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TETYS: Towards the Next-Generation Open-Source Web Topic Explorer 36

TETYS: Towards the Next-Generation Open-Source Web Topic Exp...

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36th international conference on Advanced Information systems engineering, CAiSE-RPE 2024

作者： Bernasconi, Anna Invernici, Francesco Ceri, Stefano Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy

Users who search the web for specialized content typically lack knowledge of the precise topology of the dataset upon which the search is performed. Funded by European Union, TETYS is a beneficiary of the Next Generation Internet (NGI) Search Initiative;it proposes to build the next-generation open-source Web topic explorer. Our architecture inspects big textual corpora;it is composed of 1) a pipeline for ingesting huge data corpora, extracting highly relevant topics, clustered along orthogonal dimensions;and 2) an interactive dashboard, supporting topic visualization as word clouds and exploration of temporal series, with easy-to-drive statistical testing. The first prototype, CORToViz, explores the CORD-19 dataset (COVID-19 / SARS-CoV-2 virus research abstracts). Many different domains will be explored using TETYS (e.g., climate change and controversial debates on social media). © 2024 Copyright for this paper by its authors.

关键词： data Analytics

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Approaches Towards AI-Based Recommender System

Approaches Towards AI-Based Recommender System

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2022 international conference on Machine Learning, Big data, Cloud and Parallel Computing, COM-IT-CON 2022

作者： Rawat, Amarjeet Ghildiyal, Sunil Dixit, Anil Kumar Memoria, Minakshi Kumar, Rajiv Kumar, Sanjeev Uttaranchal University Department of Computer Science and Engineering Dehradun India Uttaranchal University Law College Dehradun Dehradun India Uttaranchal University Department of Computer Applications Dehradun India Himgiri Zee University Department of Computer Science and Information Technology Dehradun India

ISBN: (数字)9781665496025

ISBN: (纸本)9781665496025

Recommender systems (RS) have application in all areas where digital information is generating at high rate. They are used to filter large volume of digital data containing user preferences, interests and behaviour patterns for products and services. Today artificial intelligence has achieved rapid development in automation, computation, knowledge-engineering, information retrieval and processing. Techniques such as fuzzy logic, neural networks, natural language processing, transfer learning, machine learning are also contributing to enhance the performance, accuracy of recommendation system and reducing problems like cold-start, data-sparsity, privacy and scalability. This paper explains the development stages and different categories of recommender system. This paper further explores the challenges and recent trends in building recommendation system. © 2022 IEEE.

关键词： Recommender systems

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Structured database Design for iDSS-ProLean a Decision Support System for Lean Semiconductor manufacturing

Structured Database Design for iDSS-ProLean a Decision Suppo...

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TVET Excellence & Development (ICTeD), international conference on

作者： Nur Ain Qistina Muhammad Shafee Effendi Mohamad Mohd Soufhwee Abd Rahman Nor Asmaa Alyaa Nor Azlan Mohd Hamdi Abd Shukor Rudi Nurdiansyah Faculty of Industrial and Manufacturing Techonology and Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia Faculty of Mechanical Engineering Universiti Teknologi Malaysia Johor Malaysia Faculty of Engineering Universiti Malaya Kuala Lumpur Malaysia Department of Mechanical Industrial Engineering Universitas Negeri Malang Jawa Timur Indonesia

ISBN: (数字)9798331516413

ISBN: (纸本)9798331516420

This work describes the thorough planning and execution of a structured database for the intelligent decision support system (DSS) called iDSS-ProLean, which was created to maximise semiconductor manufacturing lines. SMED (Single-Minute Exchange of Dies), Kanban, and Line Balancing are just a few of the critical lean manufacturing technologies that are supported by the carefully designed database. An IoT interface layer is also included for real-time data collection from the factory floor. Critical operations like etching, cutting, and assembly are handled by the system, which has database tables made specifically for efficient data management and resource allocation. The database structure ensures smooth communication across several manufacturing stages by including essential components including machinery, labour, and production data. By streamlining data flow and providing a robust platform for decision-making, this work demonstrates how the structured database enhances iDSS-ProLean’s ability to manage production resources, improve efficiency, and meet demand targets more effectively in semiconductor manufacturing environments.

关键词： Decision support systems Semiconductor device measurement databases System performance Scalability Production Semiconductor device manufacture data collection Real-time systems Resource management

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Use of Mechatronics and Software-as-a-service for Enhancing Total Quality Management in the manufacturing Industry 6

Use of Mechatronics and Software-as-a-service for Enhancing ...

