Multi-island single electron transistor (MISET) is a kind of single electron transistor (SET), which has advantages of the room temperature operating. A novel semi-empirical compact model for MISET is proposed. The ne...
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Multi-island single electron transistor (MISET) is a kind of single electron transistor (SET), which has advantages of the room temperature operating. A novel semi-empirical compact model for MISET is proposed. The new approach combines the orthodox theory of single electron tunneling for single Coulomb island and a novel empirical analysis for a chain of Coulomb islands. The model is verified by the Monte-Carlo method in SIMON simulator, and is much faster than the traditional multi-island SET simulator, which has the advantages for the large scale multi-island SET circuit simulation.
The aim of multi-agent reinforcement learning systems is to provide interacting agents with the ability to collaboratively learn and adapt to the behavior of other agents. In many real-world applications, the agents c...
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Retrieval-augmented generation (RAG) has shown promising potential in knowledge intensive question answering (QA). However, existing approaches only consider the query itself, neither specifying the retrieval preferen...
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Document-level event extraction task has achieved significant progress based on template generation methods. However, there is no reasonable regulation and restriction in the existing template-based generation methods...
Document-level event extraction task has achieved significant progress based on template generation methods. However, there is no reasonable regulation and restriction in the existing template-based generation methods, which results in the uncontrollability of the generation results. In some scenarios, model generates entities that do not belong to the input text, or generate template content repeatedly. It is determined by the nature of the extraction task and the generation task. To this end, we propose a controllable template generation event extraction model. According to the characteristics of template generation and event extraction tasks, the model devises copy mechanism, inhibition mechanism and rejection mechanism under the appropriately constructed template. Our model achieves state-of-the-art result on MUC-4 dataset, and finally through experimental analysis, it demonstrates the effectiveness of each mechanism we proposed.
With the rapid development of Internet technology, various network attack methods come out one after the other. SQL injection has become one of the most severe threats to Web applications and seriously threatens vario...
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With the rapid development of Internet technology, various network attack methods come out one after the other. SQL injection has become one of the most severe threats to Web applications and seriously threatens various Web application services and users' data security. There are both traditional detection methods and emerging methods based on deep learning technology with higher detection accuracy for the detection of SQL injection. However, they are all for detecting a single statement and cannot determine the stage of the attack. To further improve the effect of SQL injection detection, this paper proposes an integrated detection framework for SQL injection behavior based on both text features and traffic features. We propose a SQL-LSTM model based on deep learning technology as the detection model at the text features level. Meanwhile,the features of the data traffic are merged. By this integrated method, the detection effect of SQL injection is further improved.
The increasing algorithm complexity and dataset sizes necessitate the use of networked machines for many graph-parallel algorithms, which also makes fault tolerance a must due to the increasing scale of machines. Unfo...
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The increasing algorithm complexity and dataset sizes necessitate the use of networked machines for many graph-parallel algorithms, which also makes fault tolerance a must due to the increasing scale of machines. Unfortunately, existing large-scale graph-parallel systems usually adopt a distributed checkpoint mechanism for fault tolerance, which incurs not only notable performance overhead but also lengthy recovery time. This paper observes that the vertex replicas created for distributed graph computation can be naturally extended for fast in-memory recovery of graph states. This paper proposes Imitator, a new fault tolerance mechanism, that supports cheaply maintenance of vertex states by replicating vertex states to their replicas during normal message exchanges, and provides fast in-memory reconstruction of failed vertices from replicas in other machines. Imitator has been implemented by extending Hama, a popular open-source clone of Pregel. Evaluation shows that Imitator incurs negligible performance overhead (less than 5% for all cases) and can recover from failures of more than one million of vertices with less than 3.4 seconds.
Large-scale floating-point matrix multiplication is a fundamental kernel in many scientific and engineering applications. Most existing work only focus on accelerating matrix multiplication on FPGA by adopting a linea...
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Encryption technology has become an important mechanism of securing data stored in the outsourced database. However, it is a difficulty to query efficiently the encrypted data and many researchers take it into conside...
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ISBN:
(纸本)9781424477050
Encryption technology has become an important mechanism of securing data stored in the outsourced database. However, it is a difficulty to query efficiently the encrypted data and many researchers take it into consideration. To solve the problem, an encrypted schema, based on the Postgresql DBMS, is proposed. Through the security dictionary and the extended SQL, the approach implements the encrypted storage and efficiently query over the encrypted data in the outsourced databases. Results of experiments validate the efficiency and feasibility of our approach.
Mobile robot object recognition has attracted significant attention in the internet of things recently, in which there are many challenging tasks, such as the objects, the communication networks and the computer syste...
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ISBN:
(数字)9781728132488
ISBN:
(纸本)9781728132495
Mobile robot object recognition has attracted significant attention in the internet of things recently, in which there are many challenging tasks, such as the objects, the communication networks and the computer system. It still needs a large of computation, communication and storage capability for the whole system. In this paper, we propose a scheme of mobile robot object recognition in IOT and use edge nodes to process the data from robot vision instead of cloud computing. Besides, we adopt YOLOv3 as the main algorithm in the edge nodes to process the video data. The video from the camera on the robot is transmitted to the fog node by a Wi-Fi router. The advantages of using edge nodes for computation local robot clusters are reliability, real-time capability and flexibility compared with the cloud. In our experiment, we efficiently train the computer model using COCO database deployed to GPU. The robot using the proposed model could recognize the objects in real-time. We achieve mAP of 31.0% and response time of 52ms that illustrates the state-of-art performance of the proposed framework.
Memory-intensive applications often suffer from the poor performance of disk swapping when memory is inadequate. Remote memory sharing schemes, which provide a remote memory that is faster than the local hard disk, ar...
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ISBN:
(纸本)9781424400546
Memory-intensive applications often suffer from the poor performance of disk swapping when memory is inadequate. Remote memory sharing schemes, which provide a remote memory that is faster than the local hard disk, are able to improve the performance of such applications. Due to the limitation of being applicable within single clusters only, however, most of the previous remote memory mechanisms, such as the network memory scheme, fail to be extendable into a large scale, distributed, heterogeneous, and dynamic environment. In this work, we propose a service-oriented grid memory sharing scheme, distributed paging RAM grid (DPRG). We study the properties and criteria of large scale memory sharing, and then design major operations and optimizations to fit the usage of grid systems. We collect trace from our grid environment, and evaluate DPRG through comprehensive trace-driven simulations. Results show that DPRG significantly outperforms existing remote memory sharing schemes and supports grid computing applications effectively
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