A backward wave oscillator with parallel multiple beams and multi-pin slow-wave structure(SWS)operating at the frequency above 500 GHz is studied. Both the cold-cavity dispersion characteristics and CST Particle Studi...
详细信息
A backward wave oscillator with parallel multiple beams and multi-pin slow-wave structure(SWS)operating at the frequency above 500 GHz is studied. Both the cold-cavity dispersion characteristics and CST Particle Studio simulation results reveal that there are obvious mode competition problems in this kind of terahertz *** that the structure of the multi-pin SWS is similar to that of two-dimensional photonic crystals, we introduce the defects of photonic crystal with the property of filtering into the SWS to suppress high-order ***, a detailed study of the effect of suppressing higher-order modes is carried out in the process of changing location and arrangement pattern of the point defects. The stable, single-mode operation of the terahertz source is realized. The simulation results show that the ratio of the output peak power of the higher-order modes to that of the fundamental mode is less than 1.9%. Also, the source can provide the output peak power of 44.8 m W at the frequency of 502.2 GHz in the case of low beam voltage of 4.7 kV.
Multi-hop reasoning for incomplete Knowledge Graphs(KGs)demonstrates excellent interpretability with decent *** Learning(RL)based approaches formulate multi-hop reasoning as a typical sequential decision *** intractab...
详细信息
Multi-hop reasoning for incomplete Knowledge Graphs(KGs)demonstrates excellent interpretability with decent *** Learning(RL)based approaches formulate multi-hop reasoning as a typical sequential decision *** intractable shortcoming of multi-hop reasoning with RL is that sparse reward signals make performance *** mainstream methods apply heuristic reward functions to counter this ***,the inaccurate rewards caused by heuristic functions guide the agent to improper inference paths and unrelated object *** this end,we propose a novel adaptive Inverse Reinforcement Learning(IRL)framework for multi-hop reasoning,called AInvR.(1)To counter the missing and spurious paths,we replace the heuristic rule rewards with an adaptive rule reward learning mechanism based on agent’s inference trajectories;(2)to alleviate the impact of over-rewarded object entities misled by inaccurate reward shaping and rules,we propose an adaptive negative hit reward learning mechanism based on agent’s sampling strategy;(3)to further explore diverse paths and mitigate the influence of missing facts,we design a reward dropout mechanism to randomly mask and perturb reward parameters for the reward learning *** results on several benchmark knowledge graphs demonstrate that our method is more effective than existing multi-hop approaches.
Real-world datasets often exhibit long-tailed distributions, compromising the generalization and fairness of learning-based models. This issue is particularly pronounced in Image Aesthetics Assessment (IAA) tasks, whe...
详细信息
Real-world datasets often exhibit long-tailed distributions, compromising the generalization and fairness of learning-based models. This issue is particularly pronounced in Image Aesthetics Assessment (IAA) tasks, where such imbalance is difficult to mitigate due to a severe distribution mismatch between features and labels, as well as the great sensitivity of aesthetics to image variations. To address these issues, we propose an Enhancer against Long-Tail for Aesthetics-oriented models (ELTA). ELTA first utilizes a dedicated mixup technique to enhance minority feature representation in high-level space while preserving their intrinsic aesthetic qualities. Next, it aligns features and labels through a similarity consistency approach, effectively alleviating the distribution mismatch. Finally, ELTA adopts a specific strategy to refine the output distribution, thereby enhancing the quality of pseudo-labels. Experiments on four representative datasets (AVA, AADB, TAD66K, and PARA) show that our proposed ELTA achieves state-of-the-art performance by effectively mitigating the long-tailed issue in IAA datasets. Moreover, ELTA is designed with plug-and-play capabilities for seamless integration with existing methods. To our knowledge, this is the first contribution in the IAA community addressing long-tail. All resources are available in here. Copyright 2024 by the author(s)
As an important task in emotion analysis, Multimodal Emotion-Cause Pair Extraction in conversations (MECPE) aims to extract all the emotion-cause utterance pairs from a conversation. However, there are two shortcoming...
详细信息
As an important task in emotion analysis, Multimodal Emotion-Cause Pair Extraction in conversations (MECPE) aims to extract all the emotion-cause utterance pairs from a conversation. However, there are two shortcomings in the MECPE task: 1) it ignores emotion utterances whose causes cannot be located in the conversation but require contextualized inference;2) it fails to locate the exact causes that occur in vision or audio modalities beyond text. To address these issues, in this paper, we introduce a new task named Multimodal Emotion-Cause Pair Generation in Conversations (MECPG), which aims to identify the emotion utterances with their emotion categories and generate their corresponding causes in a conversation. To tackle the MECPG task, we construct a dataset based on a benchmark corpus for MECPE. We further propose a generative framework named MONICA, which jointly performs emotion recognition and emotion cause generation with a sequence-to-sequence model. Experiments on our annotated dataset show the superiority of MONICA over several competitive systems. Our dataset and source codes will be publicly released. IEEE
Recent advances in wireless sensor networks (WSNs) have brought the sensor based monitoring developments to the surface in many applications. In such a scenario, the security of communication is a major challenge in t...
详细信息
With the continuous enhancement of informatization in production safety, the need to strengthen the analysis capability of big data in production safety is increasingly growing. This is crucial for preventing major ac...
详细信息
With the development of Industry 4.0 and big data technology,the Industrial Internet of Things(IIoT)is hampered by inherent issues such as privacy,security,and fault tolerance,which pose certain challenges to the rapi...
详细信息
With the development of Industry 4.0 and big data technology,the Industrial Internet of Things(IIoT)is hampered by inherent issues such as privacy,security,and fault tolerance,which pose certain challenges to the rapid development of *** technology has immutability,decentralization,and autonomy,which can greatly improve the inherent defects of the *** the traditional blockchain,data is stored in a Merkle *** data continues to grow,the scale of proofs used to validate it grows,threatening the efficiency,security,and reliability of blockchain-based ***,this paper first analyzes the inefficiency of the traditional blockchain structure in verifying the integrity and correctness of *** solve this problem,a new Vector Commitment(VC)structure,Partition Vector Commitment(PVC),is proposed by improving the traditional VC ***,this paper uses PVC instead of the Merkle tree to store big data generated by *** can improve the efficiency of traditional VC in the process of commitment and ***,this paper uses PVC to build a blockchain-based IIoT data security storage mechanism and carries out a comparative analysis of *** mechanism can greatly reduce communication loss and maximize the rational use of storage space,which is of great significance for maintaining the security and stability of blockchain-based IIoT.
This study focuses on enhancing Natural Language Processing (NLP) in generative AI chatbots through the utilization of advanced pre-trained models. We assessed five distinct Large Language Models (LLMs): TRANSFORMER M...
详细信息
Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ...
详细信息
Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ad hoc *** is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined *** fetches data from a fixed *** redundancy,mobility,and location dependency are the main issues of the IP network *** these factors result in poor performance of wireless ad hoc *** main disadvantage of IP is that,it does not provide in-network ***,there is a need to move towards a new network that overcomes these *** Data Network(NDN)is a network that overcomes these *** is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user *** NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and *** considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless *** cachingmechanism-based results are also *** the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.
In order to reduce the impact of public health emergencies on the normal life of residents, at the same time to prevent the secondary spread of diseases caused by improper methods in the management process. On the pre...
详细信息
暂无评论