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Using Cluster Computers in Bioinformatics Research
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作者 周澄 郁松年 《Journal of Shanghai University(English Edition)》 CAS 2003年第4期370-374,共5页
In the last ten years, high-performance and massively parallel computing technology comes into a high speed developing phase and is used in all fields. The cluster computer systems are also being widely used for their... In the last ten years, high-performance and massively parallel computing technology comes into a high speed developing phase and is used in all fields. The cluster computer systems are also being widely used for their low cost and high performance. In bioinformatics research, solving a problem with computer usually takes hours even days. To speed up research, high-performance cluster computers are considered to be a good platform. Moving into the new MPP (massively parallel processing) system, the original algorithm should be parallelized in a proper way. In this paper, a new parallelizing method of useful sequence alignment algorithm (Smith-Waterman) is designed based on its optimizing algorithm already exists. The result is gratifying. 展开更多
关键词 MPP (massively parallel processing) algorithm parallelization clusterING BIOINFORMATICS sequence alignments algorithm.
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基于Blending-Clustering集成学习的大坝变形预测模型
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作者 冯子强 李登华 丁勇 《水利水电技术(中英文)》 北大核心 2024年第4期59-70,共12页
【目的】变形是反映大坝结构性态最直观的效应量,构建科学合理的变形预测模型是保障大坝安全健康运行的重要手段。针对传统大坝变形预测模型预测精度低、误报率高等问题导致的错误报警现象,【方法】选取不同预测模型和聚类算法集成,构... 【目的】变形是反映大坝结构性态最直观的效应量,构建科学合理的变形预测模型是保障大坝安全健康运行的重要手段。针对传统大坝变形预测模型预测精度低、误报率高等问题导致的错误报警现象,【方法】选取不同预测模型和聚类算法集成,构建了一种Blending-Clustering集成学习的大坝变形预测模型,该模型以Blending对单一预测模型集成提升预测精度为核心,并通过Clustering聚类优选预测值改善模型稳定性。以新疆某面板堆石坝变形监测数据为实例分析,通过多模型预测性能比较,对所提出模型的预测精度和稳定性进行全面评估。【结果】结果显示:Blending-Clustering模型将预测模型和聚类算法集成,均方根误差(RMSE)和归一化平均百分比误差(nMAPE)明显降低,模型的预测精度得到显著提高;回归相关系数(R~2)得到提升,模型具备更强的拟合能力;在面板堆石坝上22个测点变形数据集上的预测评价指标波动范围更小,模型的泛化性和稳定性得到有效增强。【结论】结果表明:Blending-Clustering集成预测模型对于预测精度、泛化性和稳定性均有明显提升,在实际工程具有一定的应用价值。 展开更多
关键词 大坝 变形 预测模型 Blending集成 clustering集成 模型融合
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Formation and transformation of metastable LPSO building blocks clusters in Mg-Gd-Y-Zn-Zr alloys by spinodal decomposition and heterogeneous nucleation 被引量:1
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作者 Xin Zhao Zhong Yang +2 位作者 Jiachen Zhang Minxian Liang Liying Wang 《Journal of Magnesium and Alloys》 SCIE EI CAS CSCD 2024年第2期673-686,共14页
To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)stru... To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)structures in the Mg-Gd-Y-Zn-Zr alloy annealed at 300℃~500℃.Various types of metastable LPSO building block clusters were found to exist in alloy structures at different temperatures,which precipitate during the solidification and homogenization process.The stability of Zn/Y clusters is explained by the first principles of density functional theory.The LPSO structure is distinguished by the arrangement of its different Zn/Y enriched LPSO structural units,which comprises local fcc stacking sequences upon a tightly packed plane.The presence of solute atoms causes local lattice distortion,thereby enabling the rearrangement of Mg atoms in the different configurations in the local lattice,and local HCP-FCC transitions occur between Mg and Zn atoms occupying the nearest neighbor positions.This finding indicates that LPSO structures can generate necessary Schockley partial dislocations on specific slip surfaces,providing direct evidence of the transition from 18R to 14H.Growth of the LPSO,devoid of any defects and non-coherent interfaces,was observed separately from other precipitated phases.As a result,the precipitation sequence of LPSO in the solidification stage was as follows:Zn/Ycluster+Mg layers→various metastable LPSO building block clusters→18R/24R LPSO;whereas the precipitation sequence of LPSO during homogenization treatment was observed to be as follows:18R LPSO→various metastable LPSO building block clusters→14H LPSO.Of these,14H LPSO was found to be the most thermodynamically stable structure. 展开更多
关键词 LPSO Spinodal decomposition Homogenization treatment clusterS Phase transformation
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Unsaturated bi-heterometal clusters in metal-vacancy sites of 2D MoS2 for efficient hydrogen evolution 被引量:1
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作者 Gonglei Shao Jie Xu +4 位作者 Shasha Gao Zhang Zhang Song Liu Xu Zhang Zhen Zhou 《Carbon Energy》 SCIE EI CAS CSCD 2024年第3期264-275,共12页
