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GliomaCNN: An Effective Lightweight CNN Model in Assessment of Classifying Brain Tumor from Magnetic Resonance Images Using Explainable AI

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computer Modeling in engineering & sciences 2024年第9期140卷 2425-2448页

作者： Md.Atiqur Rahman Mustavi Ibne Masum Khan Md Hasib M.F.Mridha Sultan Alfarhood Mejdl Safran Dunren Che Department of Computer Science and Engineering Ahsanullah University of Science and TechnologyDhaka1208Bangladesh Department of Computer Science and Software Engineering The University of Western AustraliaPerthWA 6009Australia Department of Computer Science American International University-BangladeshDhaka1229Bangladesh Department of Computer Science College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia School of Computing Southern Illinois UniversityCarbondale62901USA

Brain tumors pose a significant threat to human lives and have gained increasing attention as the tenth leading cause of global *** study addresses the pressing issue of brain tumor classification using Magnetic resonance imaging(MRI).It focuses on distinguishing between Low-Grade Gliomas(LGG)and High-Grade Gliomas(HGG).LGGs are benign and typically manageable with surgical resection,while HGGs are malignant and more *** research introduces an innovative custom convolutional neural network(CNN)model,*** stands out as a lightweight CNN model compared to its *** research utilized the BraTS 2020 dataset for its *** with the gradient-boosting algorithm,GliomaCNN has achieved an impressive accuracy of 99.1569%.The model’s interpretability is ensured through SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM++).They provide insights into critical decision-making regions for classification *** challenges in identifying tumors in images without visible signs,the model demonstrates remarkable performance in this critical medical application,offering a promising tool for accurate brain tumor diagnosis which paves the way for enhanced early detection and treatment of brain tumors.

关键词： Deep learning magnetic resonance imaging convolutional neural networks explainable AI boosting algorithm ablation

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Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis

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Neural Regeneration Research 2024年第7期19卷 1553-1558页

作者： Sihong Huang Jungong Han Hairong Zheng Mengjun Li Chuxin Huang Xiaoyan Kui Jun Liu Department of Radiology The Second Xiangya HospitalCentral South UniversityChangshaHunan ProvinceChina Department of Computer Science Aberystwyth UniversityAberystwythCeredigionUK Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhenGuangdong ProvinceChina School of Computer Science and Engineering Central South UniversityChangshaHunan ProvinceChina Department of Radiology Quality Control Center of Hunan ProvinceChangshaHunan ProvinceChina Clinical Research Center for Medical Imaging of Hunan Province ChangshaHunan ProvinceChina

Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly *** resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain *** approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and ***,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional *** that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is *** the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain *** this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy ***-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network *** the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention *** than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 ***,better cognitive function was associated with more efficient ***,our data indicated that small-worldness in the acute sta

关键词： cognitive function cross-section follow-up functional connectivity graph theory longitudinal study mild traumatic brain injury prediction small-worldness structural connectivity subnetworks whole brain network

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Interfacial Zn^(2+)-solvation regulator towards reversible and stable Zn anode

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Journal of Energy Chemistry 2025年第1期100卷 684-692页

作者： Miao Zhou Xiongbin Luo Hang Li Shan Guo Zhuang Tong Xiaotao Zhou Xu Li Zhaohui Hou Shuquan Liang Guozhao Fang College of Mechanical Engineering Key Laboratory of Hunan Province for Advanced Carbon-based Functional MaterialsHunan Institute of Science and TechnologyYueyang 414006HunanChina School of Materials Science and Engineering Key Laboratory of Electronic Packaging and Advanced Functional Materials of Hunan ProvinceCentral South UniversityChangsha 410083HunanChina College of Materials and Metallurgy Guizhou UniversityGuiyang 550000GuizhouChina National Energy Metal Resources and New Materials Key Laboratory Central South UniversityChangsha 410083HunanChina

