Expert Systems with Applications: An International Journal

Clinicians and researchers commonly assess hand movements to detect and monitor neurological disorders. With the growing use of deep learning and biomedical informatics, computer vision can be applied to hand movement videos to extract movement ...

• A new network achieved state-of-the-art performance in hand motion de-blur task.
• An investigation to assess the current methods in addressing hand motion blur issue.
• A new 3-dimension feature discriminator is designed to improve ...

Textual reviews contain fine-grained information that can effectively infer user preferences over the items. Accordingly, the latest studies in the field of recommender systems exploit content-rich review texts to complement user and item ...

• Identifying blockchain solutions to gain sustainability in the supply chains.
• Offering a new application for using blockchain in the agricultural products.
• Presenting a novel integrated SWARA-CoCoSo approach based on Z-numbers.

Nowadays, because of the increase in global competition and the need to pay attention to sustainable issues, achieve a competitive advantage, reduce costs, and improve Supply Chain (SC) network management, the use of blockchain and its ...

• Develop a novel two-layer coordinated multi-agent reinforcement learning algorithm.
• Synergize traffic signals through local cooperation and global coordination.
• Optimization of vehicle emissions and traffic congestion as ...

Intersection traffic signal control considering vehicle emissions has become an important topic, however, the decision complexity of traffic signal control increases dramatically in a dynamic traffic environment with multi-intersections. It is a ...

With the rapid development of deep learning, emotion recognition from facial expressions has also greatly improved, but there are still limitations in terms of reliability when applied to the real world. In other words, facial expressions and the ...

• Real-time multimodal emotion recognition with visual, audio, and biological signals.
• The mismatch between the inner and external expressions was considered first time.
• An adaptive fusion method for adaptively analyzing a subject’s ...

In order to predict wind power quickly and accurately and reduce the negative impact of wind power instability on the grid, this study proposes an ultra-short-term wind power prediction model based on financial technical indicators and parameter ...

Modeling and estimating mixed memberships for overlapping unipartite un-weighted networks has been well studied in recent years. However, to our knowledge, there is no model for a more general case, the overlapping bipartite weighted networks. To ...

• We propose a novel model BiMMDF for overlapping bipartite weighted networks.
• We use an algorithm with a theoretical guarantee of consistency to fit BiMMDF.
• Separation conditions of BiMMDF for different distributions are analyzed.

• An explainable deep learning approach is proposed to predict and analyze rainfall.
• An encoder-decoder with an attention mechanism predicts rainfall multi-step-ahead.
• An explanation module can discover the main factors affecting ...

Monthly rainfall prediction is a crucial topic for the management of water resources and prevention of hydrological disasters. To make a multi-step monthly rainfall prediction and discover the primary factors affecting rainfall, this study ...

Modifying some keywords or numbers on documents to change the original intention is illegal. In some litigation cases, especially economic cases, there is often a need to examine the type of ink on documents. This paper proposes a nondestructive ...

The challenge of selecting the best transportation mode is one of the most significant issues that organizations deal with during the product delivery phase. Many criteria that influence the selection of an appropriate mode of transportation are ...

To meet the frequent transportation requirements between distributed manufacturing services (MSs), logistics services (LSs) have played an essential role in cloud manufacturing. However, previous studies on service scheduling focused on MSs and ...

Medical images are closely related to the patient's condition. We put forward the model of Sin-Arcsin-Arnold Multi-Dynamic random nonadjacent Coupled Map Lattice (SAMCML) and found that it has good chaotic properties, so we used it to design an ...

Deciding the signal length is an important challenge for one-class time-series classification (OCTSC). This paper aims to develop an OCTSC algorithm that does not require model retraining for different signal lengths. For this purpose, a distance-...

Due to the emergence of new network attack technologies, cloud manufacturing platforms may be subject to various network attacks at any time. Traditional network attack prediction aims to predict the upcoming types of network attacks with ...

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• A hybrid network attack detection method is given for a cloud manufacturing platform.
• It adopts a Savitzky–Golay filter for data smoothing and noise elimination.
• It adopts a self-attention mechanism of an encoder to reduce network ...

In implant prosthesis treatment, the design of the surgical guide heavily relies on the manual location of the implant position, which is subjective and prone to doctor’s experiences. When deep learning based methods has started to be applied to ...