The valence states and coordination structures of doped heterometal atoms in two-dimensional(2D)nanomaterials lack predictable regulation strategies.Hence,a robust method is proposed to form unsaturated heteroatom clu... The valence states and coordination structures of doped heterometal atoms in two-dimensional(2D)nanomaterials lack predictable regulation strategies.Hence,a robust method is proposed to form unsaturated heteroatom clusters via the metal-vacancy restraint mechanism,which can precisely regulate the bonding and valence state of heterometal atoms doped in 2D molybdenum disulfide.The unsaturated valence state of heterometal Pt and Ru cluster atoms form a spatial coordination structure with Pt–S and Ru–O–S as catalytically active sites.Among them,the strong binding energy of negatively charged suspended S and O sites for H+,as well as the weak adsorption of positively charged unsaturated heterometal atoms for H*,reduces the energy barrier of the hydrogen evolution reaction proved by theoretical calculation.Whereupon,the electrocatalytic hydrogen evolution performance is markedly improved by the ensemble effect of unsaturated heterometal atoms and highlighted with an overpotential of 84 mV and Tafel slope of 68.5 mV dec^(−1).In brief,this metal vacancy-induced valence state regulation of heterometal can manipulate the coordination structure and catalytic activity of heterometal atoms doped in the 2D atomic lattice but not limited to 2D nanomaterials. 展开更多
关键词 clusterS hydrogen evolution reaction metal vacancy MOS2 unsaturated heterometal
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Deep Learning and Tensor-Based Multiple Clustering Approaches for Cyber-Physical-Social Applications 被引量:1
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作者 Hongjun Zhang Hao Zhang +3 位作者 Yu Lei Hao Ye Peng Li Desheng Shi 《Computers, Materials & Continua》 SCIE EI 2024年第3期4109-4128,共20页
The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Inst... The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed at enhancing their positive aspects and mitigating their negative repercussions. To achieve this, the study introduces a weight learning method grounded in multi-linear attribute ranking. This approach serves to evaluate the significance of attribute combinations across all feature spaces. Additionally, a novel clustering method based on tensors is proposed to elevate the quality of clustering while effectively distinguishing selected features. The methodology incorporates a weighted average similarity matrix and optionally integrates weighted Euclidean distance, contributing to a more nuanced understanding of attribute importance. The analysis of the proposed methods yields significant findings. The weight learning method proves instrumental in discerning the importance of attribute combinations, shedding light on key aspects within feature spaces. Simultaneously, the clustering method based on tensors exhibits improved efficacy in enhancing clustering quality and feature distinction. This not only advances our understanding of attribute importance but also paves the way for more nuanced data analysis methodologies. In conclusion, this research underscores the pivotal role of network platforms in contemporary society, emphasizing their potential for both positive contributions and adverse consequences. The proposed methodologies offer novel approaches to address these dualities, providing a foundation for future research and practical applications. Ultimately, this study contributes to the ongoing discourse on optimizing the utility of network platforms while minimizing their negative impacts. 展开更多
关键词 Network platform tensor-based clustering weight learning multi-linear euclidean
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Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks 被引量:1
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作者 Youseef Alotaibi B.Rajasekar +1 位作者 R.Jayalakshmi Surendran Rajendran 《Computers, Materials & Continua》 SCIE EI 2024年第3期4243-4262,共20页
Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effect... Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods. 展开更多
关键词 Vehicular networks communication protocol clusterING falcon optimization algorithm ROUTING
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Engineering of oxygen vacancy and bismuth cluster assisted ultrathin Bi_(12)O_(17)Cl_(2)nanosheets with efficient and selective photoreduction of CO_(2)to CO 被引量:1
