The comet assay is a versatile method used to determine the DNA damage in individual cells. The cells processed by this technique preserve the stable genetic material in the head of the comet and the unstable portion ...
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ISBN:
(纸本)9783031829307;9783031829314
The comet assay is a versatile method used to determine the DNA damage in individual cells. The cells processed by this technique preserve the stable genetic material in the head of the comet and the unstable portion of DNA in the tail. The analysis of the resulting microscopic images from this test must be carried out by an expert, who must precisely determine the extent of DNA liberated from the head of the comet, since it is related to the level of damage. Since this is a time-consuming and very specialized task, the objective of this research is to develop a computational system, based on the use of a convolutional neural network, for the automatic classification of cells processed by comet assay according to the level of DNA damage they present.
As energy systems evolve, single-system economic optimization no longer meets the growing multi-energy demands of users. To address this problem, this paper proposes a multi-objective optimization method for distribut...
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In this era, Peer-to-Peer (P2P) networks have developed as a revolutionized network for data distribution and alternate to traditional client-server network. The features of P2P networks allow a distributed group of u...
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Nowadays, anew generation of decentralized internet framework, coined as Web3.0, is emerging. However, due to the insufficient computing power on the user side and the know-your-customer regulatory requirements, it is...
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Nowadays, anew generation of decentralized internet framework, coined as Web3.0, is emerging. However, due to the insufficient computing power on the user side and the know-your-customer regulatory requirements, it is unrealistic to fully achieve decentralization in Web3.0 currently. The service provider-intermediated architecture seems more practical by including federated service providers. At the same time, in order to fully stimulate users to create and share contents in the era of Web3.0, the importance of digital assets, e.g., digit tokens and cryptocurrencies, is increasing. Asa result, whether digital asset transfer can be securely and efficiently accommodated determines the further development of Web3.0. Blockchain is believed to be one effective solution to guarantee the security of digital asset transfer. However, existing works either target fully decentralized scenarios or fail to settle digital asset transfers with high efficiency. Thus in this paper, a formal yet novel service provider-intermediated architecture is firstly proposed to closely align with the practical requirements of Web3.0. Then, an efficient privacy-preserving distributed ledger construction protocol, coined as EPPDL, is proposed to safeguard digital asset transfer among users registered at different service providers. Concrete security analysis proves that the proposed EPPDL is secure against different types of adversaries, while comprehensive experiments verify its efficiency and effectiveness.
The rapid proliferation of electric vehicles (EVs) and the corresponding expansion of charging systems, driven by global regulatory mandates, present significant challenges to the electric grid. These systems also gen...
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The rapid deployment of IoT networks in different industrial services has caused the emanation of a huge volume of data from sensors and monitors. The efficient analysis and compact representation of the big data gene...
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Reducing resource waste while maintaining end-to-end latency service-level objective (SLO) by simultaneously managing CPU bandwidth, memory allocation, and pod number of web applications running on Java virtual machin...
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Reducing resource waste while maintaining end-to-end latency service-level objective (SLO) by simultaneously managing CPU bandwidth, memory allocation, and pod number of web applications running on Java virtual machine (JVM) is challenging. The challenges stem from the complexity of the multi-type resource allocation optimization problem, the high sensitivity of JVM performance to resource scaling actions, and the lack of low-level resource scaling mechanisms. We present GenesisRM, a resource management framework with a novel state-driven architecture. Specifically, we design a state control model for JVM web applications that encompasses seven pod states. This model serves as an abstraction layer, decoupling the centralized resource management system into a global state manager and distributed pod managers. The state manager controls the state transitions of the pods based on the overall workload, while the pod managers dynamically allocate resources for each pod according to the state and local workload. Then, we propose a multi-frequency control model with two predictive state controllers and a reactive state controller to manage the state of pods based on the state control model. In addition, GenesisRM brings new mechanisms to scale JVM pods' low-level resources without damaging their performance. We evaluate our work using a real-world JVM web application benchmark in three different scale server clusters of Pengcheng Laboratory Developer Cloud, and the 21- day experimental results show that GenesisRM saves 31.70% CPU and 17.60% memory compared to the best-performing state-of-the-art solutions while guaranteeing the SLO imposed on end-to-end latency.
The rapid deployment of IoT networks in different industrial services has caused the emanation of a huge volume of data from sensors and monitors. The efficient analysis and compact representation of the big data gene...
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Multi-branch neural networks are widely used in remote sensing intelligent interpretation because they can fuse multi-modal remote sensing data to improve interpretation accuracy. Meanwhile, in the current "big d...
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In recent years, the application domains of unmanned swarms have been continuously expanding. ing swarm navigation methods predominantly rely on communication networks for frequently information exchange to achieve st...
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In recent years, the application domains of unmanned swarms have been continuously expanding. ing swarm navigation methods predominantly rely on communication networks for frequently information exchange to achieve stable navigation behavior. However, this reliance presents challenges in achieving coordinated cooperative behavior in communication-restricted and obstacle-rich environments. To the task efficiency of swarms in such mission settings, we propose a distributed flocking framework guide unmanned aerial vehicle (UAV) swarms in navigating from a starting point to a target in unknown environments. Our approach begins by employing Boyd's OODA loop (Observe, Orient, Decide, Act), combined with a locally limited perception model, to develop an interactive decision-making process between individual UAVs and their external environment. We classify the roles of different UAV platforms within the swarm, enhancing cooperative flight efficiency through the guiding behavior of critical nodes. Each UAV utilizes dynamic adjustment mechanism for control parameters, allowing adaptive modifications based on local states. Additionally, each UAV is equipped with a model predictive control (MPC) controller, which provides feasible control inputs to ensure robust and reliable operation in complex and dynamic scenarios. To evaluate the adaptability of our method, we conducted simulations across various task environments with differing obstacle densities and numbers of UAVs. The results validate the algorithm's effectiveness and scalability, highlighting its robustness and potential applicability to real-world scenarios.
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