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281 Results Found

  • Article
  • Open Access
1,412 Views
13 Pages

19 August 2024

Many individuals aspire to start their own businesses and achieve financial success. Before launching a business, they must decide on a location and the type of service to offer. This decision requires collecting and analyzing various characteristics...

  • Article
  • Open Access
3 Citations
5,044 Views
12 Pages

27 June 2019

Non-negative tensor factorization (NTF) is a widely used multi-way analysis approach that factorizes a high-order non-negative data tensor into several non-negative factor matrices. In NTF, the non-negative rank has to be predetermined to specify the...

  • Article
  • Open Access
3 Citations
4,477 Views
19 Pages

9 March 2020

Low-rank tensor factorization can not only mine the implicit relationships between data but also fill in the missing data when working with complex data. Compared with the traditional collaborative filtering (CF) algorithm, the changes are essentiall...

  • Article
  • Open Access
11 Citations
4,164 Views
27 Pages

21 August 2019

Hyperspectral and light detection and ranging (LiDAR) data fusion and classification has been an active research topic, and intensive studies have been made based on mathematical morphology. However, matrix-based concatenation of morphological featur...

  • Article
  • Open Access
10 Citations
2,703 Views
18 Pages

14 January 2022

Recently, unmixing methods based on nonnegative tensor factorization have played an important role in the decomposition of hyperspectral mixed pixels. According to the spatial prior knowledge, there are many regularizations designed to improve the pe...

  • Article
  • Open Access
13 Citations
3,890 Views
26 Pages

4 September 2019

The incipient damages of mechanical equipment excite weak impulse vibration, which is hidden, almost unobservable, in the collected signal, making fault detection and failure prevention at the inchoate stage rather challenging. Traditional feature ex...

  • Article
  • Open Access
1,367 Views
16 Pages

6 June 2025

In structural health monitoring (SHM), ensuring data completeness is critical for enhancing the accuracy and reliability of structural condition assessments. SHM data are prone to random missing values due to signal interference or connectivity issue...

  • Article
  • Open Access
3 Citations
3,009 Views
24 Pages

The rapid development of big data technology and mobile intelligent devices has led to the development of location-based social networks (LBSNs). To understand users’ behavioral patterns and improve the accuracy of location-based services, poin...

  • Article
  • Open Access
29 Citations
8,222 Views
18 Pages

16 March 2018

Multiplayer online battle arena is a genre of online games that has become extremely popular. Due to their success, these games also drew the attention of our research community, because they provide a wealth of information about human online interac...

  • Article
  • Open Access
2 Citations
3,889 Views
19 Pages

Background: It is crucial to understand the neural feedback mechanisms and the cognitive decision-making of the brain during the processing of rewards. Here, we report the first attempt for a simultaneous electroencephalography (EEG)–functional...

  • Article
  • Open Access
3 Citations
3,318 Views
19 Pages

25 March 2019

With the rapid expansion of the railway represented by high-speed rail (HSR) in China, competition between railway and aviation will become increasingly common on a large scale. Beijing, Shanghai, and Guangzhou are the busiest cities and the hubs of...

  • Article
  • Open Access
1 Citations
1,463 Views
23 Pages

Power consumption (PC) data are fundamental for optimizing energy use and managing industrial operations. However, with the widespread adoption of data-driven technologies in the energy sector, maintaining the integrity and quality of these data has...

  • Article
  • Open Access
2 Citations
3,987 Views
17 Pages

This work presents a method for hyperspectral image unmixing based on non-negative tensor factorization. While traditional approaches may process spectral information without regard for spatial structures in the dataset, tensor factorization preserve...

  • Article
  • Open Access
14 Citations
4,781 Views
20 Pages

18 October 2018

Underdetermined blind source separation (UBSS) is a hot topic in signal processing, which aims at recovering the source signals from a number of observed mixtures without knowing the mixing system. Recently, expectation-maximization algorithm shows a...

  • Article
  • Open Access
6 Citations
2,454 Views
33 Pages

9 May 2024

A hyperspectral image (HSI) is often corrupted by various types of noise during image acquisition, e.g., Gaussian noise, impulse noise, stripes, deadlines, and more. Thus, as a preprocessing step, HSI denoising plays a vital role in many subsequent t...