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6th international conference on Intelligent Computing and Control systems, ICICCS 2022

作者： Baskar, S. Mehta, Shiv Abisheva, Gulmira Minayeva, Aislu Seidullaeva, Gulzhan Ahamad, Shaik Fasi Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India Abay Myrzakhmetov Kokshetau University Department of Design Kazakhstan International Education Corporation Department of Linguistics Almaty050042 Kazakhstan International Education Corporation Department of Construction Almaty Kazakhstan Jain University Cms Business School Department of Business Administration Bangalore India

ISBN: (纸本)9781665410359

Quality management within a company ensures high quality of product, after elimination of defects and developing continuous changing process. Managing quality process of the manufacturing unit is the key aspect to ensure loyal customers. As a result, it can be stated that engaging mechatronics as an effective admin dashboard template to improve quality management process within a manufacturing company will be the most essential aspect. This user-friendly template develops a design for allowing making an easy to operate admin dashboard. This admin dashboard can be effective to manage their company website for improving e-commerce channel, CRM (Customer Relationship Management), SAAS (Software as a Service) and CMS (Content Management System). All these factors are related to the quality management of a company that can draw the attention of potential customers in a completive market structure. Focus of this research is to develop an idea regarding mechatronics within a manufacturing sector and in which way it accelerates the company's value in market. In the introduction part, main aim, objective and research question has been reflected in this study. The literature section has provided idea of admin template, concept of quality management service within Indian manufacturing Industry. The research paper has considered secondary data collection method with themes to identify the result. It has been found that, Indian manufacturing sector do not have impended mechatronics as such for their quality management process. They develop other aspects of quality management and example from other countries, which uses such admin template like mechatronics, are discussed to understand its positive effect. © 2022 IEEE.

关键词： Industrial research

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Methodology for Characterizing Spectrum data by Combining Quantitative and Qualitative Information 16th

Methodology for Characterizing Spectrum Data by Combining Qu...

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16th European-Alliance-for-Innovation (EAI) international conference on Cognitive Radio Oriented Wireless Networks (EAI CROWNCOM)

作者： Nagpure, Vaishali Das, Udayan Hood, Cynthia IIT Chicago IL 60616 USA St Marys Coll Calif Moraga CA 94575 USA

ISBN: (纸本)9783030980023;9783030980016

Wideband spectrum data can provide information on how large portions of the spectrum are being used. Spectrograms are typically used to visualize this data. The interpretation of the spectrogram (e.g., identification of bands and patterns) is left to the user, requires significant domain knowledge and is extremely time consuming. In this paper, we present a methodology for combining quantitative and qualitative information to identify channels and changes in spectrum occupancy. Channel identification and change detection algorithms are applied to real spectrum data collected over several years on two different measurement systems in Chicago. These analyses were then used to formulate queries to a knowledge graph implemented on a neo4j graph database. The results of the queries validated the channel identification and provided validation and explanation of the changes detected. This methodology was tested on measurement data from 470-698 MHz.

关键词： Spectrum measurements knowledge graph Graph database Change detection

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Use Case Scenario in Federated Learning-Based Intrusion Detection systems

Use Case Scenario in Federated Learning-Based Intrusion Det...

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international conference on data Analytics and Insights, ICDAI 2023

作者： Sharma, Rhythm Kaur, Ravneet Babbar, Himanshi Sharma, Anshika Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

ISBN: (纸本)9789819938773

A relatively new development in artificial intelligence (AI), federated (FL), also known as collaborative learning, is still in its infancy or formative stage. A substantial majority of dispersed servers that retain localized sequence data are used in this machine learning (ML) paradigm to train algorithms without transferring the real data samples. A web service receives data that has been educated and aggregated using a variety of smart objects, including pcs, cellphones, as well as other devices, for ML. Due to FL’s fundamental advantages, which will be covered in more detail later in this paper, it can be applied in a wide range of industries, including healthcare, security, Internet of Things (IoT), and others. The goal of this research paper’s overview is to give readers a thorough understanding of FL, including its current situation, workings, fundamental advantages, types, potential applications, algorithms, and difficulties it now faces. There are not many academic articles or research papers on federated learning because it is still a young idea and in its infancy. Of course, there are certain writings on this subject that are entirely devoted to it and offer us a wealth of great knowledge about it. This report included crucial suggestions for further research on situations encountered in the real world that would aid in the advancement of FL. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Mixed Attitude towards ChatGPT on Social Media: Digital Emotion Contagion or knowledge Sharing 44

Mixed Attitude towards ChatGPT on Social Media: Digital Emot...

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44th international conference on Information systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

作者： Wang, Wei-Jun Wu, Chun-Kai Liu, Wenting Hung, Yu-Chen Ren, Jing Horng, Jorng-Tzong Computer Science and Information Engineering National Central University Taoyuan Taiwan Department of Mathematics National Central University Taoyuan Taiwan School of Business Singapore University of Social Sciences Singapore

ISBN: (纸本)9781713893622

ChatGPT-3, a highly anticipated chatbot developed by OpenAI, has garnered significant attention since its public release in November 2022. The impact of ChatGPT on various sectors has fuelled mixed responses. Despite the breadth and depth of its impact, research on public sentiments remains limited, with few exceptions. This study aims to fill that gap by exploring the emotional reactions to ChatGPT on Twitter, tracking changes in emotions over time, and identifying the key topics associated with these emotional shifts. By analyzing Twitter data with the ChatGPT hashtag, the study uncovered a range of emotions expressed by social media users. Furthermore, it investigated the topics dominating online discussions related to ChatGPT and its emotional impact. This research sheds light on the public sentiment surrounding ChatGPT, and the implications for its adoption. Copyright © 2023 [Wei-Jun Wang and Chun-Kai Wu].

