IEEE Open Journal of the Computer Society最新文献_第9页

Prediction of Customer Behavior Changing via a Hybrid Approach 通过混合方法预测客户行为变化

IEEE Open Journal of the Computer Society Pub Date : 2023-11-29 DOI: 10.1109/OJCS.2023.3336904

Nien-Ting Lee;Hau-Chen Lee;Joseph Hsin;Shih-Hau Fang

{"title":"Prediction of Customer Behavior Changing via a Hybrid Approach","authors":"Nien-Ting Lee;Hau-Chen Lee;Joseph Hsin;Shih-Hau Fang","doi":"10.1109/OJCS.2023.3336904","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3336904","url":null,"abstract":"This study proposes a hybrid approach to predict customer churn by combining statistic approaches and machine learning models. Unlike traditional methods, where churn is defined by a fixed period of time, the proposed algorithm uses the probability of customer alive derived from the statistical model to dynamically determine the churn line. After observing customer churn through clustering over time, the proposed method segmented customers into four behaviors: new, short-term, high-value, and churn, and selected machine learning models to predict the churned customers. This combination reduces the risk to be misjudged as churn for customers with longer consumption cycles. Two public datasets were used to evaluate the hybrid approach, an online retail of U.K. gift sellers and the largest E-Commerce of Pakistan. Based on the top three learning models, the recall ranged from 0.56 to 0.72 in the former while that ranged from 0.91 to 0.95 in the latter. Results show that the proposed approach enables companies to retain important customers earlier by predicting customer churn. The proposed hybrid method requires less data than existing methods.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"5 ","pages":"27-38"},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10334013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139060318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Real-Time 3-Dimensional Object Detection Based Human Action Recognition Model 基于三维物体检测的实时人体动作识别模型

IEEE Open Journal of the Computer Society Pub Date : 2023-11-20 DOI: 10.1109/OJCS.2023.3334528

Chhaya Gupta;Nasib Singh Gill;Preeti Gulia;Sangeeta Yadav;Giovanni Pau;Mohammad Alibakhshikenari;Xiangjie Kong

{"title":"A Real-Time 3-Dimensional Object Detection Based Human Action Recognition Model","authors":"Chhaya Gupta;Nasib Singh Gill;Preeti Gulia;Sangeeta Yadav;Giovanni Pau;Mohammad Alibakhshikenari;Xiangjie Kong","doi":"10.1109/OJCS.2023.3334528","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3334528","url":null,"abstract":"Computer vision technologies have greatly improved in the last few years. Many problems have been solved using deep learning merged with more computational power. Action recognition is one of society's problems that must be addressed. Human Action Recognition (HAR) may be adopted for intelligent video surveillance systems, and the government may use the same for monitoring crimes and security purposes. This paper proposes a deep learning-based HAR model, i.e., a 3-dimensional Convolutional Network with multiplicative LSTM. The suggested model makes it easier to comprehend the tasks that an individual or team of individuals completes. The four-phase proposed model consists of a 3D Convolutional neural network (3DCNN) combined with an LSTM multiplicative recurrent network and Yolov6 for real-time object detection. The four stages of the proposed model are data fusion, feature extraction, object identification, and skeleton articulation approaches. The NTU-RGB-D, KITTI, NTU-RGB-D 120, UCF 101, and Fused datasets are some used to train the model. The suggested model surpasses other cutting-edge models by reaching an accuracy of 98.23%, 97.65%, 98.76%, 95.45%, and 97.65% on the abovementioned datasets. Other state-of-the-art (SOTA) methods compared in this study are traditional CNN, Yolov6, and CNN with BiLSTM. The results verify that actions are classified more accurately by the proposed model that combines all these techniques compared to existing ones.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"5 ","pages":"14-26"},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10323158","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139060146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Benchmark for Personalized Federated Learning 个性化联合学习的基准

IEEE Open Journal of the Computer Society Pub Date : 2023-11-13 DOI: 10.1109/OJCS.2023.3332351

Koji Matsuda;Yuya Sasaki;Chuan Xiao;Makoto Onizuka

{"title":"Benchmark for Personalized Federated Learning","authors":"Koji Matsuda;Yuya Sasaki;Chuan Xiao;Makoto Onizuka","doi":"10.1109/OJCS.2023.3332351","DOIUrl":"10.1109/OJCS.2023.3332351","url":null,"abstract":"Federated learning is a distributed machine learning approach that allows a single server to collaboratively build machine learning models with multiple clients without sharing datasets. Since data distributions may differ across clients, data heterogeneity is a challenging issue in federated learning. To address this issue, numerous federated learning methods have been proposed to build personalized models for clients, referred to as personalized federated learning. Nevertheless, no studies comprehensively investigate the performance of personalized federated learning methods in various experimental settings such as datasets and client settings. Therefore, in this article, we aim to benchmark the performance of existing personalized federated learning methods in various settings. We first survey the experimental settings in existing studies. We then benchmark the performance of existing methods through comprehensive experiments to reveal their characteristics in computer vision and natural language processing tasks which are the most popular tasks based on our survey. Our experimental study shows that (i) large data heterogeneity often leads to highly accurate predictions and (ii) standard federated learning methods (e.g. FedAvg) with fine-tuning often outperform personalized federated learning methods.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"5 ","pages":"2-13"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10316561","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135612465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data Extraction and Question Answering on Chart Images Towards Accessibility and Data Interpretation 面向可及性和数据解释的图表图像数据提取与问答

