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2nd International conference on 3D Immersion, Interaction and Multi-Sensory Experiences, ICDIIME 2023

作者： Lin, Xinya Xu, Han Dong, Jianwen Fujian Agriculture and Forestry University Fuzhou China

ISBN: (纸本)9798350323818

In order to fully grasp the development and research status of forest landscape ecology, this paper analyzed the literatures related to forest landscape from 1982 to 2020 on CNKI and Wanfang data Service platform. Based on Python language environment, this paper uses Scrapy framework to extract literature data, and uses CiteSpace visual analysis software to draw knowledge map. It analyzes and visualizes the amount of articles published, research groups, research hotspots and trends. The results showed that: (1) the development process of forest landscape ecology research was divided into three stages: initial exploration period from 1982 to 2002, rapid development period from 2003 to 2008, and stable development period from 2009 to present. (2) The number of scholars in this field is relatively large and scattered, and the influential core author group and institutional group has not yet been formed;(3) The hot research directions are forest landscape pattern, sustainable development of forest, and forest landscape planning and design. (4) The focus of forest landscape ecology research has gradually shifted from geographic information system to eco-Tourism, urban forest and planning and design, and the research has become specialized and meticulous. © 2023 IEEE.

关键词： Big data

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Unlocking the Perfect Fit: ML Approach for Apparel Size Recommendation 10

Unlocking the Perfect Fit: ML Approach for Apparel Size Reco...

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10th International conference on Applied System Innovation, ICASI 2024

作者： Bhaskar, Shashin Hebbar, Shishir Kumar, Ruthvik v Poorvi, B. vanamala, H.R. Pes University Department of Electronics and Communication Engineering Karnataka Bengaluru560085 India

ISBN: (纸本)9798350394924

This study is based on the exploration of an e-commerce apparel size recommendation system through machine learning and image processing, evaluating three backbone architectures for YOLOv8 - EfficientNet, ResNet, and CSPDarknet - identifying CSPDarknet as the most effective. The novelty of the model is emphasized by its conjunction with a custom-gathered dataset, further optimized by CLAHE for data augmentation and the AdamW optimizer. validated with precise measurements on a set of numerous diverse individuals, the approach integrates C2f and SPPF blocks to enhance gradient flow and model efficiency, significantly advancing the online shopping experience by optimizing the analysis of one single user image. © 2024 IEEE.

关键词： Electronic commerce

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Cloud-Powered Mobility: A Seamless Integration Approach for Mobile Apps 8

Cloud-Powered Mobility: A Seamless Integration Approach for ...

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8th International conference on Inventive Systems and Control, ICISC 202

作者： Satwik, P.v.S. Reddy, T. Sai Jeevan Prabhas, B. Sai Burugari, vijay Kumar Sridhar, P.S.v.S. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Guntur India

ISBN: (纸本)9798350386578

As cloud services continue to gain importance, their integration with mobile applications lags, despite notable exceptions such as Telegram. This research study analyzes the foundational aspects of cloud computing systems, their organization, architecture, and the need for mobile application integration. It explains the necessary development tools and motivations driving app migration to the cloud, while also exploring the fundamentals and layers of mobile cloud computing systems. Through an analysis of techniques like data synchronization and computational offloading, this study highlights the importance of security and reliability. Case studies across domains demonstrate the scalability of this framework for next-generation mobile applications. Furthermore, security and privacy concerns are addressed, alongside an exploration of the services offered by mobile-based cloud providers. Highlighting measures for ensuring security, privacy, and reliability in cloud-powered mobility solutions, this research study covers fault tolerance, data encryption, and authentication systems. Integration with major cloud providers like Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform is discussed, along with advanced methodologies and recommendations for future advancements in the field. © 2024 IEEE.

关键词： Cloud platforms

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Machine Learning for Enabling Strategic Insights to Future-Proof E-Commerce 5

Machine Learning for Enabling Strategic Insights to Future-P...

