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Hybrid Deep Learning Approach for Automating App Review Classification:Advancing Usability Metrics Classification with an Aspect-Based Sentiment Analysis Framework

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computers, Materials & Continua 2025年第1期82卷 949-976页

作者： Nahed Alsaleh Reem Alnanih Nahed Alowidi Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computer Science and EngineeringUniversity of HailHail81451Saudi Arabia

App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their *** the analysis of these reviews is vital for efficient review *** traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior *** research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and *** propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification *** analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,*** contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews *** advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.

关键词： Requirements Engineering(RE) app review analysis usabilitymetrics hybrid deep learning BERT-BiLSTM-CNN

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Introduction to the Special Issue on the Bottleneck of Blockchain Techniques Scalability,Security and Privacy Protection

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computer Modeling in Engineering & sciences 2024年第12期141卷 1933-1937页

作者： Shen Su Daojing He Neeraj Kumar Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China School of Computer Science and Technology Harbin Institute of Technology(Shenzhen)Shenzhen518055China Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatiala147004India

Blockchain technology has been extensively studied over the past decade as a foundation for decentralized information-sharing platforms due to its promising *** the success of existing blockchain architectures like Bitcoin,Ethereum,Filecoin,Hyperledger Fabric,BCOS,and BCS,current blockchain applications are still quite *** struggles with scenarios requiring high-speed transactions(e.g.,online markets)or large data storage(e.g.,video services)due to consensus efficiency *** restrictions pose risks to investors in blockchain-based economic systems(e.g.,DeFi),deterring current and potential *** protection challenges make it difficult to involve sensitive data in blockchain applications.

关键词： services Ether limitations

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Heuristic Search with Cut Point Based Strategy for Critical Node Problem

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Journal of computer science & technology 2024年第6期39卷 1328-1340页

作者： Zhi-Han Chen Shao-Wei Cai Jian Gao Shi-Ke Ge Chan-Juan Liu Jin-Kun Lin School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 101408China Key Laboratory of System Software(Chinese Academy of Sciences)and State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China College of Information Science and Technology Northeast Normal UniversityChangchun 130024China School of Computer Science and Technology Dalian University of TechnologyDalian 116024China SeedMath Technology Limited Beijing 100086China

The critical node problem(CNP)aims to deal with critical node identification in a graph,which has extensive applications in many *** CNP is a challenging task due to its computational complexity,and it attracts much attention from both academia and *** this paper,we propose a population-based heuristic search algorithm called CPHS(Cut Point Based Heuristic Search)to solve CNP,which integrates two main *** first one is a cut point based greedy strategy in the local search,and the second one involves the functions used to update the solution pool of the ***,a mutation strategy is applied to solutions with probability based on the overall average similarity to maintain the diversity of the solution *** are performed on a synthetic benchmark,a real-world benchmark,and a large-scale network benchmark to evaluate our *** with state-of-the-art algorithms,our algorithm has better performance in terms of both solution quality and run time on all the three benchmarks.

关键词： local search cut point heuristic search critical node problem

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Dynamic Spatial Focus in Alzheimer’s Disease Diagnosis via Multiple CNN Architectures and Dynamic GradNet

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computers, Materials & Continua 2025年第5期83卷 2109-2142页

作者： Jasem Almotiri Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The evolving field of Alzheimer’s disease(AD)diagnosis has greatly benefited from deep learning models for analyzing brain magnetic resonance(MR)*** study introduces Dynamic GradNet,a novel deep learning model designed to increase diagnostic accuracy and interpretability for multiclass AD ***,four state-of-the-art convolutional neural network(CNN)architectures,the self-regulated network(RegNet),residual network(ResNet),densely connected convolutional network(DenseNet),and efficient network(EfficientNet),were comprehensively compared via a unified preprocessing pipeline to ensure a fair *** these models,EfficientNet consistently demonstrated superior performance in terms of accuracy,precision,recall,and F1 *** a result,EfficientNetwas selected as the foundation for implementing Dynamic *** GradNet incorporates gradient weighted class activation mapping(GradCAM)into the training process,facilitating dynamic adjustments that focus on critical brain regions associated with early dementia *** adjustments are particularly effective in identifying subtle changes associated with very mild dementia,enabling early diagnosis and *** model was evaluated with the OASIS dataset,which contains greater than 80,000 brain MR images categorized into four distinct stages of AD *** proposed model outperformed the baseline architectures,achieving remarkable generalizability across all *** findingwas especially evident in early-stage dementia detection,where Dynamic GradNet significantly reduced false positives and enhanced classification *** findings highlight the potential of Dynamic GradNet as a robust and scalable approach for AD diagnosis,providing a promising alternative to traditional attention-based *** model’s ability to dynamically adjust spatial focus offers a powerful tool in artificial intelligence(AI)assisted precisionmedicine,particularly in the early det

关键词： Spatial focus GradCAM medical image classification deep learning early dementia detection neurodegenerative disease MRI analysis Alzheimer’s attention CNN

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Ensemble Deep Learning Approaches in Health Care:A Review

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computers, Materials & Continua 2025年第3期82卷 3741-3771页

作者： Aziz Alotaibi Department of Computer Science College of Computing and Information TechnologyTaif UniversityTaif21974Saudi Arabia

Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of ***,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/*** the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big *** deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning *** ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble *** deep learning has been successfully used in several areas,such as bioinformatics,finance,and health *** this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug *** cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also ***,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and ***,future directions and opportunities for enhancing healthcare model performance are discussed.