IEEE Open Journal of the Computer Society Pub Date : 2023-10-31 DOI: 10.1109/OJCS.2023.3328767

Shahira K C;Pulkit Joshi;Lijiya A

{"title":"Data Extraction and Question Answering on Chart Images Towards Accessibility and Data Interpretation","authors":"Shahira K C;Pulkit Joshi;Lijiya A","doi":"10.1109/OJCS.2023.3328767","DOIUrl":"10.1109/OJCS.2023.3328767","url":null,"abstract":"Graphical representations such as chart images are integral to web pages and documents. Automating data extraction from charts is possible by reverse-engineering the visualization pipeline. This study proposes a framework that automates data extraction from bar charts and integrates it with question-answering. The framework employs an object detector to recognize visual cues in the image, followed by text recognition. Mask-RCNN for plot element detection achieves a mean average precision of 95.04% at a threshold of 0.5 which decreases as the Intersection over Union (IoU) threshold increases. A contour approximation-based approach is proposed for extracting the bar coordinates, even at a higher IoU of 0.9. The textual and visual cues are associated with the legend text and preview, and the chart data is finally extracted in tabular format. We introduce an extension to the TAPAS model, called TAPAS++, by incorporating new operations and table question answering is done using TAPAS++ model. The chart summary or description is also produced in an audio format. In the future, this approach could be expanded to enable interactive question answering on charts by accepting audio inquiries from individuals with visual impairments and do more complex reasoning using Large Language Models.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"314-325"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10302417","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135263025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finding the Truth From Uncertain Time Series by Differencing 用差分法从不确定时间序列中求真

IEEE Open Journal of the Computer Society Pub Date : 2023-10-19 DOI: 10.1109/OJCS.2023.3326150

Jizhou Sun;Delin Zhou;Bo Jiang

引用次数: 0

Towards Reliable Utilization of AIGC: Blockchain-Empowered Ownership Verification Mechanism 走向AIGC的可靠利用:区块链授权的所有权验证机制

IEEE Open Journal of the Computer Society Pub Date : 2023-09-18 DOI: 10.1109/OJCS.2023.3315835

Chuan Chen;Yihao Li;Zihou Wu;Mingfeng Xu;Rui Wang;Zibin Zheng

{"title":"Towards Reliable Utilization of AIGC: Blockchain-Empowered Ownership Verification Mechanism","authors":"Chuan Chen;Yihao Li;Zihou Wu;Mingfeng Xu;Rui Wang;Zibin Zheng","doi":"10.1109/OJCS.2023.3315835","DOIUrl":"10.1109/OJCS.2023.3315835","url":null,"abstract":"With the development of the blockchain technology, a decentralized and de-trusted network paradigm has been constructed, enabling multiple digital assets like NFT, to be permanently recorded and authenticated by blockchain. Also, the uniqueness and verifiability of these assets allows them to flow and generate value between any network entities. With the emergence of AI Generative Content (AIGC), the ownership of models and generative contents, which are also digital assets, has not been well protected. Both because the black-box nature of neural networks makes it difficult to mark models' ownership and because the lack of a reliable third-party verification platform. Meanwhile, the existing model-attack threat and raising ethical problems driven the research on model watermark embedding for traceability and verification, and thus the reliable basic algorithm and the verification platform are needed. In this survey, while emphasizing the importance and reason of the ownership protection in AIGC and summarizing the recent research using model watermarking, we will also introduce the achievements of blockchain in copyright in order to summarize the research history and point out future direction of model copyright validation from both the underlying technology and the supporting platform.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"326-337"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10254223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135502429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time High-Quality Visualization for Volumetric Contents Rendering: A Lyapunov Optimization Framework 体积内容绘制的实时高质量可视化：一个Lyapunov优化框架

IEEE Open Journal of the Computer Society Pub Date : 2023-09-06 DOI: 10.1109/OJCS.2023.3312371

Hankyul Baek;Rhoan Lee;Soyi Jung;Joongheon Kim;Soohyun Park

引用次数: 0

MetaCIDS: Privacy-Preserving Collaborative Intrusion Detection for Metaverse based on Blockchain and Online Federated Learning MetaCIDS:基于区块链和在线联合学习的Metaverse隐私保护协同入侵检测

