Big Data and Cognitive Computing最新文献_第8页

Digital Twin Four-Dimension Fusion Modeling Method Design and Application to the Discrete Manufacturing Line 数字孪生四维融合建模方法在离散生产线中的设计与应用

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-05-08 DOI: 10.3390/bdcc7020089

Jieyu Xie, J. Wan

{"title":"Digital Twin Four-Dimension Fusion Modeling Method Design and Application to the Discrete Manufacturing Line","authors":"Jieyu Xie, J. Wan","doi":"10.3390/bdcc7020089","DOIUrl":"https://doi.org/10.3390/bdcc7020089","url":null,"abstract":"With the development of new-generation information technologies, such as big data and artificial intelligence, digital twins have become a key technology in intelligent manufacturing. The introduction of digital twin technology has addressed many problems in discrete manufacturing lines, including low visualization and difficult cyber–physical integration. However, the application of digital twin technology to discrete manufacturing lines still faces problems of low modeling accuracy, response delay, and insufficient production line control accuracy. Therefore, this paper proposes a digital twin four-dimension fusion modeling method to solve the above problems. First, a digital twin system architecture for a discrete manufacturing production line is designed. Then, the information control dimension is integrated into traditional digital twin modeling methods. Further, a digital twin geometry–physics–behavior–information control four-dimension fusion modeling method is proposed. This method can describe the geometric and physical characteristics of a physical entity and map its behavior mechanism. More importantly, it reveals the control logic and virtual–real mapping rules, which provides important support for the virtual–real intelligent mutual control. Finally, the feasibility and effectiveness of the proposed method are verified by experiments on a fidget spinner discrete manufacturing line, and a digital twin operation and maintenance management system is developed. The results presented in this study could provide ideas for the digital transformation of discrete manufacturing enterprises.","PeriodicalId":36397,"journal":{"name":"Big Data and Cognitive Computing","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48779469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An Ensemble-Learning-Based Technique for Bimodal Sentiment Analysis 基于集成学习的双峰情感分析技术

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-30 DOI: 10.3390/bdcc7020085

Shariq Shah, Hossein Ghomeshi, Edlira Vakaj, Emmett Cooper, Rasheed Mohammad

引用次数: 2

A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption 基于同态加密的安全外包矩阵乘法的比较研究

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-28 DOI: 10.3390/bdcc7020084

M. Babenko, E. Golimblevskaia, A. Tchernykh, E. Shiriaev, Tatiana Ermakova, Luis Bernardo Pulido-Gaytan, G. Valuev, A. Avetisyan, Lana A. Gagloeva

{"title":"A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption","authors":"M. Babenko, E. Golimblevskaia, A. Tchernykh, E. Shiriaev, Tatiana Ermakova, Luis Bernardo Pulido-Gaytan, G. Valuev, A. Avetisyan, Lana A. Gagloeva","doi":"10.3390/bdcc7020084","DOIUrl":"https://doi.org/10.3390/bdcc7020084","url":null,"abstract":"Homomorphic encryption (HE) is a promising solution for handling sensitive data in semi-trusted third-party computing environments, as it enables processing of encrypted data. However, applying sophisticated techniques such as machine learning, statistics, and image processing to encrypted data remains a challenge. The computational complexity of some encrypted operations can significantly increase processing time. In this paper, we focus on the analysis of two state-of-the-art HE matrix multiplication algorithms with the best time and space complexities. We show how their performance depends on the libraries and the execution context, considering the standard Cheon–Kim–Kim–Song (CKKS) HE scheme with fixed-point numbers based on the Microsoft SEAL and PALISADE libraries. We show that Windows OS for the SEAL library and Linux OS for the PALISADE library are the best options. In general, PALISADE-Linux outperforms PALISADE-Windows, SEAL-Linux, and SEAL-Windows by 1.28, 1.59, and 1.67 times on average for different matrix sizes, respectively. We derive high-precision extrapolation formulas to estimate the processing time of HE multiplication of larger matrices.","PeriodicalId":36397,"journal":{"name":"Big Data and Cognitive Computing","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43712048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Dataset for Optimal Circulant Topologies 最优循环拓扑的数据集

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-20 DOI: 10.3390/bdcc7020080

