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Article
Computer Science, Information Systems
Yuanchao Dai et al.
Summary: In order to assist the rehabilitation treatment of musculoskeletal injury patients, standard rehabilitation actions are needed to guide the process. Existing evaluation systems based on laser, ultrasound, and image have limitations due to their dependence on specialized equipment or susceptibility to ionizing radiation. Therefore, constructing a low-cost, effective, and safe musculoskeletal rehabilitation evaluation system remains a challenge.
ACM TRANSACTIONS ON SENSOR NETWORKS
(2023)
Article
Computer Science, Information Systems
Chen Huang et al.
Summary: In this article, a novel co-evolutionary method called TPCSO is proposed to enhance the convergence and search ability of CSO. The modified CSO divides the population into two sub-populations and adjusts the update strategy based on diversity and convergence requirements. Experimental results show that TPCSO can effectively solve large-scale optimization problems and achieve optimal results with higher accuracy compared to other algorithms.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Shengsheng Wang et al.
Summary: This paper proposes a novel OT-based Class-Aware Sample Reweighting (CASR) method to achieve sample-level fine-grained alignment between multi-source and target. Extensive experiments show that CASR presents significant advantages compared with other MSDA methods, and the visualization analysis further demonstrates the effectiveness of each proposed module.
Article
Computer Science, Artificial Intelligence
Zongda Wu et al.
Summary: In this article, a privacy protection solution is proposed for a Chinese keyword-based book search service. By modifying the user query sequence, the user query topics can be confused to protect the user's topic privacy on an untrusted server, while maintaining the accuracy of the book search service. A client-based framework and privacy model are introduced to guide the generation of cover queries based on a user query sequence. The proposed modification algorithm quickly generates cover queries that meet the privacy model by replacing, deleting, and adding keywords. The effectiveness of the approach is demonstrated through theoretical analysis and experimental evaluation, showing improved security for users' topic privacy without compromising efficiency, accuracy, and usability of the existing Chinese keyword book search service, thus contributing to the construction of a privacy-preserving text retrieval platform in an untrusted network environment.
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
(2023)
Article
Engineering, Biomedical
Bo Yang et al.
Summary: This work aims to predict the 3D coordinates of the point of interest (POI) on the surface of beating heart in dynamic minimally invasive surgery, using deep learning technique, to improve the manoeuvrability and expand functions of cardiac surgical robots.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Ying Chen et al.
Summary: Iris segmentation algorithms based on deep learning lack generalization ability and cannot accurately segment iris images without corresponding ground truth data. Normalization is required to reduce the influence of pupil deformation, but it introduces noise in nonconnected iris regions and decreases recognition rate. This paper proposes an end-to-end unified framework based on deep learning that achieves improved accuracy in iris segmentation and recognition without normalization. The framework includes MADNet for iris segmentation and DSANet for iris recognition, and experiments show that it outperforms other methods on low-quality iris images without ground truth data.
Article
Engineering, Biomedical
Siyu Lu et al.
Summary: This paper proposes a discriminative sparse transform iterative reconstruction algorithm for low-dose CT images, which introduces a priori image and global constraint term to reduce noise and artifacts, improve image quality, and overcome the dependence on prior images and registration problems in traditional methods.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Interdisciplinary Applications
Yang Li et al.
Summary: Retinal vessel segmentation is crucial for diagnosing fundus diseases, and this paper proposes a novel method called DE-DCGCN-EE. It uses a dual encoder to preserve edge information during down-sampling, a dynamic-channel graph convolutional network to address the issue of insufficient channel information utilization, and an edge enhancement block to improve the accuracy of fine blood vessel segmentation. Experimental results show that DE-DCGCN-EE outperforms other state-of-the-art methods on five retinal image datasets, indicating its potential clinical application.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2022)
Article
Engineering, Multidisciplinary
Qihang Li et al.
Summary: This study simulated the deformation process of a large and steep rock slope in China under variable rainfall, finding that the increased deformation region is positively correlated with increasing pore water pressure and water content values, while the infiltration of rainfall softens weak interlayers and leads to failure of the slope toe first, followed by the middle and upper parts sliding and failing sequentially. The proposed improved region growing segmentation method showed a significantly reduced average identification error in X and Y directions compared to the original method, indicating its potential for high-precision identification of rock slope deformation in complex scenes.
Article
Radiology, Nuclear Medicine & Medical Imaging
Caohui Duan et al.
Summary: The study accelerated multiple b-value gas DW-MRI using deep learning, achieving high-quality reconstructions with faster speed. The DC-RDN demonstrated effectiveness in maintaining accurate estimation of lung microstructural morphometry, showing great potential for studying lung diseases in the future.