IEEE Open Journal of the Computer Society Pub Date : 2023-09-05 DOI: 10.1109/OJCS.2023.3312299

Vu Tuan Truong;Long Bao Le

{"title":"MetaCIDS: Privacy-Preserving Collaborative Intrusion Detection for Metaverse based on Blockchain and Online Federated Learning","authors":"Vu Tuan Truong;Long Bao Le","doi":"10.1109/OJCS.2023.3312299","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3312299","url":null,"abstract":"Metaverse is expected to rely on massive Internet of Things (IoT) connections so it inherits various security threats from the IoT network and also faces other sophisticated attacks related to virtual reality technology. As traditional security approaches show various limitations in the large-scale distributed metaverse, this paper proposes MetaCIDS, a novel collaborative intrusion detection (CID) framework that leverages metaverse devices to collaboratively protect the metaverse. In MetaCIDS, a federated learning (FL) scheme based on unsupervised autoencoder and an attention-based supervised classifier enables metaverse users to train a CID model using their local network data, while the blockchain network allows metaverse users to train a machine learning (ML) model to detect intrusion network flows over their monitored local network traffic, then submit verifiable intrusion alerts to the blockchain to earn metaverse tokens. Security analysis shows that MetaCIDS can efficiently detect zero-day attacks, while the training process is resistant to SPoF, data tampering, and up to 33% poisoning nodes. Performance evaluation illustrates the efficiency of MetaCIDS with 96% to 99% detection accuracy on four different network intrusion datasets, supporting both multi-class detection using labeled data and anomaly detection trained on unlabeled data.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"253-266"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10239541.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Co-Existence With IEEE 802.11 Networks in the ISM Band Without Channel Estimation 在没有信道估计的ISM频带中与IEEE 802.11网络共存

IEEE Open Journal of the Computer Society Pub Date : 2023-08-31 DOI: 10.1109/OJCS.2023.3310913

Muhammad Naveed Aman;Muhammad Ishfaq;Biplab Sikdar

{"title":"Co-Existence With IEEE 802.11 Networks in the ISM Band Without Channel Estimation","authors":"Muhammad Naveed Aman;Muhammad Ishfaq;Biplab Sikdar","doi":"10.1109/OJCS.2023.3310913","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3310913","url":null,"abstract":"Any new deployment of networks in the industrial, scientific, and medical (ISM) band, even though it is license-free, has to co-exist with IEEE 802.11 networks. IoT devices are typically deployed in the ISM band, creating a spectrum bottleneck for competing networks. This article investigates the issue of co-existence of wireless networks with WiFi networks. In our scenario, we consider WiFi as the “primary” or higher priority network co-existing with multiple “secondary” networks that may be used for low priority devices, with both networks operating in the ISM band. Towards this end, we first develop an analytical model for a metric called the “received symbol distance” at the primary receiver to obtain a power control parameter for secondary users. This power control parameter is used to scale the power of the secondary user according to the wireless channel between the primary transmitter and primary receiver. The proposed approach is computationally simple and does not require any estimation of channel coefficients. Simulation results show that the proposed technique can be used to effectively increase the spectrum utilization and the probability of a successful transmission by the secondary user, while not having any harmful effect on the primary user.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"267-279"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10236489.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Identity-Based Adaptor Signature Scheme and its Applications in the Blockchain System 一种基于身份的适配器签名方案及其在区块链系统中的应用

IEEE Open Journal of the Computer Society Pub Date : 2023-08-29 DOI: 10.1109/OJCS.2023.3309836

Zijian Bao;Debiao He;Cong Peng;Min Luo;Kim-Kwang Raymond Choo

{"title":"An Identity-Based Adaptor Signature Scheme and its Applications in the Blockchain System","authors":"Zijian Bao;Debiao He;Cong Peng;Min Luo;Kim-Kwang Raymond Choo","doi":"10.1109/OJCS.2023.3309836","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3309836","url":null,"abstract":"Adaptor signature, as a new emerging cryptographic primitive, has become one promising method to mitigate the \u0000<italic>scalability</i>\u0000 issue on blockchain. It can transform an incomplete signature into a complete signature by revealing the witness of a pre-set hard relation, which can be applied to atomic swap, payment channel, payment hub, and other blockchain scenarios. Recently, a general transformation for constructing adaptor signatures has been proposed for some signature schemes with specific structures, e.g., Schnorr, ECDSA, SM2 signatures. However, we note that there is no identity-based adaptor signature method so far. In this article, we put forward an adaptor signature scheme for the identity-based signature scheme in the IEEE P1363 standard. Then, we formally prove the security of our scheme under the random oracle model. We also present the computation and communication costs, compared with other adaptor signatures. Finally, we show our scheme's potential use in atomic swaps and payment channel networks of blockchain.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"231-242"},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10234020.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0