计算机科学最新文献_第9页

On real and observable rational realizations of input–output equations

IF 2.1 3区计算机科学

Systems & Control Letters Pub Date : 2025-03-05 DOI: 10.1016/j.sysconle.2025.106059

Sebastian Falkensteiner , Dmitrii Pavlov , J. Rafael Sendra

{"title":"On real and observable rational realizations of input–output equations","authors":"Sebastian Falkensteiner , Dmitrii Pavlov , J. Rafael Sendra","doi":"10.1016/j.sysconle.2025.106059","DOIUrl":"10.1016/j.sysconle.2025.106059","url":null,"abstract":"<div><div>Given a single (differential–algebraic) input–output equation, we present a method for finding different representations of the associated system in the form of rational realizations; these are dynamical systems with rational right-hand sides. It has been shown that in the case where the input–output equation is of order one, rational realizations can be computed, if they exist. In this work, we focus first on the existence and actual computation of the so-called observable rational realizations, and secondly on rational realizations with real coefficients. The study of observable realizations allows to find every rational realization of a given first order input–output equation, and the necessary field extensions in this process. We show that for first order input–output equations the existence of a rational realization is equivalent to the existence of an observable rational realization. Moreover, we give a criterion to decide the existence of real rational realizations. The computation of observable and real realizations of first order input–output equations is fully algorithmic. We also present partial results for the case of higher order input–output equations.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"198 ","pages":"Article 106059"},"PeriodicalIF":2.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

One-class graph autoencoder: A new end-to-end, low-dimensional, and interpretable approach for node classification

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-03-05 DOI: 10.1016/j.ins.2025.122060

Marcos Paulo Silva Gôlo, José Gilberto Barbosa de Medeiros Junior, Diego Furtado Silva, Ricardo Marcondes Marcacini

{"title":"One-class graph autoencoder: A new end-to-end, low-dimensional, and interpretable approach for node classification","authors":"Marcos Paulo Silva Gôlo, José Gilberto Barbosa de Medeiros Junior, Diego Furtado Silva, Ricardo Marcondes Marcacini","doi":"10.1016/j.ins.2025.122060","DOIUrl":"10.1016/j.ins.2025.122060","url":null,"abstract":"<div><div>One-class learning (OCL) for graph neural networks (GNNs) comprises a set of techniques applied when real-world problems are modeled through graphs and have a single class of interest. These methods may employ a two-step strategy: first representing the graph and then classifying its nodes. End-to-end methods learn the node representations while classifying the nodes in OCL process. We highlight three main gaps in this literature: (i) non-customized representations for OCL; (ii) the lack of constraints on hypersphere learning; and (iii) the lack of interpretability. This paper presents <strong><u>O</u></strong>ne-c<strong><u>L</u></strong>ass <strong><u>G</u></strong>raph <strong><u>A</u></strong>utoencoder (OLGA), a new OCL for GNN approach. OLGA is an end-to-end method that learns low-dimensional representations for nodes while encapsulating interest nodes through a proposed and new hypersphere loss function. Furthermore, OLGA combines this new hypersphere loss with the graph autoencoder reconstruction loss to improve model learning. The reconstruction loss is a constraint to the sole use of the hypersphere loss that can bias the model to encapsulate all nodes. Finally, our low-dimensional representation makes the OLGA interpretable since we can visualize the representation learning at each epoch. OLGA achieved state-of-the-art results and outperformed six other methods with statistical significance while maintaining the learning process interpretability with its low-dimensional representations.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"708 ","pages":"Article 122060"},"PeriodicalIF":8.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the Transformative Impact of Blockchain Technology on Healthcare: Security, Challenges, Benefits, and Future Outlook

IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2025-03-05 DOI: 10.1002/ett.70087

Anita Thakur, Virender Ranga, Ritu Agarwal

{"title":"Exploring the Transformative Impact of Blockchain Technology on Healthcare: Security, Challenges, Benefits, and Future Outlook","authors":"Anita Thakur, Virender Ranga, Ritu Agarwal","doi":"10.1002/ett.70087","DOIUrl":"https://doi.org/10.1002/ett.70087","url":null,"abstract":"<div>\u0000 \u0000 <p>This study aims to methodically explore the diverse applications of blockchain technology (BT) within the healthcare domain. Additionally, it seeks to analyze the inherent challenges of integrating BT into healthcare systems. Furthermore, this study elucidates blockchain's advantageous contributions to the healthcare domain. The suggested research thoroughly reviews the literature from various databases, using predetermined criteria, such as exclusion and inclusion, to identify pertinent studies. It also demonstrates the properties of blockchain and its functionality for the patient, healthcare providers, or overall healthcare infrastructure to assist the healthcare industry in a contemporary direction. The substantial advantages of BT within the medical field are notable. However, it is vital to acknowledge the security vulnerabilities by employing a blockchain-centered strategy to mitigate these challenges, allowing for the creation of a robust and streamlined system and framework. The importance of this study is that as this investigation navigates the convergence of healthcare and BT, it not only delineates the multifaceted applications of BT but also meticulously examines the associated security challenges. The findings of this study chart a course toward a technologically advanced, secure, and efficient healthcare ecosystem, improving patient outcomes and reshaping the future of healthcare delivery worldwide.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Transactions on Broadcasting Information for Authors