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作者 Meili Guan Ni Lu +7 位作者 Xuan Zhang Qiuwan Wang Jian Bao Guiye Chen Hao Yu Huaming Li Jiexiang Xia Xuezhong Gong 《Carbon Energy》 SCIE EI CAS CSCD 2024年第4期1-11,共11页
The photocatalytic conversion of CO_(2)into solar‐powered fuels is viewed as a forward‐looking strategy to address energy scarcity and global warming.This work demonstrated the selective photoreduction of CO_(2)to C... The photocatalytic conversion of CO_(2)into solar‐powered fuels is viewed as a forward‐looking strategy to address energy scarcity and global warming.This work demonstrated the selective photoreduction of CO_(2)to CO using ultrathin Bi_(12)O_(17)Cl_(2)nanosheets decorated with hydrothermally synthesized bismuth clusters and oxygen vacancies(OVs).The characterizations revealed that the coexistences of OVs and Bi clusters generated in situ contributed to the high efficiency of CO_(2)–CO conversion(64.3μmol g^(−1)h^(−1))and perfect selectivity.The OVs on the facet(001)of the ultrathin Bi_(12)O_(17)Cl_(2)nanosheets serve as sites for CO_(2)adsorption and activation sites,capturing photoexcited electrons and prolonging light absorption due to defect states.In addition,the Bi‐cluster generated in situ offers the ability to trap holes and the surface plasmonic resonance effect.This study offers great potential for the construction of semiconductor hybrids as multiphotocatalysts,capable of being used for the elimination and conversion of CO_(2)in terms of energy and environment. 展开更多
关键词 Bi cluster Bi_(12)O_(17)Cl_(2)nanosheet oxygen vacancy photocatalytic CO_(2)reduction
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Clustered张拉整体结构的动力学建模
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作者 张子宇 王彤 周斌 《振动与冲击》 EI CSCD 北大核心 2024年第16期287-294,共8页
针对clustered张拉整体结构,提出了一种基于任意拉格朗日-欧拉(arbitrary Lagrangian-Eulerian, ALE)法的多体动力学模型。相较于传统的拉格朗日法模型,该研究中的模型具有更为简单的运动学约束。首先,引入了一种ALE时变长度索单元,其... 针对clustered张拉整体结构,提出了一种基于任意拉格朗日-欧拉(arbitrary Lagrangian-Eulerian, ALE)法的多体动力学模型。相较于传统的拉格朗日法模型,该研究中的模型具有更为简单的运动学约束。首先,引入了一种ALE时变长度索单元,其网格节点与物质点可以独立运动,提供了一种自然的方式描述结构中运动的滑轮和滑动绳索;其次,利用达朗贝尔原理,推导了该单元的广义力向量并计算了相应的雅可比矩阵;然后,建立了张拉整体系统的动力学方程,并利用广义α算法对其进行求解,选取节点的全局位置坐标和物质坐标作为广义坐标,其中全局位置坐标可以被不同物体共享,以减少动力学方程的自由度数和消除物体间的约束;最后,展示了一个数值算例,10层可折叠张拉整体塔架,对其折叠过程进行了准静态和动力学仿真,验证了模型的有效性。所提出的模型和算法可为clustered张拉整体结构的设计提供理论指导,具有工程意义。 展开更多
关键词 多体动力学模型 clustered张拉整体 任意拉格朗日-欧拉(ALE) 可展开空间结构
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基于Windows Server Failover Cluster的Apache故障转移集群应用实践
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作者 李应晓 矫健 +2 位作者 宋庆章 吴连强 徐庶 《长江信息通信》 2024年第10期166-168,共3页
在当前互联网时代,Web应用程序的高可用性和可靠性是确保业务持续运行的关键因素。针对Apache Web服务器,介绍了利用Windows Server 2019 Failover Cluster构建Apache故障转移集群的实践方案。通过配置两个节点的故障转移集群,当某个节... 在当前互联网时代,Web应用程序的高可用性和可靠性是确保业务持续运行的关键因素。针对Apache Web服务器,介绍了利用Windows Server 2019 Failover Cluster构建Apache故障转移集群的实践方案。通过配置两个节点的故障转移集群,当某个节点发生故障时,Apache服务将自动在另一个节点上重新启动,从而最大程度地减少系统中断的时间,提高Web应用的可用性。详细阐述了集群搭建的具体步骤、配置要点、集群验证方法以及运行时的监控与维护方法,为构建高可用Apache Web服务器提供一种实用的解决方案。 展开更多
关键词 Windows Server 2019 Failover cluster APACHE 故障转移 集群
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Effects of interstitial cluster mobility on dislocation loops evolution under irradiation of austenitic steel
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作者 Xin‑Hua Yan Lu Sun +5 位作者 Du Zhou Teng Xie Chang Peng Ye‑Xin Yang Li Chen Zhen‑Feng Tong 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2024年第8期69-78,共10页
The evolution of dislocation loops in austenitic steels irradiated with Fe^(+)is investigated using cluster dynamics(CD)simulations by developing a CD model.The CD predictions are compared with experimental results in... The evolution of dislocation loops in austenitic steels irradiated with Fe^(+)is investigated using cluster dynamics(CD)simulations by developing a CD model.The CD predictions are compared with experimental results in the literature.The number density and average diameter of the dislocation loops obtained from the CD simulations are in good agreement with the experimental data obtained from transmission electron microscopy(TEM)observations of Fe~+-irradiated Solution Annealed 304,Cold Worked 316,and HR3 austenitic steels in the literature.The CD simulation results demonstrate that the diffusion of in-cascade interstitial clusters plays a major role in the dislocation loop density and dislocation loop growth;in particular,for the HR3 austenitic steel,the CD model has verified the effect of temperature on the density and size of the dislocation loops. 展开更多
关键词 cluster dynamics Dislocation loops In-cascade interstitial clusters Austenitic steels
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Weak Merging Scenario of CLASH Cluster A209
