Economic and technological progress in the cloud are the main topics of this article. The essay examines the question of whether or not it makes financial sense to build software in the cloud, vs in-house. This resear...
详细信息
Economic and technological progress in the cloud are the main topics of this article. The essay examines the question of whether or not it makes financial sense to build software in the cloud, vs in-house. This research work provides an overview of the current model-based re-engineering practises. A novel and more thorough method is outlined in Business Process Model and Notation (BPMN) with some example activities, inputs, and outputs. As an integral element of the primary re-engineering process, reverse engineering is also something to be considered. Therefore, it expands on the concept of “SBSE for the cloud,” providing actionable formulations of problems associated with cloud computing. The system has been built in the cloud to track the health of analytical services while they are being called into use. As an example of analytical services, a number of implementations of data mining methods are hosted from a number of packages. Their Quality of Service (QoS) values are also sampled by running them on certain real datasets. Based on the analysis of the KSEA National Math Competition event management system, this project will suggest some guidelines for software reengineering using AWS cloud computing services and web application technologies. Using these best practises, the informational gaps in software reengineering are bridged for web applications built in with cloud computing frameworks.
In contrast to the general population, behavior recognition among the elderly poses increased specificity and difficulty, rendering the reliability and usability aspects of safety monitoring systems for the elderly mo...
详细信息
In contrast to the general population, behavior recognition among the elderly poses increased specificity and difficulty, rendering the reliability and usability aspects of safety monitoring systems for the elderly more challenging. Hence, this study proposes a multi-modal perception-based solution for an elderly safety monitoring recognition system. The proposed approach introduces a recognition algorithm based on multi-modal cross-attention mechanism, innovatively incorporating complex information such as scene context and voice to achieve more accurate behavior recognition. By fusing four modalities, namely image, skeleton, sensor data, and audio, we further enhance the accuracy of recognition. Additionally, we introduce a novel human-robot interaction mode, where the system associates directly recognized intentions with robotic actions without explicit commands, delivering a more natural and efficient elderly assistance paradigm. This mode not only elevates the level of safety monitoring for the elderly but also facilitates a more natural and efficient caregiving approach. Experimental results demonstrate significant improvement in recognition accuracy for 11 typical elderly behaviors compared to existing methods.
Online social networks are becoming more and more popular, according to recent trends. The user's primary concern is the secure preservation of their data and privacy. A well-known method for preventing individual...
详细信息
Unikernels provide an efficient and lightweight way to deploy cloud computing services in application-specialized and single-address-space virtual machines (VMs). They can efficiently deploy hundreds of unikernel-base...
详细信息
Unikernels provide an efficient and lightweight way to deploy cloud computing services in application-specialized and single-address-space virtual machines (VMs). They can efficiently deploy hundreds of unikernel-based VMs in a single physical server. In such a cloud computing platform, main memory is the primary bottleneck resource for high-density application deployment. Recently, non-volatile memory (NVM) technologies has become increasingly popular in cloud data centers because they can offer extremely large memory capacity at a low expense. However, there still remain many challenges to utilize NVMs for unikernel-based VMs, such as the difficulty of heterogeneous memory allocation and high performance overhead of address *** this paper, we present UCat, a heterogeneous memory management mechanism that support multi-grained memory allocation for unikernels. We propose front-end/back-end cooperative address space mapping to expose the host memory heterogeneity to unikernels. UCat exploits large pages to reduce the cost of two-layer address translation in virtualization environments, and leverages slab allocation to reduce memory waste due to internal memory fragmentation. We implement UCat based on a popular unikernel--OSv and conduct extensive experiments to evaluate its efficiency. Experimental results show that UCat can reduce the memory consumption of unikernels by 50% and TLB miss rate by 41%, and improve the throughput of real-world benchmarks such as memslap and YCSB by up to 18.5% and 14.8%, respectively.
Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar...
详细信息
Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar flares in order to ensure the safety of human ***,the research focuses on two directions:first,identifying predictors with more physical information and higher prediction accuracy,and second,building flare prediction models that can effectively handle complex observational *** terms of flare observability and predictability,this paper analyses multiple dimensions of solar flare observability and evaluates the potential of observational parameters in *** flare prediction models,the paper focuses on data-driven models and physical models,with an emphasis on the advantages of deep learning techniques in dealing with complex and high-dimensional *** reviewing existing traditional machine learning,deep learning,and fusion methods,the key roles of these techniques in improving prediction accuracy and efficiency are *** prevailing challenges,this study discusses the main challenges currently faced in solar flare prediction,such as the complexity of flare samples,the multimodality of observational data,and the interpretability of *** conclusion summarizes these findings and proposes future research directions and potential technology advancement.