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5th International conference on Smart Electronics and Communication, ICOSEC 2024

作者： Kodete, Chandra Shikhi Pasupuleti, vikram Thuraka, Bharadwaj Gayathri, v. valli Sundar, v. S. Divya Shariff, vahiduddin Eastern Illinois University School of Technology United States Northwest Missouri State University Department of Information Systems United States Sir C R Reddy College of Engineering Department of Cse Eluru India Saveetha Engineering College Department of Cse Chennai India

ISBN: (纸本)9798331504403

In the rapidly evolving e-commerce sector, predictive analytics is becoming an increasingly important tool for businesses to employ to forecast consumer behavior, enhance marketing efforts, and boost overall productivity. The reason for this examination project is to utilize machine learning procedures to work on the predictive investigation in the E-commerce business area. The limit concerning expectation concerning a business examiner is subject to artificial intelligence. Artificial intelligence (AI) is a quickly developing field that is utilized in numerous spaces, particularly in data analysis and prediction. This study utilizes machine learning, which is a subtype of AI. Deciding the future development and application capability of Internet business is the point of this examination. To give a reasonable clarification, E-commerce comprehension shoppers was taken to interpret the general commitment of the Indian internet business area and utilized optional data available worth of online business as a premise to help the pay produced by E- e-commerce business. Python was used for the impending years, 2024 to 2026. By utilizing two additional factors - the extent of Indian e- commerce customers and online business income - the new review looks to build the accuracy of the market esteem gauge. By consolidating bits of knowledge from both scholastic exploration and industry activities, this article intends to give helpful suggestions and best practices for online business professionals and chiefs craving to utilize machine learning for predictive examination. At last, the exploration adds as far as anyone is concerned of online business examination and establishes the groundwork for future examination and imaginative reasoning in this field. © 2024 IEEE.

关键词： Marketplaces

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visual analysis of Spatio-temporal Phenomena with 1D Projections

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COMPUTER GRAPHICS FORUM 2021年第3期40卷 335-347页

作者： Franke, M. Martin, H. Koch, S. Kurzhals, K. Univ Stuttgart Stuttgart Germany Swiss Fed Inst Technol Zurich Switzerland Inst Adv Res Artificial Intelligence Vienna Austria

It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio-temporal data, based on a set of neighborhood-preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real-world application scenarios and discuss the feedback we received from domain and visualization experts.

关键词： CCS Concepts • Human-centered computing → visual analytics Geographic visualization Information visualization visualization systems and tools

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A Hybrid Machine Learning Approach for Sleep and Awake States Detection Using EEG data

A Hybrid Machine Learning Approach for Sleep and Awake State...

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2024 IEEE International conference on Innovation and Novelty in Engineering and Technology, INNOvA 2024

作者： Adhyapak, Shrinivas Ghuli, Anand Patil, Shashidhar Hiremath, Shivamurti Department of MCA BLDEA’s V.P. Dr. P.G. Halakatti College of Engineering and Technology Affiliated to Visvesvaraya Technological University Belagavi Karnataka Vijayapur India

ISBN: (纸本)9798331505134

Brain wave analysis significantly contributes in neurological diagnostics and research by clinically offering critical insights into neural activity and different patterns of sleep. This work aims in accurately detecting sleep stages using Electroencephalography (EEG) data using Exploratory data analysis (EDA) and advanced modelling techniques, with a focus on precisely identifying and categorizing sleep stages. The dataset for this study is extracted from Kaggle that includes complete EEG recordings of individuals during sleep is processed and visualized using EDA. During the modelling stage, predictive models for sleep stage classification are constructed using Machine Learning (ML) algorithms like Random Forest, SvM, KNN, and Logistic Regression. Using ensemble techniques, hyperparameter optimization, and cross-validation, these models go through rigorous training, validation, and testing. The most accurate model was a hybrid one that combined Random Forests, SvM, KNN, and Logistic Regression as a meta-learner. The polysomnographic recordings that make up the dataset provide rich brain wave data from various stages of sleep. The methodology was validated using benchmark datasets, which confirmed its high accuracy in identifying different stages of sleep. These results demonstrate the importance of rigorous data exploration and reliable modelling approaches for the advancement of neuroinformatics research. © 2024 IEEE.

关键词： Sleep research

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Decoded visual Stimulus Studies Using Functional Magnetic Resonance Imaging 6

Decoded Visual Stimulus Studies Using Functional Magnetic Re...

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6th International conference on Computational Biology and Bioinformatics (ICCBB)

作者： Ma, Junzhu Zhu, Yiming Stuart Country Day Sch 1200 Stuart Rd Princeton NJ 08540 USA Hong Kong Polytech Univ Hong Kong Peoples R China

ISBN: (纸本)9781450397636

In this paper, data from Kay experiment were used to explore how different brain regions involved in visual processing encode different types of visual stimuli, and whether this process has similarities to principal component analysis (PCA). By correlating brain activity with projections on principal components (PCS) of images extracted from the Kay image dataset, v1 and v2 voxel activities were found to have the highest average correlations with image projections on the top 10 PCS. Meanwhile, v2 processes "animal" images, a set of photos of animals, such as a giraffe, that most closely resemble PCA across all brain regions. Next, the brain voxels were correlated with the vectors of each image label, showing an increasing correlation between brain activity and the semantic information of the corresponding visual stimuli. This trend was further demonstrated on "artifact" images, with the exception of v4, after the same correlations were calculated based on image categories.