  • Article
  • Open Access
1,830 Views
22 Pages

14 January 2025

Background/Objectives: The integration of microbiome and metabolome data could unveil profound insights into biological processes. However, widely used multi-omic data analyses often employ a stepwise mining approach, failing to harness the full pote...

  • Article
  • Open Access
12 Citations
2,609 Views
16 Pages

11 April 2021

Recently, non-negative tensor factorization (NTF) as a very powerful tool has attracted the attention of researchers. It is used in the unmixing of hyperspectral images (HSI) due to its excellent expression ability without any information loss when d...

  • Article
  • Open Access
1 Citations
1,917 Views
14 Pages

A Tensor-Based Approach to Blind Despreading of Long-Code Multiuser DSSS Signals

  • Liangliang Li,
  • Tao Liang,
  • Huaguo Zhang,
  • Songmao Du and
  • Lin Gao

22 February 2023

In this paper, a tensor-based approach to blind despreading of long-code multiuser DSSS signals is proposed. We aim to generalize the tensor-based methods originally developed for blind separation of short-code multiuser DSSS signals to long-code cas...

  • Article
  • Open Access
3 Citations
5,405 Views
49 Pages

Interpretable Topic Extraction and Word Embedding Learning Using Non-Negative Tensor DEDICOM

  • Lars Hillebrand,
  • David Biesner,
  • Christian Bauckhage and
  • Rafet Sifa

Unsupervised topic extraction is a vital step in automatically extracting concise contentual information from large text corpora. Existing topic extraction methods lack the capability of linking relations between these topics which would further help...

  • Article
  • Open Access
2 Citations
1,075 Views
42 Pages

22 November 2024

Since multi-view learning leverages complementary information from multiple feature sets to improve model performance, a tensor-based data fusion layer for neural networks, called Multi-View Data Tensor Fusion (MV-DTF), is used. It fuses M feature sp...

  • Article
  • Open Access
2 Citations
2,149 Views
21 Pages

Longitudinal Metabolomics Data Analysis Informed by Mechanistic Models

  • Lu Li,
  • Huub Hoefsloot,
  • Barbara M. Bakker,
  • David Horner,
  • Morten A. Rasmussen,
  • Age K. Smilde and
  • Evrim Acar

24 December 2024

Background: Metabolomics measurements are noisy, often characterized by a small sample size and missing entries. While data-driven methods have shown promise in terms of analyzing metabolomics data, e.g., revealing biomarkers of various phenotypes, m...

  • Article
  • Open Access
1,034 Views
17 Pages

21 July 2025

In this paper, we aim to develop an efficient algorithm for the solving Tensor Robust Principal Component Analysis (TRPCA) problem, which focuses on obtaining a low-rank approximation of a tensor by separating sparse and impulse noise. A common appro...

  • Article
  • Open Access
2 Citations
1,837 Views
19 Pages

8 December 2024

With the widespread application of unmanned aerial vehicles (UAVs) in civilian and military fields, how to effectively detect and resolve conflicts of large-volume and high-density UAV flights in local airspace has become an important issue. This pap...

  • Article
  • Open Access
4,172 Views
16 Pages

21 January 2019

We approach scalability and cold start problems of collaborative recommendation in this paper. An intelligent hybrid filtering framework that maximizes feature engineering and solves cold start problem for personalized recommendation based on deep le...

  • Article
  • Open Access
5 Citations
3,706 Views
22 Pages

23 May 2018

This paper presents a nonparametric regression model of categorical time series in the setting of conditional tensor factorization and Bayes network. The underlying algorithms are developed to provide a flexible and parsimonious representation for fu...

  • Article
  • Open Access
2 Citations
3,035 Views
12 Pages

An Accelerated Symmetric Nonnegative Matrix Factorization Algorithm Using Extrapolation

  • Peitao Wang,
  • Zhaoshui He,
  • Jun Lu,
  • Beihai Tan,
  • YuLei Bai,
  • Ji Tan,
  • Taiheng Liu and
  • Zhijie Lin

17 July 2020

Symmetric nonnegative matrix factorization (SNMF) approximates a symmetric nonnegative matrix by the product of a nonnegative low-rank matrix and its transpose. SNMF has been successfully used in many real-world applications such as clustering. In th...