A. Romanov

引用次数: 0

Analyzing Online Fake News Using Latent Semantic Analysis: Case of USA Election Campaign 利用潜在语义分析分析网络假新闻:以美国大选为例

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-20 DOI: 10.3390/bdcc7020081

Richard G. Mayopu, Yi-Yun Wang, Long-Sheng Chen

{"title":"Analyzing Online Fake News Using Latent Semantic Analysis: Case of USA Election Campaign","authors":"Richard G. Mayopu, Yi-Yun Wang, Long-Sheng Chen","doi":"10.3390/bdcc7020081","DOIUrl":"https://doi.org/10.3390/bdcc7020081","url":null,"abstract":"Recent studies have indicated that fake news is always produced to manipulate readers and that it spreads very fast and brings great damage to human society through social media. From the available literature, most studies focused on fake news detection and identification and fake news sentiment analysis using machine learning or deep learning techniques. However, relatively few researchers have paid attention to fake news analysis. This is especially true for fake political news. Unlike other published works which built fake news detection models from computer scientists’ viewpoints, this study aims to develop an effective method that combines natural language processing (NLP) and latent semantic analysis (LSA) using singular value decomposition (SVD) techniques to help social scientists to analyze fake news for discovering the exact elements. In addition, the authors analyze the characteristics of true news and fake news. A real case from the USA election campaign in 2016 is employed to demonstrate the effectiveness of our methods. The experimental results could give useful suggestions to future researchers to distinguish fake news. This study finds the five concepts extracted from LSA and that they are representative of political fake news during the election.","PeriodicalId":36397,"journal":{"name":"Big Data and Cognitive Computing","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47156950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Multi-Modal Entity Alignment Method with Inter-Modal Enhancement 一种具有模态间增强的多模态实体对齐方法

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-18 DOI: 10.3390/bdcc7020077

Song Yuan, Zexin Lu, Qiyuan Li, J. Gu

引用次数: 1

Managing and Optimizing Big Data Workloads for On-Demand User Centric Reports 管理和优化以按需用户为中心的报告的大数据工作量

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-18 DOI: 10.3390/bdcc7020078

A. Băicoianu, Ion Valentin Scheianu

引用次数: 0

National Payment Switches and the Power of Cognitive Computing against Fintech Fraud 国家支付转换与认知计算对抗金融科技欺诈的力量

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-17 DOI: 10.3390/bdcc7020076

A. Faccia

{"title":"National Payment Switches and the Power of Cognitive Computing against Fintech Fraud","authors":"A. Faccia","doi":"10.3390/bdcc7020076","DOIUrl":"https://doi.org/10.3390/bdcc7020076","url":null,"abstract":"National Payment Switches (NPSs) and International Payment Switches (IPSs), including major players such as SWIFT, Mastercard, and CHIPS, have become vital to the financial infrastructure, facilitating secure and efficient transactions among local financial institutions. Nonetheless, the growing adoption of digital payments has heightened the risk of financial fraud. Consequently, NPSs, under the direct ownership of Central Banks (CBs), are increasingly adopting advanced technologies, such as cognitive computing, to bolster their fraud detection capabilities in their respective countries. This article delves into the role of cognitive computing in detecting financial fraud within NPSs. It examines the advantages of cognitive computing in recognising patterns of fraudulent behaviour and analysing vast amounts of data. Additionally, the study highlights the importance of focusing on how cognitive computing can augment traditional fraud detection methods, such as rule-based systems and data analytics. Nineteen real-world cases from eighteen countries are analysed, exploring the cognitive computing tools employed by NPSs to identify fraudulent transactions. The challenges and limitations of implementing cognitive computing in fraud detection and potential solutions to address these issues are identified. The primary assumption that cognitive computing is crucial for detecting financial fraud in NPSs is substantiated. Its ability to analyse large datasets and pinpoint patterns of fraudulent behaviour proves invaluable for financial institutions seeking to protect themselves against financial fraud in a progressively digital world. The conclusions drawn from the overview of the cases aim to identify best practices, potentially trigger new benchmarking standards, and facilitate the development of integrated cross-border solutions to combat financial fraud on a global scale effectively. The purpose of this research is to examine the role of cognitive computing in detecting financial fraud within NPSs, identify its advantages, challenges and limitations, and provide real-world case examples.","PeriodicalId":36397,"journal":{"name":"Big Data and Cognitive Computing","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48783390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Review of Social Media Data Utilization for the Prediction of Disease Outbreaks and Understanding Public Perception 社交媒体数据在疾病爆发预测和理解公众认知中的应用综述