Wind turbines have become one of the essential sources of energy generation due to their contribution to energy security, economic development, job creation, and technological innovation. This work proposes a methodology for designing robust ...

• A Takagi–Sugeno (TS) zonotopic observer scheme for fault diagnosis is proposed.
• The uncertain TS models are identified with a MANFIS using healthy data.
• A set of TS zonotopic observers are designed to detect faults in the wind ...

Topology control is an efficient and low-cost measure to adjust the power flow to ensure the security and economic operation of power systems. Since topology control involves large-scale action space and is difficult to solve by traditional ...

• A novel progressive decision-making framework for power system topology control.
• A multi-stage reinforcement learning method for efficient exploration.
• Extracting both the local and global graph-based features for multi-stage ...

Deep learning architectures have demonstrated outstanding results in image classification in the last few years. However, applying sophisticated neural network architectures in small datasets remains challenging. In this context, transfer ...

• We propose multiscale patch-based graphs to represent image information.
• Transfer learning is adopted for dealing with small datasets.
• The approach can handle images with heterogeneous sizes.
• The approach represents visual ...

Researchers working in the field of unmanned aerial vehicles are observing rapid developments in the field, such as the use of quadrotors to grasp, manipulate, and transport objects. These advancements are made possible through sophisticated ...

Identification of the optimal subset of features for Feature Selection (FS) problems is a demanding problem in machine learning and data mining. A trustworthy optimization approach is required to cope with the concerns involved in such a problem. ...

• Binary capuchin search algorithm is used for the first time for feature selection.
• Three other versions of BCSA are also proposed for feature selection.
• The results revealed that BCSA has high efficiency over the 26 datasets.
• ...

Android has been a significant target of malware applications due to the exponential growth of mobile devices. This may result in severe threats to Android users such as financial loss, information leakage etc. The security of smartphones has ...

The evaluation and identification of high-quality patents are urgently needed for the technological research and development and the transformation of achievements. Traditional researchers and analysts mainly focus on developing various patent ...

Geographical Topic Phrases (GTPs) are specialized terms for describing geographical objects, phenomena, or events and are frequently used to organize, navigate, and index geographical resources (e.g., geographical data hosted in geoportals). ...

As an epigenetic modification that plays an important role in modifying gene function and controlling gene expression during cell development, DNA N4-methylcytosine (4mC) is still lack of researching. It is therefore necessary to accurately ...

• Structural Sparse Regularized Random Vector Functional Link Network (SSR-RVFL) is proposed for predicting 4mC sites.
• SSR-RVFL performs better and achieves higher prediction accuracy than state-of-the-art methods.
• An efficient ...

We propose a novel non-invasive tool, using deep learning and imaging, for delineating COVID-19 infection in lungs. The Ensembling of selective Focus-based Multi-resolution Convolution network (E F M C), employing Leave-One-Patient-Out (L O P O) ...

• Use of limited data for training the deep learning model.
• A multi-resolution selective-focus framework for image segmentation.
• Ensembling of classifiers through a new strategy LOPO, with good generalization.
• Results ...

Multi-view classification aims to efficiently utilize information from different views to improve classification performance. In recent researches, many effective multi-view learning methods have been proposed to perform multi-view data analysis. ...

• A novel end-to-end unified multi-view classification framework is proposed.
• A long and short span self-attention layer is constructed.
• An adaptive weight loss fusion strategy is designed.
• The performance of our method ...

Dynamic path planning has gained increasing popularity in mobile robot navigation. Some of the current path planning methods require a priori information about the motion space and are easily affected by the distribution of obstacles. To address ...

This paper provides a time series analysis of the Bank of Japan (BOJ)’s exchange traded fund (ETF) and real estate investment trust (REIT) purchase program. The program is a part of the BOJ’s unconventional monetary policy introduced in December ...

• The first attempt at investigating a dynamic aspect of the BOJ purchase program.
• Identify dynamic factors underlying the decisions of the purchases for the first time.
• Predict the timings of the purchases accurately for all periods ...

In a complex transaction and operation environment, supply chain usually faces the disruption risk, especially the supplier selection. Fortunately, the blockchain technology not only can provide traceability and decentration for supply chain ...

• Learn and generalize the evaluation criteria for supplier selection.
• This paper develops the robustness PROMETHEE method.
• Construct a correction approach to amend the performance of suppliers.