  • Article
  • Open Access
11 Citations
4,582 Views
25 Pages

The paradigms of taxis and ride-hailing, the two major players in the personal mobility market, are compared systematically and empirically in a unified spatial–temporal context. Supported by real field data from Xiamen, China, this research proposes...

  • Article
  • Open Access
14 Citations
7,276 Views
33 Pages

19 August 2017

Low-rank matrix factorizations such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD) and Non-negative Matrix Factorization (NMF) are a large class of methods for pursuing the low-rank approximation of a given data matrix. The...

  • Article
  • Open Access
1 Citations
1,781 Views
13 Pages

14 October 2024

Reconfigurable intelligent surfaces (RISs) are a promising technology for sixth-generation (6G) wireless networks. However, a fully passive RIS cannot independently process signals. Wireless systems equipped with it often encounter the challenge of l...

  • Article
  • Open Access
1 Citations
2,139 Views
16 Pages

Parallel Factorization to Implement Group Analysis in Brain Networks Estimation

  • Andrea Ranieri,
  • Floriana Pichiorri,
  • Emma Colamarino,
  • Valeria de Seta,
  • Donatella Mattia and
  • Jlenia Toppi

3 February 2023

When dealing with complex functional brain networks, group analysis still represents an open issue. In this paper, we investigated the potential of an innovative approach based on PARAllel FActorization (PARAFAC) for the extraction of the grand avera...

  • Article
  • Open Access
6 Citations
2,543 Views
17 Pages

Fusing Multiview Functional Brain Networks by Joint Embedding for Brain Disease Identification

  • Chengcheng Wang,
  • Limei Zhang,
  • Jinshan Zhang,
  • Lishan Qiao and
  • Mingxia Liu

29 January 2023

Background: Functional brain networks (FBNs) derived from resting-state functional MRI (rs-fMRI) have shown great potential in identifying brain disorders, such as autistic spectrum disorder (ASD). Therefore, many FBN estimation methods have been pro...

  • Article
  • Open Access
535 Views
14 Pages

L2: Accurate Forestry Time-Series Completion and Growth Factor Inference

  • Linlu Jiang,
  • Meng Yang,
  • Benye Xi,
  • Weiliang Meng and
  • Jie Duan

26 May 2025

In forestry data management and analysis, data integrity and analytical accuracy are of critical importance. However, existing techniques face a dual challenge: first, sensor failures, data transmission interruptions, and human errors lead to the pre...

  • Article
  • Open Access
3 Citations
2,212 Views
21 Pages

Several Approaches for the Prediction of the Operating Modes of a Wind Turbine

  • Hannah Yun,
  • Ciprian Doru Giurcăneanu and
  • Gillian Dobbie

Growing concern about climate change has intensified efforts to use renewable energy, with wind energy highlighted as a growing source. It is known that wind turbines are characterized by distinct operating modes that reflect production efficiency. I...

  • Article
  • Open Access
2 Citations
2,956 Views
12 Pages

Modeling of the Resonant X-ray Response of a Chiral Cubic Phase

  • Timon Grabovac,
  • Ewa Gorecka,
  • Damian Pociecha and
  • Nataša Vaupotič

21 February 2021

The structure of a continuous-grid chiral cubic phase made of achiral constituent molecules is a hot topic in the field of thermotropic liquid crystals. Several structural models have been proposed so far. Resonant X-ray scattering (RXS), which gives...

  • Article
  • Open Access
4 Citations
2,081 Views
22 Pages

26 December 2023

Hyperspectral image (HSIs) denoising is a preprocessing step that plays a crucial role in many applications used in Earth observation missions. Low-rank tensor representation can be utilized to restore mixed-noise HSIs, such as those affected by mixe...

  • Article
  • Open Access
1,809 Views
19 Pages

Piano-based occupational therapy has emerged as an engaging and effective rehabilitation strategy for improving upper limb motor functions. However, a lack of comprehensive biomechanical modeling, objective rehabilitation assessment, and real-time fa...

