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检索条件"任意字段=Conference on Visual Data Exploration and Analysis V"

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24th International conference on Innovations for Community Services, I4CS 2024

24th International Conference on Innovations for Community S...

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24th International conference on Innovations for Community Services, I4CS 2024

ISBN: (纸本)9783031604324

The proceedings contain 23 papers. The special focus in this conference is on Innovations for Community Services. The topics include: QUBO Formulation for Sparse Sensor Placement for Classification;Leveraging Quantum Technology to Enhance Community Services and Supportive ICT Infrastructure;SATQUBOLIB: A Python Framework for Creating and Benchmarking (Max-)3SAT QUBOs;better Together – Empowering Citizen Collectives with Community Learning;the Future of Ageing: The Impact of Smart Home Technologies on Ageing in Place;examining Smart Neighborhood Platforms: A Qualitative exploration of Features and Applications;webMap - Large Language Model-assisted Semantic Link Induction in the Web;Development and validation of AI-Driven NLP Algorithms for Chatbots in Requirement Engineering;Structured Knowledge Extraction for Digital Twins: Leveraging LLMs to Analyze Tweets;Oblivious Graph Algorithms for Solving TSP and vRP Using FHE and MPC;route Optimization of an Unmanned Aerial vehicle Beyond visual Line of Sight;spanning Thread: A Multidimensional Classification Method for Efficient data Center Management;integrating Contextual Integrity in Privacy Requirements Engineering: A Study Case in Personal E-Health Applications;the System Architecture of a Reliable Telesurgery Service and its Performance analysis;emulation of Denial-of-Service Attacks for Software Defined Networks;scared? Prepared? Toward a Ransomware Incident Response Scenario;COPYCAT: Applying Serious Games in Industry for Defending Supply Chain Attack;operation Raven: Design of a Cyber Security Incident Response Game;greenhouse Gas Emissions as Commons: A Community Service Approach with Blockchain on the Edge;the Digital Product Passport: Enabling Interoperable Information Flows Through Blockchain Consortia for Sustainability;digital Sovereignty and Open-Source Software - A Discussion Paper;web-Based Protocol Enabling Distributed Identity Information Networks for Greater Sovereignty.

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SUMMvIS: Interactive visual analysis of Models, data, and Evaluation for Text Summarization 59

SUMMVIS: Interactive Visual Analysis of Models, Data, and Ev...

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Joint conference of 59th Annual Meeting of the Association-for-Computational-Linguistics (ACL) / 11th International Joint conference on Natural Language Processing (IJCNLP) / 6th Workshop on Representation Learning for NLP (RepL4NLP)

作者： vig, Jesse Kryscinski, Wojciech Goel, Karan Rajani, Nazneen Fatema Salesforce Res Palo Alto CA 94301 USA Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781954085565

Novel neural architectures, training strategies, and the availability of large-scale corpora haven been the driving force behind recent progress in abstractive text summarization. However, due to the black-box nature of neural models, uninformative evaluation metrics, and scarce tooling for model and data analysis, the true performance and failure modes of summarization models remain largely unknown. To address this limitation, we introduce SUMMvIS, an open-source tool for visualizing abstractive summaries that enables fine-grained analysis of the models, data, and evaluation metrics associated with text summarization. Through its lexical and semantic visualizations, the tools offers an easy entry point for in-depth model prediction exploration across important dimensions such as factual consistency or abstractiveness.

关键词： Semantics

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Improving Stage Isolation in vaca Muerta Wells Through Observations from an Integrated Fiber Optic Pilot

Improving Stage Isolation in Vaca Muerta Wells Through Obser...

