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The rapid advancement of mobile communication technology and devices has greatly improved our way of life. It also presents a new possibility that data sources can be used to accomplish computing tasks at nearby locations. Mobile Edge Computing (...

The data quality is a critical factor that affects the accuracy of feature selection algorithms. Meanwhile, structured knowledge information is embedded in complex feature correlations. However, the uncertainty of data and the complex correlation of ...

Social media serves as a real-time collecting and disseminating center of users’ ideas, opinions, and experiences. The deliberate disinformation and rumors propagate rapidly online due to their exaggerated facts, controversial opinions, divisive ...

This paper presents an improving teaching-learning-based optimization algorithm (called DRCMTLBO) combined with the dynamic ring neighborhood topology. Firstly, based on the individuals’ fitness distribution and clustered state within and beyond ...

• Proposing two relative neighborhood quality evaluations for expanding information.
• Designing a dynamic neighborhood strategy adapted to the search tendency.
• A novel crossover mechanism enhances the exploration of opposite ...

Palmprint recognition has shown great value for biometric recognition due to its advantages of good hygiene, semi-privacy and low invasiveness. However, most existing palmprint recognition studies focus only on homogeneous palmprint recognition, where ...

It is challenging to eliminate the domain shift between seen and unseen classes in multimodal zero-shot learning tasks due to the underlying disparity between the data distributions in the seen and unseen domains. In this paper, we propose a progressive ...

Social media allows the public to access information conveniently, in which the false messages that are eye-catching may spread fast. In this paper, we propose a two-stage confidence-guided boundary adaption (CBA) network, consisting of a feature ...

Multi objective optimization problems (MOPs) with irregular Pareto Fronts (PFs) appear frequently in a large of practical cases. Proximity and diversity are the key indicators for decomposition-based multi-objective evolutionary ...

Medical machine learning technology has garnered great attention from both the computer and medical fields. In this study, a multi-objective evolutionary algorithm integrating decomposition and harris hawks learning (MOEA/D-HHL) is ...

• The MOEA/D-HHL is presented for medical ML.
• Performance of the MOEA/D is ...

Teaching–learning-based optimization (TLBO) is a powerful metaheuristic algorithm for solving complex optimization problems pertaining to the global optimum. Many TLBO variants have been presented to improve the local optima avoidance capability ...

In this article, we consider the dynamic allocation of bursty requests stochastically arriving at heterogeneous servers with uncertain setup times. Lower expected response time and less power consumption are desirable objectives of users and service ...

Precisely evaluating the prognosis of invasive ductal carcinoma (IDC) of the breast is challenging as most prognostic signatures use single-omics data based on gene or clinical information.

Whole-slide images (WSIs), ...

• The method for WSI preprocessing and feature extraction was proposed and tested.
• A multi-omics model was established by combining CAF genes, WSI features, and lymph node status.
• Multi-omics model showed excellent performance in ...

This paper proposes a joint class metric and sparse representation regularized deep belief network (J‐DBN) method for intelligent fault diagnosis of the rotary equipment. In this novel method, the joint class metric and sparse representation ...

Multiobjective optimization assumes a one-to-one mapping between decisions and objective space, however, this is not always the case. When many variables have the same or equivalent objective value, a multimodal multiobjective issue ...

• The ESNSGA-II is presented for MMOPs.
• Performance of the ESNSGA-II is enhanced ...

Most anchor‐based detectors use intersection over union (IoU) to assign targets to anchors during training. However, IoU did not pay enough attention to the proximity of the anchor's centre to the centre of the truth box, resulting in two issues: (...

Vibration signals are widely used in fault diagnosis of rotating machinery in real-world situations. However, it is very challenging to extract effective fault features from noisy signals and construct an accurate diagnosis model. In this paper, ...

Single-stage object detectors have been widely applied in computer vision applications due to their high efficiency. However, the loss functions adopted by single-stage detectors hurt the localization accuracy seriously. Firstly, the ...

With the development of science and technology, in order to provide better financial information for economic decision-making, people urgently need a new financial reporting model. For the existing financial reporting model, it is only published in PDF or ...

A generalized Chinese Remainder Theorem (GCRT)-based multi-secret sharing (MSS) scheme, which can solve a tricky problem that the correspondences between multi-secret and their remainders in each share are unclear, has been proposed recently. But ...

ABSTRACT: Aiming at the characteristics of multiple time delays and multiple disturbances in the long-distance indirect water-cooling temperature control loop of the ArF excimer laser discharge cavity with a dual-cavity structure, the foundation of a ...