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Modeling and Comprehensive Review of Signaling Storms in 3GPP-Based Mobile Broadband Networks:Causes,Solutions,and Countermeasures

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computer Modeling in Engineering & sciences 2025年第1期142卷 123-153页

作者： Muhammad Qasim Khan Fazal Malik Fahad Alturise Noor Rahman department of computer science Iqra National UniversityPeshawar25000Pakistan department of Cybersecurity College of ComputerQassim UniversityBuraydah52555Saudi Arabia department of computer science and Engineering Al-Fayha CollegeAl Jubayl31961Saudi Arabia

Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband ***,they consume important and scarce network resources such as bandwidth and processing *** have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial *** paper draws its motivation from such real network disaster incidents attributed to signaling *** this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and *** provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding *** important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a *** paper presents an update and an extension of our earlier conference *** our knowledge,no similar survey study exists on the subject.

关键词： Signaling storm problems control signaling load analytical modeling 3GPP networks smart devices diameter signaling mobile broadband data access data traffic mobility management signaling network architecture 5G mobile communication

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Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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computer Modeling in Engineering & sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh department of computer Engineering Aligarh Muslim UniversityAligarh202002India College of computer science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea department of computer science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia department of computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： computer vision feature selection machine learning region detection texture analysis image classification medical images

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Laboratory or department?Exploration and Creation in computer science and Technology

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计算机教育 2024年第3期 13-16页

作者： Ann Copestake department of computer science and Technology University of CambridgeWilliam Gates Building15 JJ Thomson AvenueCambridge CB30FDUK

In the very beginning,the computer Laboratory of the University of Cambridge was founded to provide computing service for different disciplines across the *** computer science developed as a discipline in its own right,boundaries necessarily arose between it and other disciplines,in a way that is now often detrimental to ***,it is necessary to reinvigorate the relationship between computer science and other academic disciplines and celebrate exploration and creativity in *** do this,the structures of the academic department have to act as supporting scaffolding rather than *** examples are given that show the efforts being made at the University of Cambridge to approach this problem.

关键词： Laboratory or department University of Cambridge Boundaries Exploration and creativity

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Global Piecewise Analysis of HIV Model with Bi-Infectious Categories under Ordinary Derivative and Non-Singular Operator with Neural Network Approach

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computer Modeling in Engineering & sciences 2025年第1期142卷 609-633页

作者： Ghaliah Alhamzi Badr Saad TAlkahtani Ravi Shanker Dubey Mati ur Rahman department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh13318Saudi Arabia department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002India School of Mathematical sciences Jiangsu UniversityZhenjiang212013China department of computer science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon

This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary *** HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered *** total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,*** proposed model is tested separately for unique solutions and existence on bi *** numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons *** proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler *** cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said *** study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered *** obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.

关键词： HIV infection model qualitative scheme approximate solution piecewise global operator neural network

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Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

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computer Modeling in Engineering & sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics Engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia department of computer science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia department of computer science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

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Inspires effective alternatives to backpropagation:predictive coding helps understand and build learning

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Neural Regeneration Research 2025年第11期20卷 3215-3216页

作者： Zhenghua Xu Miao Yu Yuhang Song School of Health sciences and Biomedical Engineering Hebei University of TechnologyTianjinChina department of computer science University of OxfordOxfordUK

Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human *** enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.

关键词： assignment learning enable

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Multi-Stage-Based Siamese Neural Network for Seal Image Recognition

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computer Modeling in Engineering & sciences 2025年第1期142卷 405-423页

作者： Jianfeng Lu Xiangye Huang Caijin Li Renlin Xin Shanqing Zhang Mahmoud Emam School of computer science and Technology Hangzhou Dianzi UniversityHangzhou310018China Shangyu Institute of science and Engineering Hangzhou Dianzi UniversityShaoxing312300China Faculty of Artificial Intelligence Menoufia UniversityShebin El-Koom32511Egypt

Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and *** seal inspection is commonly audited manually to ensure document ***,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the *** image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image ***,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp ***,the fixed training data categories make handling new categories to be a challenging *** paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these ***,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese ***,we compare the results with the pre-stored standard seal template images in the database to obtain the seal *** evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in *** proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation ***,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.