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-03-05 DOI: 10.1109/TBC.2025.3542626

引用次数: 0

Flamingo Lyrebird Optimization-Based Holistic Approach for Improving RFID-WSN Integrated Network Lifetime

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-05 DOI: 10.1002/dac.70036

V. Rajesh, A. Kaleel Rahuman

{"title":"Flamingo Lyrebird Optimization-Based Holistic Approach for Improving RFID-WSN Integrated Network Lifetime","authors":"V. Rajesh, A. Kaleel Rahuman","doi":"10.1002/dac.70036","DOIUrl":"https://doi.org/10.1002/dac.70036","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless sensor networks (WSNs) are considered a key foundation for high-level Internet of Things (IoT) practices. Moreover, WSNs depend on transmission for data transfer among sink modules and sensor nodes or intermediate points in the system. However, in WSN, there are several interruptions during the transmission of data. Further, storage space, network bandwidth, and processing power are limited, and hence, it is significant to enhance data distribution to improve network performance. Therefore, this paper devised a new approach known as the Flamingo Lyrebird Optimization Algorithm (FLOA) to improve radio frequency identification (RFID)-WSN integrated network lifetime. Firstly, the network topology of WSN-RFID is simulated, and then cluster head (CH) selection is performed by FLOA in terms of multiobjective fitness, namely, energy, network lifetime, and inter- and intracluster distance. Here, FLOA is formed by integrating Flamingo Search Optimization (FSA) and Lyrebird Optimization Algorithm (LOA). After this, the energy-efficient multipath routing is performed by utilizing FLOA, where link life time (LLT) and energy are predicted using a gated recurrent unit (GRU). Furthermore, FLOA attained the maximum performance with network lifetime and energy of 820.11, 0.923 J, and minimum delay of 0.211 s.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BET-BiLSTM Model: A Robust Solution for Automated Requirements Classification

IF 1.7 4区计算机科学

Journal of Software-Evolution and Process Pub Date : 2025-03-05 DOI: 10.1002/smr.70012

Jalil Abbas, Cheng Zhang, Bin Luo

{"title":"BET-BiLSTM Model: A Robust Solution for Automated Requirements Classification","authors":"Jalil Abbas, Cheng Zhang, Bin Luo","doi":"10.1002/smr.70012","DOIUrl":"https://doi.org/10.1002/smr.70012","url":null,"abstract":"<div>\u0000 \u0000 <p>Transformer methods have revolutionized software requirements classification by combining advanced natural language processing to accurately understand and categorize requirements. While traditional methods like Doc2Vec and TF-IDF are useful, they often fail to capture the deep contextual relationships and subtle meanings inherent in textual data. Transformer models possess unique strengths and weaknesses, impacting their ability to capture various aspects of the data. Consequently, relying on a single model can lead to suboptimal feature representations, limiting the overall performance of the classification task. To address this challenge, our study introduces an innovative BET-BiLSTM (balanced ensemble transformers using Bi-LSTM) model. This model combines the strengths of five transformer–based models BERT, RoBERTa, XLNet, GPT-2, and T5 through weighted averaging ensemble, resulting in a sophisticated and resilient feature set. By employing data balancing techniques, we ensure a well-distributed representation of features, addressing the issue of class imbalance. The BET-BiLSTM model plays a crucial role in the classification process, achieving an impressive accuracy of 96%. Moreover, the practical applicability of this model is validated through its successful implementation on three publicly available unlabeled datasets and one additional labeled dataset. The model significantly improved the completeness and reliability of these datasets by accurately predicting labels for previously unclassified requirements. This makes our approach a powerful tool for large-scale requirements analysis and classification tasks, outperforming traditional single-model methods and showcasing its real-world effectiveness.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"37 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A parallel weighted ADTC-Transformer framework with FUnet fusion and KAN for improved lithium-ion battery SOH prediction

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-03-05 DOI: 10.1016/j.conengprac.2025.106302

