Expert Systems with Applications: An International Journal

The cloud auditing model was attractive for the cloud storage system to check the integrity of the stored user files. Hence, to maximize the security concern, federated learning and the blockchain were introduced. But, in some cases, security ...

• FIS is used for attaining the optimal scaling factor.
• Efficient fusion of RDWT-QR-RSVD is utilized.
• Henon map is used for secure transmission.
• DnCNN is used to enhance robustness.
• Blockchain-based authentication is ...

Due to the vast development of computer technology, the security and copyright protection are the major issues which needs to be addressed. The medical data in one of the most important data which must be secured for correct diagnosis. ...

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Light Detection And Ranging (LiDAR) sensor offers solutions to extract real-time information of vehicle’s surroundings and can provide a new opportunity to improve the road safety related issues in mixed traffic conditions. This paper explores ...

Breast cancer is a significant health concern due to its aggressive nature and high mortality rates. Early detection is crucial to improving patient outcomes. Thermography, a non-invasive and cost-effective method, utilizes heat from the breast ...

• CEC’22 test suite is utilized for verification of LFR-COA performance.
• The LFR-COA algorithm optimizes various hyperparameters of the DenseNet121 model.
• LFR-COA algorithm is proposed for solving global optimization problems.
• ...

We explore the influence and advantages of integrating chaotic systems with deep learning for time series forecasting in this paper. It proposes a novel deep learning method based on the Chen system, which leverages the randomness, sensitivity, ...

• Chen system boosts deep learning for precise time series forecasting.
• Chaotic models outperform traditional deep learning in accuracy and robustness.
• Models save resources and adapt better across diverse datasets.
• Promising ...

Monkeypox virus has quickly expanded throughout several nations, raising serious public health concerns. Lack of precautionary measures raises concerns about the possibility of global pandemic. As a result, early detection of ...

• MOX-NET, a deep learning framework for monkeypox classification.
• Accuracy of 98.64% on the MSLID dataset, surpassing existing methods.
• An entropy-controlled firefly algorithm for efficient feature selection.
• A robust solution ...

Distributed Electric Propulsion (DEP) aircraft presents a highly promising technology aligned with the demands of green aviation due to its superior flight efficiency, reduced energy loss, and diminished noise. This paper firstly designs and ...

Attributed graph anomaly detection aims to identify abnormal nodes that significantly differ from most nodes in terms of their attribute or structure. Recent graph contrastive learning methods, which follow an augmenting-contrasting learning ...

• Enhancing data augmentation by merging prior knowledge of diverse abnormal patterns.
• Introducing an edge discriminator to distinguish between diverse edge types.
• Utilizing several well-designed loss functions to make full use of ...

At present, high-dimensional data clustering has become a vital research field in machine learning. Traditional clustering algorithms cannot perform well on high-dimensional data, where the clustering task is usually divided into two stages: ...

• The proposed PCIP accomplishes both dimensionality reduction and clustering.
• The instance penalty matrix is used to identify and handle the abnormal samples.
• We propose an iterative algorithm to solve PCIP and its convergence is ...

The identification and rank of crucial spreaders aim to survey the diffusion capability, which has a significant impact on controlling information spread in networks. However, most of the findings neglect the fused information of the structural ...

• ETC focuses on the fusion of structural hole and the former two-order information.
• Definition of Hierarchy Vector of Cluster is based on a novel layered approach IKsD.
• Tanimoto Correlation tests association strength between a pair ...

The hybrid platform is emerging into online retailing market based on reselling and direct selling, forming the dual-channel model composed of third-party operated and platform self-operated channels. To achieve structural matching between ...

Despite the economic importance and research relevance of strawberries, advances in agricultural engineering for this crop have been hampered by pervasive occlusion challenges. Accurate fruit counting is crucial for both yield prediction and ...

• Automated occlusion-robust counting for accurate strawberry yield assessment.
• Enhanced strawberry detection with improved YOLOv5s and attention.
• Developed the MultiMap algorithm for precise counting from tracking results.
• ...

Antenatal or prenatal hydronephrosis (AHN) is a common kidney complication in unborn children. While AHN is generally benign and resolves over time, this condition can inflict serious kidney damage or even organ failure ...

Chongqing is the only province and city with net energy input in southwest China, and its energy security has been in a tight balance for a long time. To propose scientific and reasonable energy policies for Chongqing under the “dual carbon” goal,...

• The conformable fractional-order accumulated generating operator is introduced to preprocess raw data.
• The CFNGBMO(1,1) model is discussed.
• The WOA algorithm is applied to search the optimal system nonlinear parameters.
• The ...