关键词： Seal recognition seal authentication document tampering siamese network spatial transformer network similarity comparison network

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Repetitive traumatic brain injury–induced complement C1–related inflammation impairs long-term hippocampal neurogenesis

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Neural Regeneration Research 2025年第3期20卷 821-835页

作者： Jing Wang Bing Zhang Lanfang Li Xiaomei Tang Jinyu Zeng Yige Song Chao Xu Kai Zhao Guoqiang Liu Youming Lu Xinyan Li Kai Shu department of Neurosurgery Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina department of Neurosurgery Shanxi Bethune HospitalShanxi Academy of Medical SciencesTongji Shanxi HospitalThird Hospital of Shanxi Medical UniversityTaiyuanShanxi ProvinceChina department of Pathophysiology School of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina Institute for Brain Research Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhanHubei ProvinceChina department of Graduate Student Chongqing Medical UniversityChongqingChina department of Basic Medicine School of Medical ScienceHubei University for NationalitiesEnshiHubei ProvinceChina department of Anatomy School of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina

Repetitive traumatic brain injury impacts adult neurogenesis in the hippocampal dentate gyrus,leading to long-term cognitive ***,the mechanism underlying this neurogenesis impairment remains *** this study,we established a male mouse model of repetitive traumatic brain injury and performed long-term evaluation of neurogenesis of the hippocampal dentate gyrus after repetitive traumatic brain *** results showed that repetitive traumatic brain injury inhibited neural stem cell proliferation and development,delayed neuronal maturation,and reduced the complexity of neuronal dendrites and *** with repetitive traumatic brain injuryalso showed deficits in spatial memory ***,following repetitive traumatic brain injury,neuroinflammation was enhanced in the neurogenesis microenvironment where C1q levels were increased,C1q binding protein levels were decreased,and canonical Wnt/β-catenin signaling was *** inhibitor of C1 reversed the long-term impairment of neurogenesis induced by repetitive traumatic brain injury and improved neurological *** findings suggest that repetitive traumatic brain injury–induced C1-related inflammation impairs long-term neurogenesis in the dentate gyrus and contributes to spatial memory retrieval dysfunction.

关键词： complement C1 dendrite dentate gyrus hippocampus neural stem cell neurogenesis neuroinflammation neurological function neuron traumatic brain injury

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Role of glutathione transferase in phase separation of FUS and TAF15 in neurons

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Neural Regeneration Research 2025年第7期20卷 1999-2000页

作者： Kiyoung Kim department of Medical science Soonchunhyang UniversityAsanKorea

Amyotrophic lateral sclerosis(ALS)is a progressive neurodegenerative disorder characterized by the degeneration of motor neurons in the brain and spinal cord,leading to muscle weakness,paralysis,and ultimately death(Cleveland and Rothstein,2001).Frontotemporal lobar degeneration(FTLD)is a neurodegenerative disease affecting the frontal and temporal lobes of the brain,leading to changes in behavior,personality,and language(Van Langenhove et al.,2012).Both ALS and FTLD are classified as proteinopathies in which abnormal protein aggregation and accumulation in neurons contribute to the disease *** in sarcoma(FUS)is a DNA/RNA-binding protein involved in various cellular processes,including transcriptional regulation,RNA splicing,and DNA *** in the FUS gene have been linked to familial ALS,highlighting the importance of FUS in the disease pathogenesis(Vance et al.,2009).In ALS and FTLD,aberrant post-translational modifications(PTMs)of FUS,such as phosphorylation,acetylation,and methylation,have been implicated in the promotion of FUS aggregation and neurotoxicity(Choi et al.,2023).Therefore,understanding the regulatory mechanisms of FUS PTMs is crucial for developing targeted therapies against these diseases.

关键词： degeneration FUS aggregation

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Cell polarization in ischemic stroke: molecular mechanisms and advances

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Neural Regeneration Research 2025年第3期20卷 632-645页

作者： Yuanwei Li Xiaoxiao Xu Xuan Wu Jiarui Li Shiling Chen Danyang Chen Gaigai Li Zhouping Tang department of Neurology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina

Ischemic stroke is a cerebrovascular disease associated with high mortality and disability rates. Since the inflammation and immune response play a central role in driving ischemic damage, it becomes essential to modulate excessive inflammatory reactions to promote cell survival and facilitate tissue repair around the injury site. Various cell types are involved in the inflammatory response, including microglia, astrocytes, and neutrophils, each exhibiting distinct phenotypic profiles upon stimulation. They display either proinflammatory or anti-inflammatory states, a phenomenon known as ‘cell polarization.’ There are two cell polarization therapy strategies. The first involves inducing cells into a neuroprotective phenotype in vitro, then reintroducing them autologously. The second approach utilizes small molecular substances to directly affect cells in vivo. In this review, we elucidate the polarization dynamics of the three reactive cell populations(microglia, astrocytes, and neutrophils) in the context of ischemic stroke, and provide a comprehensive summary of the molecular mechanisms involved in their phenotypic switching. By unraveling the complexity of cell polarization, we hope to offer insights for future research on neuroinflammation and novel therapeutic strategies for ischemic stroke.

关键词： astrocyte polarization immune regulation inflammation ischemic injury microglia polarization neutrophil polarization signaling pathways stroke

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