关键词： Sentiment analysis

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FUNCTION DRIVEN ASSESSMENT OF manufacturing RISKS IN CONCEPT GENERATION STAGES 24

FUNCTION DRIVEN ASSESSMENT OF MANUFACTURING RISKS IN CONCEPT...

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24th international conference on engineering Design, ICED 2023

作者： Brahma, Arindam Panarotto, Massimo Kipouros, Timoleon Isaksson, Ola Andersson, Petter Clarkson, P. John Chalmers University of Technology Industrial and Materials Science Gothenburg Sweden University of Cambridge Department of Engineering Cambridge United Kingdom Gkn Aerospace Engine Systems Department of System Analysis & Ip Trollhattan Sweden

Decisions made in the concept generation phase have a significant effect on the product. While product- related risks typically can be considered in the early stages of design, risks such as supply chain and manufacturing methods are rarely easy to account for in early phases. This is because the currently available methods require mature data, which may not be available during concept generation. In this paper, we propose an approach to address this. First, the product and the non-product (manufacturing and/or supply chain) attributes are modelled using the enhanced function means (EF-M) modelling method. The EF-M method provides the opportunity to model alternative solutions-set for functions. Dependencies are then mapped within the product and the manufacturing models, and also in between them. An automatic combinatorial method of concept generation is employed where each generated instance is a design concept-manufacturing method pair. A risk propagation algorithm is then used to assess the risks of all the generated alternatives. © The Author(s), 2023. Published by Cambridge University Press.

关键词： Supply chains

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Differential Analysis for Networks Obeying Conservation Laws 48

Differential Analysis for Networks Obeying Conservation Laws

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48th IEEE international conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Rayas, Anirudh Anguluri, Rajasekhar Cheng, Jiajun Dasarathy, Gautam School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85281 United States School of Computing and Augmented Intelligence Arizona State University TempeAZ85281 United States

ISBN: (纸本)9781728163277

Networked systems that occur in various domains, such as electric networks, the brain, and opinion networks, are known to obey conservation laws. For instance, electric networks obey Kirchoff's laws, and social networks obey opinion consensus. Conservation laws are often modeled as balance equations that relate appropriate injected flows and potentials at the nodes of the networks. A recent line of work considers the problem of estimating the unknown structure of such networked systems from observations of node potentials (and only the knowledge of the statistics of injected flows). Given the dynamic nature of the systems under consideration, an equally important task is estimating the change in the structure of the network from data - the so called differential network analysis problem. That is, given two sets of node potential observations, the goal is to estimate the structural differences between the underlying networks. We formulate this novel differential network analysis problem for systems obeying conservation laws and devise a convex estimator to learn the edge changes directly from node potentials. We derive conditions under which the estimate is unique in the highdimensional regime and devise an efficient ADMM-based approach to perform the estimation. Finally, we demonstrate the performance of our approach on synthetic and benchmark power network data. © 2023 IEEE.

关键词： ADMM convex optimization differential network analysis sparsity structure learning

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Refining Bird Species Identification through GAN-Enhanced data Augmentation and Deep Learning Models 28th

Refining Bird Species Identification through GAN-Enhanced Da...

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28th international conference on knowledge Based and Intelligent information and engineering systems, KES 2024

作者： Alfatemi, Ali ALJamal, Sarah Paykari, Nasim Rahouti, Mohamed Amin, Ruhul Chehri, Abdellah Department of Computer & Information Science Fordham University BronxNY30332 United States KingstonON Canada

This work addresses the challenge of classifying visually similar bird species, a task complicated by subtle interspecies variations. We focused on ten bird species, assembling a dataset of approximately 8000 images from Google Images. These species were specifically chosen for their high degree of similarity, presenting a unique challenge for classification algorithms. To enhance our dataset and improve classification accuracy, we employed Generative adversarial networks (GANs), a state-of-the-art generative adversarial network, to augment our original dataset with synthetic yet realistic images. This augmentation aimed to provide a more prosperous, diverse training environment for our deep learning model. Subsequently, we developed a specialized multi-classification model tailored to recognize and differentiate these closely related bird species. Integrating GANs like StyleGAN3-augmented data into our training process represents a novel approach to ecological image analysis, potentially setting a new standard for accuracy and efficiency in classifying highly similar species. This study demonstrates the effectiveness of advanced generative models in complex classification tasks and contributes a valuable methodology to ecological research and species identification. © 2024 The Authors.

关键词： Generative adversarial networks

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