关键词： Deep learning ensemble learning deep ensemble learning deep learning approaches for health care health care

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Breadth Learning and Network Embedding Techniques for Sensitive Information Detection in Social Media

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Informatica (Slovenia) 2024年第19期48卷 73-88页

作者： Luo, Jianping Zhu, Rongshen School of Arts and Science Chengdu College University of Electronic Science and Technology of China Chengdu611731 China School of Computer Science Chengdu College University of Electronic Science and Technology of China Chengdu611731 China

Social media platforms have brought tremendous changes to the way society communicates and transmits information. However, some extreme individuals post sensitive information such as false, malicious attacks, terrorism, or negative comments. To address this rapidly evolving network security challenge, this study introduces breadth learning and network embedding techniques from machine learning to establish a new method for information extraction and auditing. This method adopts a meta path random walk form to extract and filter effective information from multiple heterogeneous social networks. A network embedding technique based on breadth learning is proposed to transform each node into a low-dimensional feature space. Finally, a fusion function is designed to quantify the correlation between sensitive users on social platforms. The relationship between users and sensitive items is predicted by the correlation score, and then the sensitive information publisher is screened. Finally, the sensitive information released by the sensitive information publisher is effectively locked after it is identified. As a result, a sensitive information extraction and review model based on breadth learning and network embedding is constructed. The results showed that the research model exhibited a high degree of accuracy (97.3%) in mixed datasets on social platforms, outperforming other models designed for the review of sensitive information. Moreover, the model demonstrated superior performance on social platforms with larger data volumes. Accuracy represents the percentage of correct identification of sensitive information, indicating that the research model can more accurately identify sensitive information and its publishers. The research results have significant implications for the network security governance of open large-scale social media platforms. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Network embeddings

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Structural Optimization Analysis of Autonomous Wave Energy Converter Based on Maximum Power Output 20

Structural Optimization Analysis of Autonomous Wave Energy C...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Lei, Ming Heng, Wanshun Zhang, Xuexiao Xu, Yujie Harbin Engineering University College of Intelligent Science and Technology Harbin China Harbin Engineering University College of Computer Science and Technology Harbin China

ISBN: (纸本)9798350320831

In order to improve the energy conversion efficiency of autonomous wave energy converter, a novel optimization analysis method is proposed based on heave and pitch two-degree-of-freedom modeling and maximum power calculation. First of all, a restrained spring system is introduced to approximate the heave and pitch motion of autonomous wave energy converter, which simplifies the force analysis and modeling process. Then, similar to the spring system, a quantitative power computational model is constructed to illustrate the influence of the damping coefficient and wave frequency. Finally, through numerical calculation with statistical wave data of China's offshore, the optimal power take off (PTO) damping coefficient and wave frequency is obtained, providing a reference for subsequent structural optimization design. © 2023 IEEE.

关键词： Structural optimization

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Age estimation from facial images based on Gabor feature fusion and the CIASO-SA algorithm

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CAAI Transactions on Intelligence technology 2023年第2期8卷 518-531页

作者： Di Lu Dapeng Wang Kaiyu Zhang Xiangyuan Zeng School of Measurement and Communication Engineering Harbin University of Science and TechnologyHarbinChina Cheriton School of Computer Science University of WaterlooWaterlooOntarioCanada

Aiming at the problem of long time-consuming and low accuracy of existing age estimation approaches,a new age estimation method using Gabor feature fusion,and an improved atomic search algorithm for feature selection is ***,texture features of five scales and eight directions in the face region are extracted by Gabor wavelet *** statistical histogram is introduced to encode and fuse the directional index with the largest feature value on Gabor ***,a new hybrid feature selection algorithm chaotic improved atom search optimisation with simulated annealing(CIASO-SA)is presented,which is based on an improved atomic search algorithm and the simulated annealing ***,the CIASO-SA algorithm introduces a chaos mechanism during atomic initialisation,significantly improving the convergence speed and accuracy of the ***,a support vector machine(SVM)is used to get classification results of the age *** verify the performance of the proposed algorithm,face images with three resolutions in the Adience dataset are *** the Gabor real part fusion feature at 48�48 resolution,the average accuracy and 1-off accuracy of age classification exhibit a maximum of 60.4%and 85.9%,*** results prove the superiority of the proposed algorithm over the state-of-the-art methods,which is of great referential value for application to the mobile terminals.