EUROPEAN RADIOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Iman Ahmadianfar et al.
Summary: This study presents the analysis and principle of an innovative optimizer called INFO, which utilizes the weighted mean method to optimize different problems. The results show that INFO outperforms other methods in terms of exploration and exploitation, and is capable of converging to satisfactory solutions in engineering problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Automation & Control Systems
Wu Deng et al.
Summary: In this paper, an enhanced MSIQDE algorithm based on mixing multiple strategies, called EMMSIQDE, is proposed to overcome the limitations of QDE in optimization problems. EMMSIQDE achieves better optimization performance by using new mutation strategies and evolution mechanisms, as well as a feasible solution space transformation strategy.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Biology
Zongda Wu et al.
Summary: This paper proposes an effective confidential management solution for electronic medical records on the cloud, using a trusted local server to ensure the confidentiality, accuracy, and efficiency of the records.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Computer Science, Information Systems
Chunliang Zhao et al.
Summary: This paper develops an integrated information-based evolutionary framework for solving multi-scenario multi-objective optimization problems. Two integration algorithms, scenario-based dominance principle evolutionary algorithm and decomposition-based evolutionary algorithm, are constructed using the framework, and crucial components are developed under the multi-scenario environment.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Yu Xue et al.
Summary: Adam is a commonly used adaptive gradient descent approach in back-propagation algorithms, but it may fall into local optima easily. To solve this problem, an algorithm called EDEAdam, which integrates differential evolution with Adam, is proposed to achieve good results in both global and local search.
INFORMATION SCIENCES
(2022)
Article
Multidisciplinary Sciences
Zhijie Liu et al.
Summary: This study demonstrates a new imaging method, integrating femto-SRS technique with U-Net, for rapid and accurate diagnosis of gastric cancer. The method can diagnose gastric cancer without the need for pathologist-based diagnosis and holds potential for synchronizing with gastroscopic examination.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Kai Jin et al.
Summary: In this study, a color fundus image vessel segmentation dataset was collected, which is believed to be beneficial for the further development of retinal vessel segmentation.
Article
Computer Science, Information Systems
Xiaomei Qin et al.
Summary: This paper analyzes the causes of defocusing in a video microscope and proposes a new multi-focus image fusion method based on sparse representation (DWT-SR). By utilizing GPU parallel operation, the algorithm's running time is reduced, resulting in higher image contrast and more detailed representation.
Article
Computer Science, Artificial Intelligence
Yu Xue et al.
Summary: Feature selection is an important technique in classification that can improve accuracy and reduce dimensionality. This paper proposes a multi-objective evolutionary algorithm, MOEA-ISa, with interval based initialization and self-adaptive crossover operator for large-scale feature selection. Experimental results show that MOEA-ISa outperforms other algorithms and the proposed methods effectively improve its performance.
APPLIED SOFT COMPUTING
(2022)
Article
Biology
Bin Yan et al.
Summary: This study investigates the impact of different image filtering approaches and attention mechanisms on the image classification of Alzheimer's disease, and finds that these methods provide effective assistance for diagnosis and classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biology
Jun Chen et al.
Summary: In this paper, a novel clustering algorithm based on representative data objects derived from mutual neighbors is proposed to identify different shaped clusters. The algorithm first obtains mutual neighbors and estimates the density for each data object, and then represents the whole data using representative objects with high densities. Moreover, a concept of path distance is introduced to measure the similarities of representative objects for manifold structures, and an improved K-means algorithm is proposed to group the representative objects into clusters.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
Yun Liu et al.
Summary: This paper proposes an improved shuffled frog leaping algorithm that incorporates dynamic step size adjustment, specular reflection learning, and simulated annealing mechanisms. Experimental results show that the algorithm achieves superior solutions and performs well in feature selection tasks.
Article
Chemistry, Multidisciplinary
Yuxi Ban et al.
Summary: This study investigates a feature-based 2D/3D medical image registration algorithm, which uses a two-dimensional weighted spatial histogram of gradient directions to extract statistical features. The algorithm overcomes limitations and improves the accuracy and efficiency of image registration.
APPLIED SCIENCES-BASEL
(2022)
Review
Computer Science, Information Systems
Haoran Liu et al.
Summary: This paper surveys recent advances in pulse-coupled neural networks (PCNNs) and their applications in image processing. The PCNN is a neurology-inspired neural network model that aims to imitate the information analysis process of the biological cortex. Research shows that PCNN-derived models are developing rapidly and are widely used in image processing.
Article
Computer Science, Artificial Intelligence
Kunjie Yu et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Artificial Intelligence
Siamak Talatahari et al.