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作者 Wen-Cheng Feng Heng Yu +7 位作者 Hai-Hui Zhao Xiao-Lan Hou Shu-Mei Jia Cheng-Kui Li Yu-Lin Cheng Paolo Tozzi Ming Sun Yong Chen 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2024年第4期174-182,共9页
We study the structural and dynamical properties of A209 based on Chandra and XMM-Newton observations.We obtain detailed temperature,pressure,and entropy maps with the contour binning method,and find a hot region in t... We study the structural and dynamical properties of A209 based on Chandra and XMM-Newton observations.We obtain detailed temperature,pressure,and entropy maps with the contour binning method,and find a hot region in the NW direction.The X-ray brightness residual map and corresponding temperature profiles reveal a possible shock front in the NW direction and a cold front feature in the SE direction.Combined with the galaxy luminosity density map we propose a weak merger scenario.A young sub-cluster passing from the SE to NW direction could explain the optical subpeak,the intracluster medium temperature map,the X-ray surface brightness excess,and the X-ray peak offset together. 展开更多
关键词 X rays:galaxies:clusters galaxies:clusters:intracluster medium galaxies:clusters:Abell 209
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Knowledge-Driven Possibilistic Clustering with Automatic Cluster Elimination
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作者 Xianghui Hu Yiming Tang +2 位作者 Witold Pedrycz Jiuchuan Jiang Yichuan Jiang 《Computers, Materials & Continua》 SCIE EI 2024年第9期4917-4945,共29页
Traditional Fuzzy C-Means(FCM)and Possibilistic C-Means(PCM)clustering algorithms are data-driven,and their objective function minimization process is based on the available numeric data.Recently,knowledge hints have ... Traditional Fuzzy C-Means(FCM)and Possibilistic C-Means(PCM)clustering algorithms are data-driven,and their objective function minimization process is based on the available numeric data.Recently,knowledge hints have been introduced to formknowledge-driven clustering algorithms,which reveal a data structure that considers not only the relationships between data but also the compatibility with knowledge hints.However,these algorithms cannot produce the optimal number of clusters by the clustering algorithm itself;they require the assistance of evaluation indices.Moreover,knowledge hints are usually used as part of the data structure(directly replacing some clustering centers),which severely limits the flexibility of the algorithm and can lead to knowledgemisguidance.To solve this problem,this study designs a newknowledge-driven clustering algorithmcalled the PCM clusteringwith High-density Points(HP-PCM),in which domain knowledge is represented in the form of so-called high-density points.First,a newdatadensitycalculation function is proposed.The Density Knowledge Points Extraction(DKPE)method is established to filter out high-density points from the dataset to form knowledge hints.Then,these hints are incorporated into the PCM objective function so that the clustering algorithm is guided by high-density points to discover the natural data structure.Finally,the initial number of clusters is set to be greater than the true one based on the number of knowledge hints.Then,the HP-PCM algorithm automatically determines the final number of clusters during the clustering process by considering the cluster elimination mechanism.Through experimental studies,including some comparative analyses,the results highlight the effectiveness of the proposed algorithm,such as the increased success rate in clustering,the ability to determine the optimal cluster number,and the faster convergence speed. 展开更多
关键词 Fuzzy C-Means(FCM) possibilistic clustering optimal number of clusters knowledge-driven machine learning fuzzy logic
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A novel method for clustering cellular data to improve classification
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作者 Diek W.Wheeler Giorgio A.Ascoli 《Neural Regeneration Research》 SCIE CAS 2025年第9期2697-2705,共9页
Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subse... Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons. 展开更多
关键词 cellular data clustering dendrogram data classification Levene's one-tailed statistical test unsupervised hierarchical clustering
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Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network
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作者 Ruchun Jia Jianwei Zhang +2 位作者 Yi Lin Yunxiang Han Feike Yang 《Computers, Materials & Continua》 SCIE EI 2024年第5期2523-2546,共24页
