RF sensing has attracted a tremendous amount of attention and achieved promising progress in applications such as human gesture recognition and vital sign monitoring. This paper delves into sensing the moisture level ...
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This research investigates the perceptions of cybersecurity among older adults in Malaysia, aged 60 years and above, who are reliant on technology for basic activities. The data from 331 participants showed that 30.8%...
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Recently, many multi-view clustering (MVC) methods have achieved promising results through integrating complementary and consensus information from different views in the fields of signal processing and machine learni...
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Recently, many multi-view clustering (MVC) methods have achieved promising results through integrating complementary and consensus information from different views in the fields of signal processing and machine learning. However, most of the methods require complete or partial correspondence of multi-view instances which is hard to satisfy in many practical applications. To this end, this letter proposes a novel method termed Distribution-Level Multi-view Clustering for Unaligned Data (DLCU), which proves to be well-suited for scenarios where instance correspondences between different modalities are entirely absent. Specifically, in order to reconstruct cross-view correspondence, the wasserstein distance is employed to effectuate the alignment of multi-view data in distribution-level and guide the learning of cross-view transformation. Furthermore, the negative impact of the inevitable misalignment is mitigated through the global attention mechanism, which is designed to assign appropriate weights to realigned instances across multiple views. Besides, a divergence-based clustering objective is explored to encourage a clear cluster structure and conduct the training of latent representation. Experimental results on several real-world datasets show our promising performance comparing with the state-of-the-art methods.
Spatial audio quality evaluation is essential for applications like virtual and augmented reality, where accurate sound reproduction enhances user immersion. While subjective listening tests are the gold standard, the...
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Geometric representation of query embeddings (using points, particles, rectangles and cones) can effectively achieve the task of answering complex logical queries expressed in first-order logic (FOL) form over knowled...
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In recent years, more and more end-to-end deep learning methods have been applied to remote sensing image classification. Convolutional neural networks (CNN) is the most representative one. However, the convolution ke...
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Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)...
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Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be defined by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.
Since smartphones embedded with positioning systems and digital maps are widely used,location-based services(LBSs)are rapidly growing in popularity and providing unprecedented convenience in people’s daily lives;howe...
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Since smartphones embedded with positioning systems and digital maps are widely used,location-based services(LBSs)are rapidly growing in popularity and providing unprecedented convenience in people’s daily lives;however,they also cause great concern about privacy *** particular,location queries can be used to infer users’sensitive private information,such as home addresses,places of work and appointment ***,many schemes providing query anonymity have been proposed,but they typically ignore the fact that an adversary can infer real locations from the correlations between consecutive locations in a continuous *** address this challenge,a novel dual privacy-preserving scheme(DPPS)is proposed that includes two privacy protection ***,to prevent privacy disclosure caused by correlations between locations,a correlation model is proposed based on a hidden Markov model(HMM)to simulate users’mobility and the adversary’s prediction ***,to provide query probability anonymity of each single location,an advanced k-anonymity algorithm is proposed to construct cloaking regions,in which realistic and indistinguishable dummy locations are *** validate the effectiveness and efficiency of DPPS,theoretical analysis and experimental verification are further performed on a real-life dataset published by Microsoft,i.e.,GeoLife dataset.
作者：
Shi, LiangheLiu, WeiweiSchool of Computer Science
Wuhan University National Engineering Research Center for Multimedia Software Wuhan University Institute of Artificial Intelligence Wuhan University Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University
Gradual Domain Adaptation (GDA), in which the learner is provided with additional intermediate domains, has been theoretically and empirically studied in many contexts. Despite its vital role in security-critical scen...
To meet the customized requirements of customers is the core orientation to achieve the transition from production-centered manufacturing to service-centered manufacturing. As an important part of smart manufacturing ...
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To meet the customized requirements of customers is the core orientation to achieve the transition from production-centered manufacturing to service-centered manufacturing. As an important part of smart manufacturing systems in the production and operation level dominated by material flow, flexible manufacturing systems (FMS) have to make several transitions such as incorporating several manufacturing procedures, containing several manufacturing products, and meeting several manufacturing requirements. As the existing research on FMS mainly focuses on fixed manufacturing techniques and production procedures, it is imperative to propose an effective modeling and control approach. In this paper, inspired by the idea of colored Petri nets, based on the manufacturing information of workpieces in the system, we propose a customized supervisory control approach for FMS. Finally, the validity of our approach is illustrated by an FMS satisfying customized requirements. The proposed approach makes control decisions by dynamically updating the token information of the current state of the supervisor, and also by combining the information of the binding queue and the customized information of workpieces, which does not increase the scale of the supervisor.
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