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2024 SPE Hydraulic Fracturing Technology conference and Exhibition, HFTC 2024

作者： Savitski, Alexei A. Lock, Benjamin Todea, Felix Fita, Patricio Formento, Gabriel Al Lawati, Hawraa I. Mondal, Somnath Ugueto, Gustavo Shell Exploration & Production Company HoustonTX United States Shell Global Solutions Canada Inc. Calgary Canada Shell Argentina S.A. Buenos Aires Argentina Shell Global Solutions International B.V. The Hague Netherlands Shell Development Oman LLC Muscat Oman Shell International Exploration and Production Inc. HoustonTX United States

ISBN: (纸本)9781959025153

The productivity of an unconventional well depends on reservoir quality that can be selected but not controlled and completions that can be optimized. The challenge with improving a completion design is the lack of information about the actual downhole performance. An ultimate requirement for an effective completion is to have isolation between two adjacent stages. The observations and recommendations for improving stage isolation are made from the first integrated fiber optic (FO) pilot in vaca Muerta. Shell conducted an integrated diagnostic pilot in vaca Muerta that included acquisition of multiple data types, such as: permanent fiber optics installation, surface microseismic monitoring, downhole pressure gauges, mudlogging, open and cased hole logging. One of the objectives for this project was to evaluate stage isolation performance for different plug types. Stage isolation was analyzed based on the DAS and DTS interpretation in two wells equipped with permanent fiber optic cable. Complementary, isolation integrity test (IIT) was performed in three stages of each well during wireline pump down operations. These results are compared with the FO interpretations. This paper summarizes observations from the real-time monitoring of operations on two wells landed in different zones. Three solutions for stage isolation were tested in these wells. A statistical analysis of their performance is presented. The interpretation of the isolation integrity test is summarized and discussed. The isolation results between FO and IIT are cross-checked. While all stages with IIT data have good isolation based on FO interpretation, three of IIT tests indicate the lack of isolation. This discrepancy is discussed in the paper. During the execution of the pilot, observations were made about the impact of the treatment schedule on the plug performance. Modifications were implemented during execution and recommendations are made for future completions. The investigation extends to evalu

关键词： Fiber optics

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Application exploration of Robot Process Automation in Digital Labor Time Management System 3

Application Exploration of Robot Process Automation in Digit...

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3rd International conference on Machine Learning and Big data Analytics for IoT Security and Privacy, SPIoT2023

作者： Liu, Fei Li, Jian College of Basic Military and Political Education National University of Defense Technology Hunan Changsha China School of Physics and Electronic Information Engineering Neijiang Normal University Sichuan Neijiang China

In the digital era, Robotic Process Automation (RPA) has become an important technology in the field of information technology. The purpose of this article is to apply RPA technology to the digital labor time management system of enterprises to improve management efficiency and accuracy. This article mainly used data comparison and mathematical model analysis methods to draw conclusions and provide specific solutions. The experimental results showed that the minimum time reduction rate for robot process automation was 19.5%. The RPA solution for digital labor time management system has the characteristics of sustainable development, convenient management, and strong systematicity, which has great promotion and application value. © 2023 The Authors. Published by Elsevier B.v.

关键词： Process control

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Dermoscopic Skin Lesion Classification using Color Features Based on Fine-Tuning of Resnet50 and Densenet121 Transfer Learning Models

Dermoscopic Skin Lesion Classification using Color Features ...

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2024 International conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 2024

作者： Kujani, T. Kumar, v. Dhilip Bhuvanya, R. Kavitha, A. Sathya, T. Sathiya Priya, S. Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Sri Ramachandra Institute of Higher Education and Research Sri Ramachandra Faculty of Engineering and Technology Chennai India Government Polytechnic College Computer Engineering Karur India Sri Sairam Engineering College Computer Science and Business Systems Chennai India