In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set f... In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network. 展开更多
关键词 Air traffic control network security attack behavior cluster detection behavioral characteristics information gain cluster threshold automatic encoder
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Multiscale and Auto-Tuned Semi-Supervised Deep Subspace Clustering and Its Application in Brain Tumor Clustering
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作者 Zhenyu Qian Yizhang Jiang +4 位作者 Zhou Hong Lijun Huang Fengda Li Khin Wee Lai Kaijian Xia 《Computers, Materials & Continua》 SCIE EI 2024年第6期4741-4762,共22页
In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world da... In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data,particularly in the field of medical imaging.Traditional deep subspace clustering algorithms,which are mostly unsupervised,are limited in their ability to effectively utilize the inherent prior knowledge in medical images.Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process,thereby enhancing the discriminative power of the feature representations.Additionally,the multi-scale feature extraction mechanism is designed to adapt to the complexity of medical imaging data,resulting in more accurate clustering performance.To address the difficulty of hyperparameter selection in deep subspace clustering,this paper employs a Bayesian optimization algorithm for adaptive tuning of hyperparameters related to subspace clustering,prior knowledge constraints,and model loss weights.Extensive experiments on standard clustering datasets,including ORL,Coil20,and Coil100,validate the effectiveness of the MAS-DSC algorithm.The results show that with its multi-scale network structure and Bayesian hyperparameter optimization,MAS-DSC achieves excellent clustering results on these datasets.Furthermore,tests on a brain tumor dataset demonstrate the robustness of the algorithm and its ability to leverage prior knowledge for efficient feature extraction and enhanced clustering performance within a semi-supervised learning framework. 展开更多
关键词 Deep subspace clustering multiscale network structure automatic hyperparameter tuning SEMI-SUPERVISED medical image clustering
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Thermal stable Pt clusters anchored by K/TiO_(2)—Al_(2)O_(3)for efficient cycloalkane dehydrogenation
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作者 Zhendong Wang Bofeng Zhang +1 位作者 Guozhu Liu Xiangwen Zhang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第8期187-198,共12页
Catalytic dehydrogenation of cycloalkanes is considered a valuable endothermic process for alleviating the thermal barrier issue of hypersonic vehicles.However,conventional Pt-based catalysts often face the severe pro... Catalytic dehydrogenation of cycloalkanes is considered a valuable endothermic process for alleviating the thermal barrier issue of hypersonic vehicles.However,conventional Pt-based catalysts often face the severe problem of metal sintering under high-temperature conditions.Herein,we develop an efficient K_(2)CO_(3)-modified Pt/TiO_(2)—Al_(2)O_(3)(K—Pt/TA)for cycloalkane dehydrogenation.The optimized K—Pt/TA showed a high specific activity above 27.9 mol·mol^(-1)·s^(-1)(H_(2)/Pt),with toluene selectivity above 90.0%at 600℃with a high weight hourly space velocity of 266.4 h^(-1).The introduction of alkali metal ions could generate titanate layers after high-temperature hydrogen reduction treatment,which promotes the generation of oxygen vacancy defects to anchored Pt clusters.In addition,the titanate layers could weaken the surface acidity of catalysts and inhibit side reactions,including pyrolysis,polymerization,and isomerization reactions.Thus,this work provides a modification method to develop efficient and stable dehydrogenation catalysts under high-temperature conditions. 展开更多
关键词 Cycloalkane dehydrogenation Pt clusters Oxygen vacancy defects COKING Stability DEACTIVATION
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Design and construction of charged-particle telescope array for study of exotic nuclear clustering structure
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作者 Zheng‑Li Liao Xi‑Guang Cao +2 位作者 Yu‑Xuan Yang Chang‑Bo Fu Xian‑Gai Deng 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2024年第8期114-123,共10页