Aqueous zinc-ion batteries (AZIBs) are fundamentally challenged by the instability of the electrode/electrolyte interface,predominantly due to irreversible zinc (Zn) deposition and hydrogen ***,the intricate mechanisms behind the electrochemical discrepancies induced by interfacial Zn^(2+)-solvation and deposition behavior demand comprehensive *** molecules endowed with special functional groups (such as hydroxyl,carboxyl,etc.) have the potential to significantly optimize the solvation structure of Zn^(2+)and regulate the interfacial electric double layer (EDL).By increasing nucleation overpotential and decreasing interfacial free energy,these functional groups facilitate a lower critical nucleation radius,thereby forming an asymptotic nucleation model to promote uniform Zn ***,this study presents a pioneering approach by introducing trace amounts of n-butanol as solvation regulators to engineer the homogenized Zn (H-Zn) anode with a uniform and dense *** interfacial reaction and structure evolution are explored by in/ex-situ experimental techniques,indicating that the H-Zn anode exhibits dendrite-free growth,no by-products,and weak hydrogen evolution,in sharp contrast to the bare ***,the H-Zn anode achieves a remarkable Zn utilization rate of approximately 20% and simultaneously sustains a prolonged cycle life exceeding 500 ***,the H-Zn//NH_(4)V_(4)O^(10)(NVO) full battery showcases exceptional cycle stability,retaining 95.04%capacity retention after 400 cycles at a large current density of 5 A g^(-1).This study enlightens solvation-regulated additives to develop Zn anode with superior utilization efficiency and extended operational lifespan.

关键词： Aqueous zinc-ion batteries Zn^(2+)-solvation structure Interfacial reaction Asymptotic nucleation model Reversible and stable Zn anode

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Delay-Effective Task Offloading technology in Internet of Vehicles: From the Perspective of the Vehicle Platooning

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IEEE Transactions on Communications 2024年第6期73卷 3833-3848页

作者： Zhu, Fuze Liu, Xiaowu Yu, Kan Zhang, Qixun Feng, Zhiyong Li, Dong Qufu Normal University School Of Computer Science Rizhao China Macau University Of Science And Technology School Of Computer Science And Engineering Taipa999078 China Ministry Of Education Beijing University Of Posts And Telecommunications Key Laboratory Of Universal Wireless Communications Beijing100876 China

Task offloading technology plays a crucial role in the Internet of Vehicles (IoV) by minimizing processing delays through the joint optimization of heterogeneous computing resources supported by vehicles, roadside units (RSUs), and macro base stations (MBSs). Previous works have often ignored the wireless interference during the exchange and sharing of task data. Additionally, the potential for vehicles with similar driving behaviors to form vehicle platooning (VEH-PLA) and effectively integrate individual vehicle resources has not been adequately addressed. Furthermore, as a novel resource management paradigm, VEH-PLA should consider task categorization since vehicles within a VEH-PLA may have identical task offloading requestsan aspect that has also received insufficient attention. In this paper, considering wireless interference, vehicle mobility, VEH-PLA, and task categorization, we propose four task offloading models aimed at minimizing processing delays. By utilizing centralized training and decentralized execution (CTDE) based on multi-agent deep reinforcement learning (MADRL), we present a task offloading decision-making method to find the global optimal offloading decision. This results in significant enhancements in resource load balancing and reductions in processing delays. Finally, simulations validate that the proposed method significantly outperforms traditional task offloading approaches in terms of minimizing processing delays while maintaining balanced resource utilization. © 1972-2012 IEEE.

