6th international conference on Computational Intelligence in pattern recognition, CIPR 2024

ISBN: (纸本)9789819780891

the proceedings contain 45 papers. the special focus in this conference is on Computational Intelligence in pattern recognition. the topics include: Vietnamese Text Summarization Using Transformer Approach;DQN Trader: Reinforcement Learning for Automated Trading;indirect Feature Extraction for Efficient Fingerprint recognition;A Novel and Intelligent Neuroimage analysis for Tumor Classification with thermo-Color Segmentation Using VGG-16;a Deep Feature Ensemble Methodology for 2D Biomedical Image Classification;detection of Hardware Trojan in Nanocrossbar-Based Cryptographic Circuit;convolutional Neural Network Segmentation for Satellite Imagery Data to Identify Landforms Using U-Net Architecture;performance Comparison of Different Machine Learning Classifiers for Diabetes Prediction;Intelligent Anti-tamper Systems: Safeguarding Critical Infrastructure in the Era of Proliferating Interconnected Devices and IoBT;contrasting Various Cryptographic Algorithms for Storage and Cloud Computing Services;A New Technique of Cellular-Automata-Based PUF Design in Nanoscale Crossbar Circuits;CrimeScene2Graph: Generating Scene Graphs from Crime Scene Descriptions Using BERT NER;a Squeeze and Excitation Framework Utilizing ResNet-152 for Alzheimer’s Disease Dementia Classification;Identification of Real or Fake Currency Using Semi-supervised Generative Adversarial Networks (SSGANs);efficient Detection of Fake Twitter Profiles on Social Media through Hybrid Deep Learning Model;religious Sentiment analysis and Detection on Social Media;Visualizing NASDAQ Composite Index Historical Data Using Tableau;typeface Identification for English Using Convolutional Neural Networks;Adaptive Ensemble of ML Regressors and LSTM for Stock Price Prediction;PolyNMT: Neural Machine Translation Model with Seq2Seq Encoder-Decoder System;a Rectangular Slotted Sierpinski Fractal Bowtie Antenna for Multiband Wireless Communications;enhancing Cardiac Health: Machine Learning in Coronary Artery Disease Predi

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Effects of Mindfulness Meditation on Cognitive Functions: analysis of Electrocardiogram Signals and Classification Using Ensemble Methods 6th

Effects of Mindfulness Meditation on Cognitive Functions: An...

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6th international conference on Biomedical Engineering

作者： Liew, Joe Ying Lim, Chee Chin Oung, Qi Wei Vijean, Vikneswaran Awang, Saidatul Ardeenawatie Binti Chong, Yen Fook Tan, Xiao Jian Univ Malaysia Perlis Fac Elect Engn & Technol Arau 02600 Perlis Malaysia Univ Malaysia Perlis Sport Engn Res Ctr Arau 02600 Perlis Malaysia Tunku Abdul Rahman Univ Management & Technol Ctr Multimodal Signal Proc Jalan Genting Kelang Kuala Lumpur Malaysia

ISBN: (纸本)9783031803543;9783031803550

Mindfulness meditation, a nonsectarian practice centered around focused attention and conscious breathing, exerts a profound influence on diverse cognitive processes. this study delves into the realm of Electrocardiogram (ECG) signals, capturing four distinct signal types from 40 subjects during mindfulness meditation, rest, concentration tests post-meditation, and subsequent rest periods using PowerLab ADInstruments. To illuminate the intricacies within the ECG data, a series of signal processing techniques were employed. the transformative Discrete wavelet Transform (DWT) eradicated Baseline Wander (BW), while a tenacious Notch filter attenuated Powerline Interference (PLI). Further, the gentle touch of a Moving Average Filter brought serenity to the ECG signals. Employing the esteemed Daubechies 6 (Db 6) wavelet function, DWT facilitated the extraction of 11-time domain features. Additionally, the ethereal realm of frequency domain analysis revealed 4-frequency domain features. Classification endeavors were conducted with two potent classifiers: the illustrious Bagged Trees (BT) ensemble classifier and the formidable Support Vector Machine (SVM) with the Radial Basis Function (RBF) kernel. their discerning power sought to distinguish mindfulness meditation from rest states. Performance measures hailed BT as the worthy champion, flaunting a remarkable accuracy of 90.00%. this pioneering study showcases the far-reaching potential of mindfulness meditation, as it weaves its transformative tapestry through the intricate language of ECG signals. Within this concise exploration, we glimpse the captivating effects of mindfulness meditation on cognitive functions. As the radiant dawn of knowledge beckons, we stand poised to unlock the boundless frontiers of human consciousness.