Chuang Chen , Yuheng Wu , Jiantao Shi , Dongdong Yue , Ge Shi , Dongzhen Lyu

{"title":"A parallel weighted ADTC-Transformer framework with FUnet fusion and KAN for improved lithium-ion battery SOH prediction","authors":"Chuang Chen , Yuheng Wu , Jiantao Shi , Dongdong Yue , Ge Shi , Dongzhen Lyu","doi":"10.1016/j.conengprac.2025.106302","DOIUrl":"10.1016/j.conengprac.2025.106302","url":null,"abstract":"<div><div>This paper delves into the extraction and integration of local and global features for lithium-ion battery State of Health (SOH) prediction, proposing an innovative parallel weighted architecture—ADTC-Transformer. This framework combines Adaptive Dilated Temporal Convolution (ADTC) with a Transformer encoder to effectively capture and balance local and global dependencies while dynamically optimizing feature contributions through a weighted fusion mechanism. Additionally, the traditional U-shaped network (Unet) is enhanced by incorporating a Feature Pyramid Network (FPN), forming the FUnet module, which significantly strengthens the fusion and utilization of multi-scale features. Building on this, the Kolmogorov–Arnold Network (KAN) is introduced as the final prediction module, leveraging Kolmogorov–Arnold representation theory to model complex high-dimensional features through local interpolation and global nonlinear transformations. This enables the KAN module to capture intricate temporal dependencies and interactions across a wide range of feature scales, thus improving the model’s ability to predict long-term SOH. Experimental results demonstrate that the proposed method markedly improves prediction accuracy across NASA, CALCE, and WRBD datasets, excelling particularly in long-term SOH prediction for lithium-ion batteries. This provides robust support for battery health management and performance optimization.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106302"},"PeriodicalIF":5.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ensemble Quality-Aware Slow Feature Analysis for decentralized dynamic process monitoring

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2025-03-05 DOI: 10.1016/j.jprocont.2025.103400

Yuanhui Ni , Chao Jiang

{"title":"Ensemble Quality-Aware Slow Feature Analysis for decentralized dynamic process monitoring","authors":"Yuanhui Ni , Chao Jiang","doi":"10.1016/j.jprocont.2025.103400","DOIUrl":"10.1016/j.jprocont.2025.103400","url":null,"abstract":"<div><div>Slow Feature Analysis (SFA) has gained prominence in process monitoring due to its capability to capture inertial features in industrial systems. However, traditional SFA methods are predominantly unsupervised and often neglect output quality, limiting their effectiveness in large-scale, complex systems. To address these limitations, this paper introduces the Ensemble Quality-Aware Slow Feature Analysis (EQASFA) framework, which maximizes the correlation between quality variables and slow features. This decentralized monitoring framework generates fine-grained submodels by: (i) constructing a diverse set of submodels through different variable combinations, and (ii) selecting base submodels with the lowest false alarm rate on the validation dataset. The selection process utilizes a divisive hierarchical clustering algorithm, where probabilistic similarity is quantified using symmetric Kullback–Leibler divergence. In addition, novel static and dynamic metrics, derived from Bayesian inference, are proposed to distinguish routine operational fluctuations from significant anomalies. The performance of the EQASFA framework is validated through two benchmark case studies: the Tennessee Eastman process and a wastewater treatment process.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"148 ","pages":"Article 103400"},"PeriodicalIF":3.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A weighted graph network-based method for combining conflicting evidence

IF 7.5 2区计算机科学

Engineering Applications of Artificial Intelligence Pub Date : 2025-03-05 DOI: 10.1016/j.engappai.2025.110351

Jinjian Lin, Kai Xie

引用次数: 0

Improved data-driven model-free adaptive control method for an upper extremity power-assist exoskeleton

IF 3.4 2区计算机科学

Applied Intelligence Pub Date : 2025-03-05 DOI: 10.1007/s10489-025-06415-3

Shurun Wang, Hao Tang, Zhaowu Ping, Qi Tan, Bin Wang

{"title":"Improved data-driven model-free adaptive control method for an upper extremity power-assist exoskeleton","authors":"Shurun Wang, Hao Tang, Zhaowu Ping, Qi Tan, Bin Wang","doi":"10.1007/s10489-025-06415-3","DOIUrl":"10.1007/s10489-025-06415-3","url":null,"abstract":"<div><p>The widespread application of power-assist exoskeletons in physical labor and daily activities has increased the demand for robust control strategies to address challenges in human-exoskeleton interaction. Factors such as collisions and friction introduce uncertain disturbances, making it difficult to establish an accurate human-exoskeleton interaction model, thereby limiting the applicability of current model-based control methods. To overcome these problems, this study proposes an improved data-driven model-free adaptive control method (IMFAC) for the upper extremity power-assist exoskeleton. The stability and convergence of the closed-loop system are rigorously proven. To optimize the initial conditions of IMFAC, we propose an improved snake optimizer (ISO) algorithm incorporating opposition-based learning. The proposed ISO-IMFAC method is evaluated in two scenarios: a nonlinear Hammerstein model benchmark and a physical exoskeleton platform. Experimental results demonstrate that ISO-IMFAC outperforms other popular data-driven control methods across six metrics: integrated absolute error (4.756), mean integral of time-weighted absolute error (0.457), maximum error (1.167), minimum error (0), mean error (0.032), and error standard deviation (0.169). Additionally, the ISO-IMFAC method effectively drives the exoskeleton without relying on its dynamic model. In two load-bearing experiments conducted with five subjects wearing the exoskeleton, the proposed method reduces average muscle exertion per unit time by over 50% and extended working time by more than 180%. These findings highlight the significant potential of the proposed method to enhance user endurance and reduce physical strain, paving the way for practical applications in diverse real-world scenarios. The code is released at https://github.com/Shurun-Wang/ISO-IMFAC.</p></div>","PeriodicalId":8041,"journal":{"name":"Applied Intelligence","volume":"55 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0