  • Article
  • Open Access
16 Citations
6,066 Views
21 Pages

14 June 2019

This paper proposes a sound event detection (SED) method in tunnels to prevent further uncontrollable accidents. Tunnel accidents are accompanied by crashes and tire skids, which usually produce abnormal sounds. Since the tunnel environment always ha...

  • Article
  • Open Access
4 Citations
2,143 Views
20 Pages

8 February 2024

The research on the quality of employment in China holds immense significance for attaining high-quality employment development. Firstly, enhancing the quality of employment facilitates the optimization of labor resource allocation and enhances econo...

  • Article
  • Open Access
8 Citations
3,596 Views
14 Pages

16 December 2022

Multi-modal fusion can exploit complementary information from various modalities and improve the accuracy of prediction or classification tasks. In this paper, we propose a parallel, multi-modal, factorized, bilinear pooling method based on a semi-te...

  • Article
  • Open Access
3 Citations
3,255 Views
16 Pages

28 December 2020

N6-methyladenosine (m6A) editing is the most common RNA modification known to contribute to various biological processes. Nevertheless, the mechanism by which m6A regulates transcription is unclear. Recently, it was proposed that m6A controls transcr...

  • Article
  • Open Access
4 Citations
3,617 Views
17 Pages

9 February 2022

In this paper, the validity of the shell-evolution picture is investigated on the basis of shell-model calculations for the atomic mass number 25A55 neutron-rich nuclei. For this purpose, the so-called SDPF-MU interaction is used. Its c...

  • Article
  • Open Access
5 Citations
2,698 Views
18 Pages

Fusing Hyperspectral and Multispectral Images via Low-Rank Hankel Tensor Representation

  • Siyu Guo,
  • Xi’ai Chen,
  • Huidi Jia,
  • Zhi Han,
  • Zhigang Duan and
  • Yandong Tang

7 September 2022

Hyperspectral images (HSIs) have high spectral resolution and low spatial resolution. HSI super-resolution (SR) can enhance the spatial information of the scene. Current SR methods have generally focused on the direct utilization of image structure p...

  • Article
  • Open Access
17 Citations
5,786 Views
16 Pages

Tensor-Based Semantically-Aware Topic Clustering of Biomedical Documents

  • Georgios Drakopoulos,
  • Andreas Kanavos,
  • Ioannis Karydis,
  • Spyros Sioutas and
  • Aristidis G. Vrahatis

Biomedicine is a pillar of the collective, scientific effort of human self-discovery, as well as a major source of humanistic data codified primarily in biomedical documents. Despite their rigid structure, maintaining and updating a considerably-size...

  • Communication
  • Open Access
5 Citations
7,357 Views
25 Pages

15 June 2012

A research proposal on the algebraic structure, the representations and the possible applications of paraparticle algebras is structured in three modules: The first part stems from an attempt to classify the inequivalent gradings and braided group st...

  • Article
  • Open Access
1 Citations
1,710 Views
16 Pages

12 December 2022

Nonnegative Tucker decomposition (NTD) is an unsupervised method and has been extended in many applied fields. However, NTD does not make use of the label information of sample data, even though such label information is available. To remedy the defe...

  • Article
  • Open Access
4 Citations
4,126 Views
33 Pages

3 December 2019

The rapid development of sensor technology gives rise to the emergence of huge amounts of tensor (i.e., multi-dimensional array) data. For various reasons such as sensor failures and communication loss, the tensor data may be corrupted by not only sm...

  • Article
  • Open Access
2 Citations
3,050 Views
18 Pages

6 December 2019

Hyperspectral imaging is widely used to many applications as it includes both spatial and spectral distributions of a target scene. However, a compression, or a low multilinear rank approximation of hyperspectral imaging data, is required owing to th...

  • Article
  • Open Access
28 Citations
4,729 Views
20 Pages

Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition

  • Marzieh Zare,
  • Mohammad Sadegh Helfroush,
  • Kamran Kazemi and
  • Paul Scheunders

26 July 2021

Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI), aiming to produce a super-resolution hyperspectral image, has recently attracted increasing research interest. In this paper, a novel...

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