For the diagnostics and health management of lithium-ion batteries,numerous models have been developed to understand their degradation *** models typically fall into two categories:data-driven models and physical mode...
详细信息
For the diagnostics and health management of lithium-ion batteries,numerous models have been developed to understand their degradation *** models typically fall into two categories:data-driven models and physical models,each offering unique advantages but also facing ***-informed neural networks(PINNs)provide a robust framework to integrate data-driven models with physical principles,ensuring consistency with underlying physics while enabling generalization across diverse operational *** study introduces a PINN-based approach to reconstruct open circuit voltage(OCV)curves and estimate key ageing parameters at both the cell and electrode *** parameters include available capacity,electrode capacities,and lithium inventory *** proposed method integrates OCV reconstruction models as functional components into convolutional neural networks(CNNs)and is validated using a public *** results reveal that the estimated ageing parameters closely align with those obtained through offline OCV tests,with errors in reconstructed OCV curves remaining within 15 *** demonstrates the ability of the method to deliver fast and accurate degradation diagnostics at the electrode level,advancing the potential for precise and efficient battery health management.
When the ground communication base stations in the target area are severely destroyed,the deployment of Unmanned Aerial Vehicle(UAV)ad hoc networks can provide people with temporary communication ***,it is necessary t...
详细信息
The current large-scale Internet of Things(IoT)networks typically generate high-velocity network traffic *** use IoT devices to create botnets and launch attacks,such as DDoS,Spamming,Cryptocurrency mining,Phishing,**...
详细信息
The current large-scale Internet of Things(IoT)networks typically generate high-velocity network traffic *** use IoT devices to create botnets and launch attacks,such as DDoS,Spamming,Cryptocurrency mining,Phishing,*** service providers of large-scale IoT networks need to set up a data pipeline to collect the vast network traffic data from the IoT devices,store it,analyze it,and report the malicious IoT devices and types of ***,the attacks originating from IoT devices are dynamic,as attackers launch one kind of attack at one time and another kind of attack at another *** number of attacks and benign instances also vary from time to *** phenomenon of change in attack patterns is called concept ***,the attack detection system must learn continuously from the ever-changing real-time attack patterns in large-scale IoT network *** meet this requirement,in this work,we propose a data pipeline with Apache Kafka,Apache Spark structured streaming,and MongoDB that can adapt to the ever-changing attack patterns in real time and classify attacks in large-scale IoT *** concept drift is detected,the proposed system retrains the classifier with the instances that cause the drift and a representative subsample instances from the previous training of the *** proposed approach is evaluated with the latest dataset,IoT23,which consists of benign and several attack instances from various IoT *** classification accuracy is improved from 97.8%to 99.46%by the proposed *** training time of distributed random forest algorithm is also studied by varying the number of cores in Apache Spark environment.
Lithium plating is a detrimental phenomenon in lithium-ion cells that compromises both functionality and *** study investigates electro-chemo-mechanical behaviors of lithium plating in lithium iron phosphate pouch cel...
详细信息
Lithium plating is a detrimental phenomenon in lithium-ion cells that compromises both functionality and *** study investigates electro-chemo-mechanical behaviors of lithium plating in lithium iron phosphate pouch cells under different external *** force microscopy nanoindentation is performed on the graphite electrode to analyze the influence of external pressure on solid-electrolyte interphase(SEI),revealing that the mechanical strength of SEI,indicated by Young's modulus,increases with the presence of external ***,an improved phase field model for lithium plating is developed by incorporating electrochemical parameterization based on nonequilibrium *** results demonstrate that higher pressure promotes lateral lithium deposition,covering a larger area of ***,electrochemical impedance spectroscopy and thickness measurements of the pouch cells are conducted during overcharge,showing that external pressure suppresses gas generation and thus increases the proportion of lithium deposition among galvanostatic overcharge *** integrating experimental results with numerical simulations,it is demonstrated that moderate pressure mitigates SEI damage during lithium plating,while both insufficient and excessive pressure may exacerbate *** study offers new insights into optimizing the design and operation of lithium iron phosphate pouch cells under external pressures.
This paper introduces a novel electrically small antenna (ESA) with an inductive-capacitive resonator (LC-R) design tailored for compact handheld devices such as dongles, routers, tablets, and mobile handsets. The ESA...
详细信息
暂无评论