The exploration of exotic shapes and properties of atomic nuclei,e.g.,αcluster and toroidal shape,is a fascinating field in nuclear physics.To study the decay of these nuclei,a novel detector aimed at detecting multi... The exploration of exotic shapes and properties of atomic nuclei,e.g.,αcluster and toroidal shape,is a fascinating field in nuclear physics.To study the decay of these nuclei,a novel detector aimed at detecting multipleα-particle events was designed and constructed.The detector comprises two layers of double-sided silicon strip detectors(DSSD)and a cesium iodide scintillator array coupled with silicon photomultipliers array as light sensors,which has the advantages of their small size,fast response,and large dynamic range.DSSDs coupled with cesium iodide crystal arrays are used to distinguish multipleαhits.The detector array has a compact and integrated design that can be adapted to different experimental conditions.The detector array was simulated using Geant4,and the excitation energy spectra of someα-clustering nuclei were reconstructed to demonstrate the performance.The simulation results show that the detector array has excellent angular and energy resolutions,enabling effective reconstruction of the nuclear excited state by multipleαparticle events.This detector offers a new and powerful tool for nuclear physics experiments and has the potential to discover interesting physical phenomena related to exotic nuclear structures and their decay mechanisms. 展开更多
关键词 cluster decay Toroidal structure Telescope array SIPM Energy resolution
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A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters
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作者 Zhongshang Chen Ji Feng +1 位作者 Fapeng Cai Degang Yang 《Computers, Materials & Continua》 SCIE EI 2024年第8期2031-2048,共18页
In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared... In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple structures.In life,people’s first instinct for complex things is to divide them into multiple parts to complete.Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures.Taking inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold clusters.Tested on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes. 展开更多
关键词 cluster analysis shared natural neighbor hierarchical clustering
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Fixed-Time Cluster Optimization for Multi-Agent Systems Based on Piecewise Power-Law Design
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作者 Suna Duan Xinchun Jia Xiaobo Chi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第5期1301-1303,共3页
Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective fun... Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective functions of all clusters.A novel piecewise power-law control protocol with cooperative-competition relations is proposed.Furthermore,a sufficient condition is obtained to ensure that the FOMASs achieve the cluster consensus within an FXT. 展开更多
关键词 AGENT cluster OPTIMIZATION
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Advances of Synergistic Electrocatalysis Between Single Atoms and Nanoparticles/Clusters
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作者 Guanyu Luo Min Song +6 位作者 Qian Zhang Lulu An Tao Shen Shuang Wang Hanyu Hu Xiao Huang Deli Wang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2024年第11期377-412,共36页
Combining single atoms with clusters or nanoparticles is an emerging tactic to design efficient electrocatalysts.Both synergy effect and high atomic utilization of active sites in the composite catalysts result in enh... Combining single atoms with clusters or nanoparticles is an emerging tactic to design efficient electrocatalysts.Both synergy effect and high atomic utilization of active sites in the composite catalysts result in enhanced electrocatalytic performance,simultaneously provide a radical analysis of the interrelationship between structure and activity.In this review,the recent advances of single-atomic site catalysts coupled with clusters or nanoparticles are emphasized.Firstly,the synthetic strategies,characterization,dynamics and types of single atoms coupled with clusters/nanoparticles are introduced,and then the key factors controlling the structure of the composite catalysts are discussed.Next,several clean energy catalytic reactions performed over the synergistic composite catalysts are illustrated.Eventually,the encountering challenges and recommendations for the future advancement of synergistic structure in energy-transformation electrocatalysis are outlined. 展开更多
关键词 Single atoms NANOPARTICLES clusterS Synergistic composite catalysts Synergistic effect
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