关键词： visual stimulus magnetic resonance image principal component analysis

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Analyzing Difficulties of visual Questions Using Entropy values of Answer Predictions 8th

Analyzing Difficulties of Visual Questions Using Entropy Val...

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8th International conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Geetha Yadav, M. Nennuri, Rajasekhar Deepthi, N. Siri Harshitha, K. Naga vinay, A. CS & IOT MALLA REDDY UNIVERSITY Hyderabad India Department of CSE Institute of Aeronautical Engineering Hyderabad India

ISBN: (纸本)9789819786657

Our approach introduces a novel method for assessing the difficulty of visual questions in visual Question Answering (vQA) that does not depend on human annotations. Rather than using human-provided responses to real-world situations, as previous studies have done, we evaluate the performance of various vQA models to determine the level of question difficulty. We combine the predicted response distributions of three models: a baseline model that considers both images and questions, and two modified models that incorporate image and question inputs. We group visual questions in the vQA v2 validation set into clusters using k-means clustering and use advanced techniques to calculate accuracy and entropy values for each cluster. Each cluster corresponds to a specific level of visual question complexity, eliminating the need for explicit labeling of difficulty. Our approach effectively identifies clusters of challenging visual questions that even state-of-the-art tools struggle to answer. We conducted a thorough analysis of the vQA v2 dataset and found that all methods performed poorly on the most challenging cluster (with around 10% accuracy), and the accuracy of different models’ predictions diverged as the question difficulty increased. We also observed a strong correlation between entropy and accuracy values for each cluster. Our method can evaluate visual question complexity without depending on ground truth data. By clustering visual questions in the test set, we can inspire the development of new research approaches and techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： visual analytics

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Intelligentization of Art Design System Based on Multidimensional visual Image Reconstruction Algorithm 3

Intelligentization of Art Design System Based on Multidimens...

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3rd International conference on Smart data Intelligence, ICSMDI 2023

作者： Wang, Yuejuan School of Computer and Art Anhui Technical College of Industry and Economy Anhui Hefei430071 China

ISBN: (纸本)9781665464871

Among the mainstream methods of image aesthetic quality evaluation, it can be divided into traditional aesthetic evaluation methods based on the artificial design features and current popular aesthetic evaluation methods based on deep learning. Hence, this paper studies the intelligentization of art design system based on the multidimensional visual image reconstruction algorithm. In the proposed study, the modelling process contains the 2 essential aspects, namely, the multidimensional image analysis and image perception, respectively. The framework is modelled separately and then combined for the comprehensive analysis of image aesthetic quality evaluation for art design system. After testing on large sets of data, the performance is shown to be efficient. © 2023 IEEE.

关键词： Image analysis

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Research on visual analysis Method of Software Function Testing Process

Research on Visual Analysis Method of Software Function Test...

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2021 International conference on Computer Graphics, Artificial Intelligence, and data Processing, ICCAID 2021

作者： Zuo, Zihuan Wu, Yadong Chen, Yuansong Zhang, Xiaorong Qin, Renchao School of Computer Science and Technology Southwest University of Science and Technology Mianyang621000 China School of Computer Science and Engineering Sichuan University of Science and Engineering Zigong643002 China

ISBN: (数字)9781510652170

ISBN: (纸本)9781510652163

The existing research on software testing visualization is mostly at the code and developer level, and the visualization content is mostly at the code line and document level, and the target user group is very limited. In addition, the thirdparty software evaluation agency involves a large number of paper documents in the testing and review, which is inconvenient to manage, difficult to consult and analyze, and work efficiency is low. In order to solve these problems, we propose a visual analysis framework for software functional testing process. Starting from the functional testing process and the key information of each process, a set of visual analysis process is constructed, the data extraction method of the test document and the visual analysis method of the test process are studied, and the visual analysis prototype system is constructed to support the software testing process. And the key information of each process for quick analysis and further exploration. Finally, we demonstrated the application of the system in actual test projects through case analysis. © 2022 SPIE.

关键词： Software testing

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