关键词： Deep reinforcement learning

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A dynamic and resource sharing virtual network mapping algorithm

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Digital Communications and Networks 2023年第5期9卷 1101-1112页

作者： Xiancui Xiao Xiangwei Zheng Ji Bian Cun Ji Xinchun Cui School of Information Science and Engineering Shandong Normal UniversityJinan250014China School of Information Engineering Shandong Management UniversityJinan250358China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014China School of Computer Science and Technology Qufu Normal UniversityRizhao276800China

Network virtualization can effectively establish dedicated virtual networks to implement various network ***,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and *** addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation *** on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology *** the node mapping process,three properties of the node are used to measure its mapping ***,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link ***,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource *** former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision *** results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenu

关键词： Network virtualization VNRs Network frameworks Dynamic resource allocation Resource sharing

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KubeSPT: Stateful Pod Teleportation for Service Resilience with Live Migration

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IEEE Transactions on Services Computing 2025年第3期18卷 1500-1514页

作者： Zhang, Hansheng Wu, Song Fan, Hao Huang, Zhuo Xue, Weibin Yu, Chen Ibrahim, Shadi Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong China

Container orchestration systems, such as Kubernetes, streamline containerized application deployment. As more and more applications are being deployed in Kubernetes, there is an increasing need for rescheduling - relocating a running pod to different nodes - due to system upgrades, node failures, and load-balancing optimizations. Live migration, which transfers services from source nodes to target nodes with minimal downtime, is the ideal support for rescheduling. However, implementing live migration for pods that run stateful services is challenging, because Kubernetes manages pods as stateless. First, the current pod's network namespace initialization process causes a mismatch in the network state between the migrated pod and internal containers. Second, migrating the memory state results in extended downtime. Third, Kubernetes operations on pods do not consider preserving the state of the pods. Therefore, we propose KubeSPT to achieve live migration of stateful pods in rescheduling scenarios. Firstly, we synchronize the network state of pods and internal containers by controlling packet flow and implement fast service redirection. Secondly, we introduce a Hot Data and Lazy-Restore method for memory restoration to reduce migration downtime. Finally, we decouple pod migration operations from other Kubernetes operations to ensure compatibility with live migration. Experimental results show that KubeSPT reduces downtime by 86%-93% compared to current rescheduling methods. © 2008-2012 IEEE.

关键词： Restoration

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Insights into a novel nitrogen removal process based on simultaneous anammox and denitrification(SAD) following nitritation with in-situ NOB elimination

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Journal of Environmental sciences 2023年第3期125卷 160-170页

作者： Jing Chen Jia Zeng Yiran He Shiquan Sun Haipeng Wu Yaoyu Zhou Zhenguo Chen Jianhui Wang Hong Chen School of Hydraulic and Environmental Engineering Changsha University of Science&TechnologyChangsha 410114China Engineering and Technical Center of Hunan Provincial Environmental Protection for River-Lake Dredging Pollution Control Changsha 410114China College of Resources and Environment Hunan Agricultural UniversityChangsha 410128China School of Environment and Energy South China University of TechnologyGuangzhou 510006China School of Food science and Bioengineering Changsha University of Science&TechnologyChangsha 410114China

Simultaneous anammox and denitrification(SAD) is an efficient approach to treat wastewater having a low C/N ratio;however, few studies have investigated a combination of SAD and partial nitritation(PN). In this study, a lab-scale up-flow blanket filter(UBF) and zeolite sequence batch reactor(ZSBR) were continuously operated to implement SAD and PN advantages, respectively. The UBF achieved a high total nitrogen(TN) removal efficiency of over 70% during the start-up stage(days 1–50), and reached a TN removal efficiency of 96%in the following 90 days(days 51–140) at COD/NH_(4)^(+)-N ratio of 2.5. The absolute abundance of anammox bateria increased to the highest value of 1.58 × 107copies/μL DNA;Comamonadaceae was predominant in the UBF at the optimal ratio. Meanwhile, ZSBR was initiated on day 115 as fast nitritation process to satisfy the influent requirement for the UBF. The combined process was started on day 140 and then lasted for 30 days, during the combined process, between the two reactors, the UBF was the main contributor for TN(66.5% ± 4.5%)and COD(71.8% ± 4.9%) removal. These results demonstrated that strong SAD occurred in the UBF when following a ZSBR with in-situ NOB elimination. This research presents insights into a novel biological nitrogen removal process for low C/N ratio wastewater treatment.