关键词： age estimation atom search algorithm feature selection Gabor feature simulated annealing

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Space debris environment engineering model 2019:Algorithms improvement and comparison with ORDEM 3.1 and MASTER-8

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Chinese Journal of Aeronautics 2024年第5期37卷 392-409页

作者： Yuyan LIU Runqiang CHI Baojun PANG HU Diqi Wuxiong CAO Dongfang WANG School of Astronautics Harbin Institute of TechnologyHarbin 150001China College of Safety Science&Engineering Civil Aviation University of ChinaTianjin 300300China

As an essential tool for realistic description of the current or future debris environment,the Space Debris Environment Engineering Model(SDEEM)has been developed to provide support for risk assessment of *** contrast with SDEEM2015,SDEEM2019,the latest version,extends the orbital range from the Low Earth Orbit(LEO)to Geosynchronous Orbit(GEO)for the years *** this paper,improved modeling algorithms used by SDEEM2019 in propagating simulation,spatial density distribution,and spacecraft flux evaluation are *** debris fluxes of SDEEM2019 are compared with those of three typical models,i.e.,SDEEM2015,Orbital Debris Engineering Model 3.1(ORDEM 3.1),and Meteoroid and Space Debris Terrestrial Environment Reference(MASTER-8),in terms of two assessment *** orbital cases,including the Geostationary Transfer Orbit(GTO),Sun-Synchronous Orbit(SSO)and International Space Station(ISS)orbit,are selected for the spacecraft assessment mode,and the LEO region is selected for the spatial density assessment *** analysis indicates that compared with previous algorithms,the variable step-size orbital propagating algorithm based on semi-major axis control is more precise,the spatial density algorithm based on the second zonal harmonic of the non-spherical Earth gravity(J_(2))is more applicable,and the result of the position-centered spacecraft flux algorithm is more *** comparison shows that SDEEM2019 and MASTER-8 have consistent trends due to similar modeling processes,while the differences between SDEEM2019 and ORDEM 3.1 are mainly caused by different modeling approaches for uncatalogued debris.

关键词： SDEEM2019 Space debris propagating algorithm Spatial density algorithm ORDEM 3.1 MASTER-8

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Developing new Mg alloy as potential bone repair material via constructing weak anode nano-lamellar structure

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Journal of Magnesium and Alloys 2023年第1期11卷 154-175页

作者： Jinshu Xie Lele Wang Jinghuai Zhang Liwei Lu Zhi Zhang Yuying He Ruizhi Wu Key Laboratory of Superlight Material and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin150001China School of Materials Science and Engineering Hunan University of Science and TechnologyXiangtan411201China

The mechanics-corrosion and strength-ductility tradeoffs of magnesium(Mg)alloys have limited their applications in fields such as orthopedic ***,a fine-grain structure consisting of weak anodic nano-lamellar solute-enriched stacking faults(SESFs)with the average thickness of 8 nm and spacing of 16 nm is constructed in an as-extruded Mg96.9Y1.2Ho1.2Zn0.6Zr0.1(at.%)alloy,obtaining a high yield strength(YS)of 370 MPa,an excellent elongation(EL)of 17%,and a low corrosion rate of 0.30 mm y−1(close to that of high-pure Mg)in a uniform corrosion *** scanning Kelvin probe force microscopy(SKPFM),one-dimensional nanostructured SESFs are identified as the weak anode(∼24 mV)for the first *** excellent corrosion resistance is mainly related to the weak anodic nature of SESFs and their nano-lamellar structure,leading to the more uniform potential distribution to weaken galvanic corrosion and the release of abundant Y^(3+)/Ho^(3+)from SESFs to form a more protective film with an outer Ca_(10)(PO_(4))_(6)(OH)_(2)/Y_(2)O_(3)/Ho_(2)O_(3) layer(thickness percentage of this layer:72.45%).For comparison,the as-cast alloy containing block 18R long period stacking ordered(LPSO)phase and the heat-treated alloy with fine lamellar 18R-LPSO phase(thickness:80 nm,spacing:120 nm)are also studied,and the characteristics of SESFs and 18R-LPSO phase,such as the weak anode nature of the former and the cathode nature of the latter(37-90 mV),are distinguished under the same alloy ***,we put forward the idea of designing Mg alloys with high mechanical and anti-corrosion properties by constructing"homogeneous potential strengthening microstructure",such as the weak anode nano-lamellar SESFs structure.

关键词： Mg alloys Corrosion Solute-enriched stacking faults LPSO structure SKPFM Hydroxyapatite

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