This paper introduces a novel consensus theoretical framework designed to effectively manage non-cooperative behaviour in social network group decision making (SNGDM). It addresses the challenge by considering both individuals’ willingness to ...

• It introduces a CRP framework for handling non-cooperative behaviour in SNGDM.
• A new tolerance index is introduced to detect non-cooperative behaviour.
• It proposes a model that balances individual independence and group ...

The existing detection models for stored grain pests have low accuracy and poor generalization ability in fine-grained detection tasks involving numerous species, minor inter-class differences, and significant intra-class variations. This study ...

A new technique is presented for diagnosing faults in a Discrete Event System (DES) when the state of the system under diagnosis (SUD) is uncertain upon commencement of the diagnosis process. Specifically, a diagnoser is developed that detects, ...

Monitoring the heart rate of a fetus is the only method for continuously monitoring fetal well-being during labour. Decelerations in the fetal heart rate, usually corresponding with contractions, provide information regarding the ability of the ...

• Crowd-sourcing of data from medical professionals.
• Use of deep learning for fetal heart-rate deceleration detection.
• Improved specificity for deceleration detection.

Traffic prediction has drawn considerable attention due to its potential to optimize the operational efficiency of road networks. Existing methods commonly combine graph neural network (GNN) and recurrent neural network (RNN) to model spatio-...

• A time-based adaptive adjacency matrix capturing time-varying spatial correlations.
• A novel temporal convolutional module with superior prediction efficiency.
• Adding external features to capture spatio-temporal heterogeneity of ...

Wi-Fi positioning system (WPS) has been proven as an effective way to realize universal indoor navigation for smart city-related applications. The localization ability of the existing WPS is affected by the low precision of the crowdsourced ...

With the advances in social media and e-democracy technologies, large-scale decision making (LSDM) problems with trust relationships demands effective consensus-reaching processes. Existing literature has identified a need for improvement in the ...

Numerous redundant and irrelevant features are usually contained in high-dimensional data whose presence, if ignored, can bring detrimental effects on the performance of data processing tasks. Unsupervised feature selection (UFS) as a trending ...

Industry 5.0 (I5.0) is increasingly governed by Operation Technology and Information Technology. It hosts Deep Learning (DL) solutions as a premier tool for the informatization of Quality Inspection (QI) of Mass Produced Products (MPP) and Mass ...

• A customer order-driven informatization framework for mass-customized products.
• A hybrid PackMASNet scheme that minimizes mass-produced and customized products’ performance degradation.
• Lightweight Cosine-similarity threshold-based ...

Real-world applications of computer vision in the humanities require algorithms to be robust against artistic abstraction, peripheral objects, and subtle differences between fine-grained target classes. Existing datasets provide instance-level ...

• Dataset of 4712 artworks annotated with 38116 labelled object instances from 139 categories.
• First dataset of smell-related objects in artworks.
• Challenging dataset in terms of occlusion, object sizes, and spatial object ...

Edge computing is a novel and potential computing model which moves storage and computing capabilities to the network edge, substantially decreasing service latency and network traffic. The existing Internet of Things (IoT) network offloading ...

The graph-based recommendation systems achieve significant success, yet they are accompanied by malicious attacks. In most scenes, attackers will inject crafted fake profiles into the recommendation system to boost the ranking of their target ...

• We explore the stealthiness of recommender attack to fill this research gap.
• We introduce a poisoning attack method based on a bi-level optimization framework.
• We leverage contrastive learning to align item embeddings for ...

In this study, a sample of 3605 points of firm-level panel data is analyzed to examine the impacts of the attention to and deviation of online public opinions on stock price synchronicity (SPS) in China. The empirical findings demonstrate that ...

Learning dynamic user preference has become an increasingly important component for many online platforms (e.g., video-sharing sites, e-commerce systems) to make sequential recommendations. In these platforms, user–item interactive behaviors are ...

• Extracting dynamic multiples interests from dual-scale sequential patterns.
• Constructing two types of hypergraphs to model global multi-order multi-behavior dependencies.
• Fusion of sequential and hypergraph information to learn ...

As technology advances, competition among market players intensifies, highlighting the importance of comprehending both one’s own and competitors’ pricing strategies. Traditional approaches often rely on static factors for price forecasting, ...

• Referencing competitors’ prices is essential due to consumer sensitivity.
• STAD-GCN integrates competitive elements and price factors dynamically.
• The model improves price prediction via spatial–temporal attention mechanisms.
• ...