Thanks to its ubiquity,using radio frequency (RF) signals for sensing has found widespread *** traditional integrated sensing and communication systems,such as joint radar-communication systems,common sensing tasks in...
Thanks to its ubiquity,using radio frequency (RF) signals for sensing has found widespread *** traditional integrated sensing and communication systems,such as joint radar-communication systems,common sensing tasks include target localization and ***,increasingly intelligent systems,such as smart agriculture,lowaltitude economy,and smart healthcare,have demanded more comprehensive and continuous information sensing capabilities to support higher-level *** sensing has the potential to offer both spatial and temporal continuity,meeting the multi-dimensional sensing needs of these intelligent ***,numerous advanced systems have been proposed,expanding the application scope of RF sensing to be more pervasive,including discrete state ubiquitous sensing tasks (such as material identification [1]),and continuous state ubiquitous sensing tasks (such as health monitoring [2]).With the advent of the 6G era,it is anticipated that the sensing potential of RF systems will be further unleashed.
Dialogue-based relation extraction(DialogRE) aims to predict relationships between two entities in dialogue. Current approaches to dialogue relationship extraction grapple with long-distance entity relationships in di...
详细信息
Dialogue-based relation extraction(DialogRE) aims to predict relationships between two entities in dialogue. Current approaches to dialogue relationship extraction grapple with long-distance entity relationships in dialogue data as well as complex entity relationships, such as a single entity with multiple types of connections. To address these issues, this paper presents a novel approach for dialogue relationship extraction termed the hypergraphs and heterogeneous graphs model(HG2G). This model introduces a two-tiered structure, comprising dialogue hypergraphs and dialogue heterogeneous graphs, to address the shortcomings of existing methods. The dialogue hypergraph establishes connections between similar nodes using hyper-edges and utilizes hypergraph convolution to capture multi-level features. Simultaneously, the dialogue heterogeneous graph connects nodes and edges of different types, employing heterogeneous graph convolution to aggregate cross-sentence information. Ultimately, the integrated nodes from both graphs capture the semantic nuances inherent in dialogue. Experimental results on the DialogRE dataset demonstrate that the HG2G model outperforms existing state-of-the-art methods.
The pixel-wise dense prediction tasks based on weakly supervisions currently use Class Attention Maps(CAMs)to generate pseudo masks as ***,existing methods often incorporate trainable modules to expand the immature cl...
详细信息
The pixel-wise dense prediction tasks based on weakly supervisions currently use Class Attention Maps(CAMs)to generate pseudo masks as ***,existing methods often incorporate trainable modules to expand the immature class activation maps,which can result in significant computational overhead and complicate the training *** this work,we investigate the semantic structure information concealed within the CNN network,and propose a semantic structure aware inference(SSA)method that utilizes this information to obtain high-quality CAM without any additional training ***,the semantic structure modeling module(SSM)is first proposed to generate the classagnostic semantic correlation representation,where each item denotes the affinity degree between one category of objects and all the ***,the immature CAM are refined through a dot product operation that utilizes semantic structure ***,the polished CAMs from different backbone stages are fused as the *** advantage of SSA lies in its parameter-free nature and the absence of additional training costs,which makes it suitable for various weakly supervised pixel-dense prediction *** conducted extensive experiments on weakly supervised object localization and weakly supervised semantic segmentation,and the results confirm the effectiveness of SSA.
Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum...
详细信息
Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum communication, and utilize the logical relationship between the measurements of each node to derive the unitary operation performed by the end node. The hierarchical simultaneous entanglement switching(HSES) method is adopted, resulting in a significant reduction in the consumption of classical information compared to multi-hop quantum teleportation(QT)based on general simultaneous entanglement switching(SES). In addition, the proposed protocol is simulated on the IBM Quantum Experiment platform(IBM QE). Then, the data obtained from the experiment are analyzed using quantum state tomography, which verifies the protocol's good fidelity and accuracy. Finally, by calculating fidelity, we analyze the impact of four different types of noise(phase-damping, amplitude-damping, phase-flip and bit-flip) in this protocol.
Software-defined networking decouples the control plane from the data plane to enable centralized flow-level network management, while requiring periodically collecting traffic statistics from the data plane to enforc...
详细信息
Software-defined networking decouples the control plane from the data plane to enable centralized flow-level network management, while requiring periodically collecting traffic statistics from the data plane to enforce optimal management. As one of the most important traffic measurement tasks, heavy flow detection has received wide attention for its providing fundamental statistics in various practical applications. Existing studies have proposed sketch-based detection solutions to address the mismatch problem between massive traffic and limited high-speed memory resources for measurement in the data plane. However,they overlook the potential of integrating the flow table, where each entry simultaneously enforces forwarding rules for specific flows and records flow statistics into the sketch design, leading to redundant measurement between the flow table and sketch and being unable to utilize their statistics to jointly enhance estimation accuracy. We propose flow entries assisted sketch(FEA-Sketch) in this work, which employs a differentiated flow recording strategy to record flow statistics jointly using the flow table and sketch for memory-efficient and computationally efficient heavy flow detection. We also propose an optimization-based estimation algorithm to accurately recover per-flow sizes for the flows that only have aggregated statistics due to the sharing of entries in the table(or counters in the sketch). We extend the FEA-Sketch to the distributed measurement setting with a hop-based collaborative measurement strategy, which reduces the measurement workload on switches across the network by avoiding redundant measurements. The experimental results on real Internet traces show that the accuracy of heavy flow detection is improved up to 1.95 times, and the bias of flow size estimation is improved up to 2.99 times, demonstrating that integrating flow entries can significantly improve the performance of heavy flow detection.