关键词： Mindfulness Meditation Electrocardiogram Discrete wavelet Transform Support Vector Machine Bagged Trees

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Comparative analysis of Deep Learning Techniques for Underwater Multimedia Compression 6

Comparative Analysis of Deep Learning Techniques for Underwa...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Priyakanth, R. Simon, Judy Department of ECE SRM Institute of Science and Technology Ramapuram Chennai India

ISBN: (纸本)9798331522667

Recent advancements in underwater multimedia compression, particularly deep learning techniques, are explored to address the increasing data demands of the Internet of Underwater things (IoUT). Efficient compression is critical due to the limited bandwidth and greater transmission error rates in underwater acoustic channels. Deep learning models such as the UAT-SSIC scheme, which employs semantic segmentation with joint source-channel coding, and the DWT–CNN framework, which combines discrete wavelet transform with convolutional neural networks, have demonstrated superior compression performance. Advanced techniques like convolutional autoencoders (CAEs) and UCSNet leverage adaptive sampling and underwater priors to enhance image reconstruction and reduce errors. Additionally, approaches like ESPC-BCS-Net and RFD-ECNet achieve efficient compression by integrating compressed sensing and multi-scale feature extraction. these methods consistently deliver high PSNR and SSIM values, minimize spatial redundancy, and optimize energy use, demonstrating their significant potential for improving underwater communication and data processing. © 2025 IEEE.

关键词： Semantic Segmentation

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Accuracy Assessment and Calibration of a 6-DOF Robotic Arm through Simulation Data analysis 6th

Accuracy Assessment and Calibration of a 6-DOF Robotic Arm T...

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6th international conference on Computational Intelligence in pattern recognition, CIPR 2024

作者： Kailash, M. Jones, Aida Babu, K. Dinesh Praveen, S. Department of Artificial Intelligence and Data Science KCG College of Technology Tamil Nadu Chennai India

ISBN: (纸本)9789819780891

this study focuses on refining the real-time positional accuracy of a 6-degree-of-freedom (6-DOF) robotic arm’s end effector by comparing the actual X, Y, and Z axis positions with those calculated from joint angles using DH parameters. through the application of linear regression analysis, variations between these datasets are identified and quantified. the derived variations are then used to adjust the DH parameter-based calculations, resulting in significantly improved accuracy for the robotic arm’s end-effector positioning. this approach offers a systematic method for enhancing the precision of calculated positional data, thereby contributing to the advancement of robotic arm operations across diverse fields. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Degrees of freedom (mechanics)

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Research on the analysis of three-dimensional spatial pattern based on multi-scale geographically weighted regression 6

Research on the analysis of three-dimensional spatial patter...

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6th international conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Zhang, Miao Li, Yucai Shen, Wenfei Beijing University of Civil Engineering and Architecture Beijing China

ISBN: (纸本)9781510688018

this study focuses on the central urban area of Harbin, analyzing the spatial similarity, interdependence of its buildings, and their influencing factors using correlation and spatial autocorrelation analysis. Furthermore, a multi-scale geographically weighted regression (MGWR) model is employed to explore the spatial heterogeneity of three-dimensional buildings in greater depth. Compared to traditional multiple linear regression and geographically weighted regression (GWR) models, the MGWR approach not only provides a more nuanced analysis of spatial heterogeneity but also dynamically adjusts the regression bandwidths for different influencing factors. this allows for a more precise understanding of how these factors impact the three-dimensional spatial pattern. the findings reveal that the architectural landscape pattern in Harbin's central area is strongly influenced by spatial autocorrelation. the distinct characteristics of urban buildings shape the landscape pattern, contributing to notable spatial differentiation across the city. © 2025 SPIE.