关键词： Simultaneous anammox and denitrification Up-flow blanket filter Zeolite sequence batch reactor Biological nitrogen removal Wastewater treatment

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TH-SLP: Web Service Link Prediction Based on Topic-aware Heterogeneous Graph Neural Network

TH-SLP: Web Service Link Prediction Based on Topic-aware Het...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Peng, Qian Cao, Buqing Xie, Xiang Liu, Shanpeng Kang, Guosheng Liu, Jianxun Hunan University of Science and Technology Xiangtan School of Computer Science and Engineering Hunan Provincial Key Lab. for Services Computing and Novel Software Technology Hunan China

ISBN: (纸本)9798350304855

With the emergence of more and more Web services, finding suitable services becomes a difficult problem. Service link prediction is employed to disclose relationships among services, which facilitates the further development of service composition, selection, and recommendation. But the existing link prediction approaches simply utilize the structural features of the service network. In reality, the rich text content in service node description documents also carries latent but fine-grained semantics generated by multifaceted topic-aware factors, yet few efforts are committed to mining them. In this paper, we propose a Web service link prediction method based on a topic-aware heterogeneous graph neural network. Specifically, the method consists of two main layers, including the meta-path intra-decomposition and the meta-path inter-mergence. Meta-path intra-decomposition aims to mine the topic distribution of the meta-paths-based context while capturing fine-grained topic-aware semantics. Meta-path inter-mergence uniquely aggregates topic-aware factors according to the mined distribution and adopts a multifaceted attention mechanism to aggregate different meta-paths, enabling service nodes to generate multifaceted topic-aware embeddings that preserve not only the structure and but also the topic-aware semantics. In addition, a topic prior guidance regularization item is set up for quality assurance of multifaceted topic-aware embedding that depends on global knowledge of the unstructured text content in description documents. Experimental results on real datasets show that our proposed model outperforms other existing baselines methods in the link prediction task, successfully validating the effectiveness of our proposed method. © 2023 IEEE.

关键词： Semantics

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Ultimately Bounded Output Feedback Control for Networked Nonlinear Systems With Unreliable Communication Channel: A Buffer-Aided Strategy

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1566-1578页

作者： Yuhan Zhang Zidong Wang Lei Zou Yun Chen Guoping Lu the College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China IEEE the Department of Computer Science Brunel UniversityUB83PHUnited Kingdom the College of Information Science and Technology Donghua UniversityShanghai 201620 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the School of Automation Hangzhou Dianzi UniversityHangzhou 310018China the School of Electrical Engineering Nantong UniversityNantong 226019China

This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication *** transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear *** the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observerbased controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.

关键词： Buffer-aided strategy neural networks nonlinear control output-feedback control unreliable communication channel

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EAODroid: Android Malware Detection Based on Enhanced API Order

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Chinese Journal of Electronics 2023年第5期32卷 1169-1178页

作者： HUANG Lu XUE Jingfeng WANG Yong QU Dacheng CHEN Junbao ZHANG Nan ZHANG Li School of Computer Science and Technology Beijing Institute of Technology Department of Media Engineering Communication University of Zhejiang

The development of smart mobile devices brings convenience to people's lives, but also provides a breeding ground for Android malware. The sharp increasing malware poses a disastrous threat to personal privacy in the information age. Based on the fact that malware heavily resorts to system application programming interfaces(APIs) to perform its malicious actions,there has been a variety of API-based detection *** of them do not consider the relationship between APIs. We contribute a new approach based on the enhanced API order for Android malware detection, named EAODroid, which learns the similarity of system APIs from a large number of API sequences and groups similar APIs into clusters. The extracted API clusters are further used to enhance the original API calls executed by an app to characterize behaviors and perform classification. We perform multi-dimensional experiments to evaluate EAODroid on three datasets with ground truth. We compare with many state-of-the-art works, showing that EAODroid achieves effective performance in Android malware detection.

关键词： Performance evaluation Privacy Programming Information age Malware Mobile handsets Behavioral sciences

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