Summary: A novel metaheuristic algorithm called Chaos Game Optimization (CGO) is developed in this paper, based on chaos theory principles to solve optimization problems. Through evaluation of 239 mathematical functions and comparison with other algorithms, results indicate that CGO outperforms in most cases.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Computer Science, Information Systems
Zongda Wu et al.
Summary: This paper proposes a method to protect user privacy in LBS by constructing dummy query sequences to conceal user query locations and attributes, effectively protecting location privacy and attribute privacy.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Yanan Zhang et al.
Summary: Bankruptcy prediction is crucial for accurate decision making in financial fields. This paper introduces a novel bankruptcy prediction model based on KELM, utilizing an upgraded version of FOA algorithm called LSEOFOA to enhance performance. Experimental results show that LSEOFOA provides a self-assured tradeoff between exploration and exploitation, outperforming other optimization methods.
Article
Biology
Lei Liu et al.
Summary: This paper introduces a modified differential evolution algorithm based on slime mould for breast cancer image segmentation, and demonstrates that the developed multilevel image segmentation model has good performance. Experimental results show that the method has high convergence accuracy and the ability to escape local optima.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Yutao Yang et al.
Summary: The research proposes a population-based optimization technique called Hunger Games Search (HGS), designed based on the hunger-driven activities and behavioral choices of animals, with a simple structure, special stability features, and competitive performance to efficiently address constrained and unconstrained problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Xiaoyu Wen et al.
Summary: This paper proposes a method to solve the Green Multi-Objective Process Planning and Scheduling problem through a two-stage solution framework and an improved NSGA-II algorithm, achieving the minimization of manufacturing cycle time, carbon emissions, and tardiness. Experimental results demonstrate the effectiveness of the method and its successful application in a real-world case.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Iman Ahmadianfar et al.
Summary: The optimization field is plagued by metaphor-based pseudo-novel or fancy optimizers, with limited contributions to the optimization process. This study introduces a novel metaphor-free population-based optimization method called RUNge Kutta optimizer (RUN) based on mathematical foundations, showing promising results in mathematical tests and engineering problems. The RUN algorithm utilizes slope variations computed by the RK method for global optimization, demonstrating superior exploration and exploitation tendencies, fast convergence rate, and local optima avoidance.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Zongda Wu et al.
Summary: This paper proposes a method to protect users' commodity viewing privacy by constructing dummy requests on a trusted client to confuse and cover up user preferences on the untrusted server-side. The study introduces a privacy model and an implementation algorithm to measure the effectiveness of confusion and cover-up effects. The results show that the proposed approach effectively enhances the security of users' commodity viewing privacy on the untrusted server-side.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Biology
Jun Lv et al.
Summary: This study explored novel applications based on transfer learning using parallel imaging combined with the GAN model (PI-GAN), showing that transfer learning on brain tumor datasets could remove artifacts and yield smoother brain edges. Transfer learning results for knee and liver datasets were superior to those of the PI-GAN model trained with fewer training samples, although the learning process was slower in knee datasets compared to brain tumor datasets. Transfer learning improved reconstruction performance in models with acceleration factors of 2 and 6, with the AF=2 model showing better results. Transfer learning with pre-trained models helped address inconsistencies between training and test datasets and facilitated generalization to unseen data.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Biology
Songwei Zhao et al.
Summary: This paper proposes a Renyi's entropy multi-threshold image segmentation method based on an improved Slime Mould Algorithm (DASMA), which introduces diffusion mechanism and association strategy to enhance algorithm efficiency.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Ruyi Dong et al.
Summary: The Kernel Search Optimization (KSO) algorithm was proposed to simplify the optimization process by transforming the optimization of nonlinear functions into a linear process. By adopting a local search of the hill-climbing algorithm and simplifying the calculation of kernel parameters, the improved algorithm outperformed the original KSO and some well-known algorithms in terms of accuracy and running time.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Information Systems
Jie Zhou et al.
Summary: Epileptic EEG signal recognition is crucial for epilepsy detection, but traditional machine learning methods face challenges in dealing with imbalances and insufficient sample interrelationships; the proposed graph-based extreme learning machine method combines a relationship graph with ELM to improve the classification performance of imbalanced epileptic EEG signals.
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2021)
Article
Engineering, Multidisciplinary
Jiaze Tu et al.
Summary: This paper introduces a new stochastic optimizer called the Colony Predation Algorithm (CPA) based on the predation behavior of animals in nature, utilizing mathematical mapping to improve algorithm performance by simulating strategies used by animal hunting groups. The proposed CPA demonstrates competitive performance in optimizing engineering problems and will provide publicly available source code after publication.
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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
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ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
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EXPERT SYSTEMS WITH APPLICATIONS
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Review
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PATTERN RECOGNITION
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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2006)