At present,most quantum secret sharing(QSS)protocols are more or less designed with the incorporation of classical secret sharing *** the increasing maturity of quantum technology,QSS protocols based on pure quantum m...
详细信息
At present,most quantum secret sharing(QSS)protocols are more or less designed with the incorporation of classical secret sharing *** the increasing maturity of quantum technology,QSS protocols based on pure quantum mechanics are becoming more *** secret sharing schemes cannot achieve absolute security,and their involvement can compromise the security of QSS *** paper proposes a QSS scheme based on Greenberger-Horn-Zeilinger(GHZ)basis measurement and quantum entanglement *** this protocol,the secret sender stores the secret information using Pauli *** obtain their shares by measuring the product state ***,participants complete the secret reconstruction through quantum entanglement exchange and other related quantum *** addition,the particles held by participants in the protocol do not contain any secret *** participant's particles are in a state of maximum entanglement,and no participant can deduce the particle information of other participants through their own *** the same time,the protocol is based on pure quantum mechanics and does not involve classical schemes,which avoids the problem of reduced security of the *** analysis indicates that the protocol is not vulnerable to retransmission interception and collusion ***,it is capable of detecting and terminating the protocol promptly when facing with attacks from dishonest participants.
We study a novel replication mechanism to ensure service continuity against multiple simultaneous server failures. In this mechanism, each item represents a computing task and is replicated into ξ + 1 servers for som...
详细信息
We study a novel replication mechanism to ensure service continuity against multiple simultaneous server failures. In this mechanism, each item represents a computing task and is replicated into ξ + 1 servers for some integer ξ ≥ 1, with workloads specified by the amount of required resources. If one or more servers fail, the affected workloads can be redirected to other servers that host replicas associated with the same item, such that the service is not interrupted by the failure of up to ξ servers. This requires that any feasible assignment algorithm must reserve some capacity in each server to accommodate the workload redirected from potential failed servers without overloading, and determining the optimal method for reserving capacity becomes a key issue. Unlike existing algorithms that assume that no two servers share replicas of more than one item, we first formulate capacity reservation for a general arbitrary scenario. Due to the combinatorial nature of this problem, finding the optimal solution is difficult. To this end, we propose a Generalized and Simple Calculating Reserved Capacity(GSCRC) algorithm, with a time complexity only related to the number of items packed in the server. In conjunction with GSCRC, we propose a robust replica packing algorithm with capacity optimization(RobustPack), which aims to minimize the number of servers hosting replicas and tolerate multiple server failures. Through theoretical analysis and experimental evaluations, we show that the RobustPack algorithm can achieve better performance.
Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inher...
详细信息
Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inherent biases and computational burdens, especially when used to relax the rank function, making them less effective and efficient in real-world scenarios. To address these challenges, our research focuses on generalized nonconvex rank regularization problems in robust matrix completion, low-rank representation, and robust matrix regression. We introduce innovative approaches for effective and efficient low-rank matrix learning, grounded in generalized nonconvex rank relaxations inspired by various substitutes for the ?0-norm relaxed functions. These relaxations allow us to more accurately capture low-rank structures. Our optimization strategy employs a nonconvex and multi-variable alternating direction method of multipliers, backed by rigorous theoretical analysis for complexity and *** algorithm iteratively updates blocks of variables, ensuring efficient convergence. Additionally, we incorporate the randomized singular value decomposition technique and/or other acceleration strategies to enhance the computational efficiency of our approach, particularly for large-scale constrained minimization problems. In conclusion, our experimental results across a variety of image vision-related application tasks unequivocally demonstrate the superiority of our proposed methodologies in terms of both efficacy and efficiency when compared to most other related learning methods.
Spatial relations in text refer to how a geographical entity is located in space in relation to a reference *** spatial relations from text is a fundamental task in natural language *** studies have only focused on ge...
详细信息
Spatial relations in text refer to how a geographical entity is located in space in relation to a reference *** spatial relations from text is a fundamental task in natural language *** studies have only focused on generic fine-tuning methods with additional classifiers,ignoring the importance of the semantic correlation between different spatial elements and the large offset between the relation extraction task and the pre-trained *** address the above two issues,we propose a spatial relation extraction model based on Dual-view Prompt and Element Correlation(DPEC).Specifically,we first reformulate spatial relation extraction as a mask language model with a Dual-view Prompt(i.e.,Link Prompt and Confidence Prompt).Link Prompt can not only guide the model to incorporate more contextual information related to the spatial relation extraction task,but also better adapt to the original pre-training task of the language ***,Confidence Prompt can measure the confidence of candidate triplets in Link Prompt and work as a supplement to identify those easily confused examples in Link ***,we incorporate the element correlation to measure the consistency between different spatial elements,which is an effective cue for identifying the rationality of spatial *** results on the popular SpaceEval show that our DPEC significantly outperforms the SOTA baselines.
Multiarmed bandit(MAB) models are widely used for sequential decision-making in uncertain environments, such as resource allocation in computer communication systems.A critical challenge in interactive multiagent syst...
Multiarmed bandit(MAB) models are widely used for sequential decision-making in uncertain environments, such as resource allocation in computer communication systems.A critical challenge in interactive multiagent systems with bandit feedback is to explore and understand the equilibrium state to ensure stable and tractable system performance.
暂无评论