ISBN: (纸本)9798350360660

Skin cancer, which stands as the most prevalent form of human malignancy, is primarily identified through visual examination. The procedure for identifying skin lesions typically starts with an initial clinical assessment, which might be followed by dermoscopic analysis, a biopsy, and a subsequent histopathological checkup. Image-based Skin lesion classification presents a significant challenge due to the subtle and intricate variations in their appearance. Deep Convolutional Neural Network (DCNN) show promising results in managing diverse and intricate tasks involving a wide array of finely detailed object categories. Skin lesions Classification is shown in this work initially using a six-layered CNN performed on the skin cancer dataset to classify seven classes of lesions with 10015 images. Exploratory data analysis of the dataset is performed to identify any outliers and to verify the balance of samples in each class. It was observed after 50 epochs, the training accuracy was 98.03% and the testing accuracy was 67.40%. To avoid the overfitting observed in the CNN approach, the pre-trained transfer learning models, Resnet50 and Densenet121 were finetuned with data augmentation to handle the imbalance of samples present in seven classes. The results obtained prove that the Densenet121 model achieves high performance compared with the other Resnet50 model after augmentation. © 2024 IEEE.

关键词： Convolutional neural networks

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24th International conference on Enterprise Information Systems, ICEIS 2022

24th International Conference on Enterprise Information Syst...

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24th International conference on Enterprise Information Systems, ICEIS 2022

ISBN: (纸本)9783031393853

The proceedings contain 20 papers. The special focus in this conference is on Enterprise Information Systems. The topics include: Effect of Convulsion Layers and Hyper-parameters on the Behavior of Adversarial Neural Networks;modelling Software Tasks for Supporting Resource-Driven Adaptation;A Critical view on the OQuaRE Ontology Quality Framework;successful Practices in Industry-Academy Collaboration in the Context of Software Agility: A Systematic Literature Review;distance Digital Learning for Adult Learners: Self-paced e-Learning on Business Information Systems;human-Computer Interaction: Ethical Perspectives on Technology and Its (Mis)uses;Meet2Map: A Framework to Support BPM Projects Implementation Collaboratively;the Factors of Enterprise Business Architecture Readiness in Organisations;a Specification of How to Extract Relevant Process Details to Improve Process Models;a Storage Location Assignment Problem with Incompatibility and Isolation Constraints: An Iterated Local Search Approach;considering User Preferences During Business Process Execution Using Content-Based Filtering;using IoT Technology for the Skilled Crafts;Implementation Solutions for FAIR Clinical Research data Management;visual Interactive exploration and Labeling of Large volumes of Industrial Time Series data;resource Planning in Workflow Nets Based on a Symbolic Time Constraint Propagation Mechanism;implementation of the Maintenance Cost Optimization Function in Manufacturing Execution Systems;quantitative Comparison of Translation by Transformers-Based Neural Network Models;optiviTh: A Decision Guidance Framework and System for Design, analysis and Optimization of Cloud-Manufactured virtual Things.

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Preliminary exploration of a competency model for open-source processor chip design talent 23

Preliminary exploration of a competency model for open-sourc...

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2023 ACM Turing Award Celebration conference, CHINA 2023

作者： Yang, Xiaochun Zhang, Ke Yu, Zihao Shanghai AchieveFun Info Tech Co Ltd Shanghai China Institute of Computing Technology of Chinese Academy of Sciences China and University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400702334

To support the cultivation of open source processor chip design talents and to provide a high-quality talent development and assessment model for universities to assess students of the "Computing System and Processor"course and for enterprises to recruit graduates, professionals from enterprises and teachers from universities have collaborated to design an open source processor chip design talent competency model based on the CC2020 competency model, science and engineering practice theory and curriculum theory, in order to provide relatively reasonable, comprehensive and accurate reference information for talent training and education teaching. This poster designed a competency model that includes statement, computing and professional knowledge-skills pairs and dispositions. The summary results of the visual assessment tool designed on the basis of the competency model are presented, including an initial description of student characteristics, a comprehensive task-based assessment conclusion, as well as a detailed analysis of the dimensions of computing and professional knowledge-skill pairs and dispositions and corresponding suggestions. The authors will continue to refine the quantification of student learning behavior markers to provide easy-to-operate reference data for education and teaching and to enhance the usability of the model. © 2023 Owner/Author.