关键词： Multiple linear regression

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Visualizing NASDAQ Composite Index Historical Data Using Tableau 6th

Visualizing NASDAQ Composite Index Historical Data Using Tab...

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6th international conference on Computational Intelligence in pattern recognition, CIPR 2024

作者： Safuan, Halawati Abd Jalil Nyein, Chit Ko Ko Riskhan, Basheer Ashfaq, Farzeen School of Computing and Informatics Albukhary International University Alor Setar Malaysia School of Computer Science SCS Taylors University Subang Jaya Malaysia

ISBN: (纸本)9789819780891

the study explores the visualization and analysis of historical data for the NASDAQ Composite Index (^IXIC) using Tableau. It examines trends in daily closing prices and volume distribution and compares performance with the NYSE index. Findings reveal significant fluctuations in the NASDAQ index over 22 years, suggesting potential future price changes. Forecasted graphs offer insights into potential economic decline and recovery, highlighting the dynamic nature of the market. Volume distribution analysis identifies periods of heightened trading activity. Comparative performance analysis emphasizes different trends observed in the NASDAQ and NYSE indices. Due to market unpredictability and external influences, additional research is crucial for validation. this study showcases the value of data visualization and analysis in finance through Tableau. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inflation

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Multi-path error processing and application of CEEMDAN joint wavelet packet algorithm 6

Multi-path error processing and application of CEEMDAN joint...

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6th international conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Liu, Wei Fan, Xiangru Fang, Zhen Wang, Dong Wang, Jin Hou, Hao Yingpanhao Coal Mine Wushen Banner Inner Mongolia Autonomous Region Ordos City017300 China College of Geodesy and Geomatics Shandong University of Science and Technology No. 579 Qianwangang Road Qingdao266590 China

ISBN: (纸本)9781510688018

In order to weaken the influence of multi-path error on positioning results in GNSS mine tower derrick deformation monitoring, this paper proposes a multi-path error processing algorithm based on CEEMDAN joint wavelet packet analysis. the original signal is processed by CEEMDAN decomposition and wavelet packet filtering to extract the multi-path error in the coordinate sequence, which is applied to the subsequent coordinate correction, significantly weakening the influence of multi-path error on the positioning accuracy. through the experimental verification of simulation data and measured data, the results show that the algorithm effectively reduces the interference of multi-path error on GNSS positioning results, and the coordinate accuracy is significantly improved. During DOY199-200, the RMS improvement rate is better than 58.1%, 32.9% and 20.5% in ENU direction, respectively;during DOY200-201, the RMS improvement rate is better than 60.7%, 31.4% and 17.5% in ENU direction, respectively;and during DOY199-201, the RMS improvement rate is better than 56.9%, 20.4% and 15.4%. the results demonstrate that the algorithm performs well in complex mining environments, verifying its utility and reliability in GNSS mine tower derrick monitoring. © 2025 SPIE.

关键词： wavelet decomposition

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Spatial autocorrelation analysis of employment deprivation research on local labour markets 6

Spatial autocorrelation analysis of employment deprivation r...

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6th international conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Gao, Yan Ma, Xuefei Zhang, Chi Institute of Surveying and Mapping Standardization Ministry of Natural Resources Shaanxi Xi'an China Dept. of Geography and urban planning The University of Sheffield Sheffield United Kingdom Piesat Information Technology Co. Ltd Beijing100195 China

ISBN: (纸本)9781510688018

Liverpool has the highest proportion of highly deprived neighbourhoods in England. To explore the spatial pattern of employment deprivation, data from the 2011 Census, and IMD (Index of Multiple Deprivation) from the government are used. Spatial autocorrelation analysis (Moran's I and LISA methods) is applied to determine if there is a systematic pattern in the spatial distribution of the variable and to identify clusters. Time series analysis is conducted to illustrate unemployment levels in Liverpool. the results indicate a positive spatial autocorrelation for employment deprivation in Liverpool, suggesting that neighbouring areas are similar, potentially due to a lack of schools, job opportunities, and labour force demand in certain locations. this pattern of employment deprivation is concentrated, with clusters found in the northern part, southern part, and inner urban cores. Despite improvements in the employment situation, it still falls behind the overall level of the United Kingdom. © 2025 SPIE.

关键词： Autocorrelation

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