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-12 DOI: 10.3390/bdcc7020072

Alice Wang, R. Dara, Samira Yousefinaghani, Emily Maier, S. Sharif

{"title":"A Review of Social Media Data Utilization for the Prediction of Disease Outbreaks and Understanding Public Perception","authors":"Alice Wang, R. Dara, Samira Yousefinaghani, Emily Maier, S. Sharif","doi":"10.3390/bdcc7020072","DOIUrl":"https://doi.org/10.3390/bdcc7020072","url":null,"abstract":"Infectious diseases take a large toll on the global population, not only through risks of illness but also through economic burdens and lifestyle changes. With both emerging and re-emerging infectious diseases increasing in number, mitigating the consequences of these diseases is a growing concern. The following review discusses how social media data, with a focus on textual Twitter data, can be collected and processed to perform disease surveillance and understand the public’s attitude toward policies around the control of emerging infectious diseases. In this paper, we review machine learning tools and approaches that were used to determine the correlation between social media activity in disease trends within regions, understand the public’s opinion, or public health leaders’ approaches to disease presentation. While recent models migrated toward popular deep learning methods, neural networks and algorithms that optimized existing models were also explored as new standards for social media data analysis in disease prediction and monitoring. As adherence to public health policies can be improved by understanding and responding to major concerns identified by sentiment analyses, the advancements and challenges in understanding text sentiment are also discussed. Recent sentiment classifiers include more complex classifications and can even recognize epidemiological considerations that affect the spread of outbreaks. The comprehensive integration of locational and epidemiological considerations with advanced modeling capabilities and sentiment analysis will produce robust models and more precision for both disease monitoring and prediction. Accurate real-time disease outbreak prediction models will provide health organizations with the capability to address public concerns and to initiate outbreak responses proactively rather than reactively.","PeriodicalId":36397,"journal":{"name":"Big Data and Cognitive Computing","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47686492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Island Design Camps—Interactive Video Projections as Extended Realities 岛屿设计营-互动视频投影作为扩展现实

IF 3.7

Big Data and Cognitive Computing Pub Date : 2023-04-12 DOI: 10.3390/bdcc7020071

{"title":"Island Design Camps—Interactive Video Projections as Extended Realities","authors":"","doi":"10.3390/bdcc7020071","DOIUrl":"https://doi.org/10.3390/bdcc7020071","url":null,"abstract":"Over the course of seven years during ten events, the author explored real-time interactive audiovisual projections, using ad hoc and portable projectorions and audio systems. This was done in the specific location of Cockatoo Island in the waters of a part of Sydney Harbour, Australia. The island offers a unique combination of the remnants of a shipyard industrial precinct, other buildings, and increasingly restored natural environment. The project explored real-time audiovisual responses through projected overlays reminiscing the rich history and past events, interactively resonating with the current landscape and built environment. This included the maritime industrial history, as well as other historical layers such as convict barracks, school, and the significance of the location for Australia’s original inhabitants before colonisation by the British started in 1788. But most prominently, the recent use of the island for large scale art projects (such as the Outpost street art festival in 2011, and over a decade of use as part of the Sydney Biennale of Art, and the use of the island for film sets). This was a rich source of image material collected by the author and used to extend and reflect on current realities. By using the projections, overlaying and extending the present reality with historical data in the form of sounds and video, dialogues were facilitated and a conflation of past and present explored. The main activity were the VideoWalks, where the author, using a custom built portable audiovisual projection system and a bank of audiovisual material was able to re-place sound and video of previous events in the present context, in some instances whilst delivering a performative lecture on the way. The explorations are part of the author’s Traces project, exploring traces and remnants of past events and how these can inform design approaches. The project over the years also developed an element of recursion, by using footage of an earlier projection into the current, the footage of which was then used in the next event, and so on—up to five layers of extended reality.","PeriodicalId":36397,"journal":{"name":"Big Data and Cognitive Computing","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45374720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0