关键词： Curricula

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Movie Tag Prediction System Using Machine Learning

Movie Tag Prediction System Using Machine Learning

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International conference on data Analytics and Management, ICDAM 2022

作者： Mehta, vivek Singh, Tanya Reddy, K. Tarun Kumar Reddy, v. Bhanu Prakash Jain, Chirag School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (纸本)9789811976148

Movies can be tagged with various details such as genre, plot structure, soundtracks, and visual and emotional experiences. This information can be used to build automatic systems to extract similar movies, enhance user experience, and improve the recommendations. In this paper, a machine learning-based approach is proposed to predict the tags which can be associated with a given movie. The problem is posed as a multi-label classification problem. To solve this, firstly, we created a fine-tuned set of various tags that exposed the varied characteristics of movie plots (a textual summary of a movie). Then, using different textual representation techniques such as TF-IDF, AvGW2v (averaged word vector), and several machine learning classifiers are used to predict the tags associated with a movie. It is believed that the proposed machine learning-based tag prediction can be useful in other tasks related to narrative analysis. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Big data

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exploration and Discovery of the COvID-19 Literature through Semantic visualization

Exploration and Discovery of the COVID-19 Literature through...

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conference of the North-American-Chapter of the Association-for-Computational-Linguistics - Human Language Technologies (NAACL-HLT)

作者： Tu, Jingxuan verhagen, Marc Cochran, Brent Pustejovsky, James Brandeis Univ Waltham MA 02453 USA Tufts Univ Sch Med Boston MA 02111 USA

ISBN: (纸本)9781954085503

We propose semantic visualization as a linguistic visual analytic method. It can enable exploration and discovery over large datasets of complex networks by exploiting the semantics of the relations in them. This involves extracting information, applying parameter reduction operations, building hierarchical data representation and designing visualization. We also present the accompanying COvID-SEMvIZ, a searchable and interactive visualization system for knowledge exploration of COvID-19 data to demonstrate the application of our proposed method.(1) In the user studies, users found that semantic visualization-powered COvID-SEMvIZ is helpful in terms of finding relevant information and discovering unknown associations.

关键词： COvID-19

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Implementing Agile Task Management System: Leveraging Web Development and Power BI for Enhanced Decision-Making 2

Implementing Agile Task Management System: Leveraging Web De...

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2nd International conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Jaishree, M. Anupriya, v. Sukitha, M. Sri Ramakrishna Engineering College Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350368413

Developing a Task management system can benefit organizations in several ways which offers a comprehensive solution that enhances productivity, improves collaboration, provides visibility, supports Agile practices, ensures accountability, and allows for seamless integration and scalability. This helps organizations manage their tasks and projects more efficiently, ultimately leading to better outcomes and increased success. The Agile Task Management system can be developed by combining both the front-end and back-end along with a database for storing and organizing the company project details like the status, project timeline, and project team details like their mail IDs and the particular projects they belong to. The task management web application can be developed in various languages and frameworks for managing and aggregating projects with specific employees. This research study focuses on two main areas: developing a task management web application and creating a dashboard using Power BI for in-depth analysis of the organization's project dataset. Power BI plays a crucial role in data analytics by integrating data from multiple sources, enabling interactive exploration, and facilitating collaborative decision-making through its powerful visualization and reporting tools. The discussion includes using HTML, JavaScript, Ajax, and Bootstrap for the front end, PHP for the backend, and MySQL for the database to create a comprehensive Task Management web application. Additionally, it covers the development of a simple task management system with a Python Flask application using SQL Alchemy and PyQt5 for GUI creation with an SQLite database. Additionally, the system is designed to handle complete project-related datasets by incorporating Power BI Desktop to create interactive dashboards for visualizing project data which is a separate part of the task management system. © 2024 IEEE.

关键词： Query languages

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