Under the influence of the epidemic, online fitness exercise is becoming more and more popular. This is followed by higher requirements for the intelligence and personalization of sports and fitness. Therefore, this p...
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As users increasingly befriend others and interact online via their social media accounts,online social networks (OSNs)are expanding *** with the big data generated by users,it is imperative that data storage be distr...
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As users increasingly befriend others and interact online via their social media accounts,online social networks (OSNs)are expanding *** with the big data generated by users,it is imperative that data storage be distributed,scalable,and *** one of the most significant challenges about this topic is determining how to minimize the cost without deteriorating system *** many storage systems use the distributed key value store,it cannot be directly applied to OSN storage *** because users'data are highly correlated,hash storage leads to frequent inter-server communications,and the high inter-server traffic costs decrease the OSN storage system's scalability. Previous studies proposed conducting network partitioning and data replication based on social ***,data replication increases storage costs and impacts traffic ***,we consider how to minimize costs from the perspective of data storage,by combining partitioning and *** cost-efficient data storage approach supports scalable OSN storage *** proposed approach co-locates frequently interactive users together by conducting partitioning and replication simultaneously while meeting load-balancing *** experiments are undertaken on two real- world traces,and the results show that our approach achieves lower cost compared with state-of-the-art *** we conclude that our approach enables economic and scalable OSN data storage.
Research on biometrics for high security applica- tions has not attracted as much attention as civilian or foren- sic applications. Limited research and deficient analysis so far has led to a lack of general solutions...
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Research on biometrics for high security applica- tions has not attracted as much attention as civilian or foren- sic applications. Limited research and deficient analysis so far has led to a lack of general solutions and leaves this as a challenging issue. This work provides a systematic analy- sis and identification of the problems to be solved in order to meet the performance requirements for high security applica- tions, a double low problem. A hybrid ensemble framework is proposed to solve this problem. Setting an adequately high threshold for each matcher can guarantee a zero false accep- tance rate （FAR） and then use the hybrid ensemble framework makes the false reject rate （FRR） as low as possible. Three ex- periments are performed to verify the effectiveness and gener- alization of the framework. First, two fingerprint verification algorithms are fused. In this test only 10.55% of fingerprints are falsely rejected with zero false acceptance rate, this is sig- nificantly lower than other state of the art methods. Second, in face verification, the framework also results in a large re- duction in incorrect classification. Finally, assessing the per- formance of the framework on a combination of face and gait verification using a heterogeneous database show this frame- work can achieve both 0% false rejection and 0% false accep- tance simultaneously.
Remote sensing object detection faces unique challenges due to objects' varied scales and orientations. To address these challenges, we propose the Spatial Channel Attention Fusion Module (SCAF-Module), designed t...
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Based on an analog radio frequency(RF)network,hybrid precoding(HPC)for massive MIMO can achieve very high spectral efficiencies with moderate hardware cost and power *** the extensive research efforts in recent years,...
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Based on an analog radio frequency(RF)network,hybrid precoding(HPC)for massive MIMO can achieve very high spectral efficiencies with moderate hardware cost and power *** the extensive research efforts in recent years,the practioners are still looking for HPCs that are efficient and *** this paper,we present a new method termed as the universal hybrid precoding(UHP),which is nearly optimal,computationally efficient,and applicable to various types of RF network(thus,the name universal):the components of the network can be phase shifters(with finite or infinite resolutions),switches,or their combinations;the topology of the network can be fully-connected or *** the standard UHP,we also propose a simplified version termed as sUHP to trade a negligible performance loss for much reduced computational *** analysis shows that the computational complexity of the proposed UHP/sUHP is one to two orders of magnitude lower than the state-of-theart *** results verify the(near-)optimality of the proposed UHP scheme for various forms of the analog networks.
The emergence of 5G networks has enabled the deployment of a two-tier edge and vehicular-fog network. It comprises Multi-access Edge Computing (MEC) and Vehicular-Fogs (VFs), strategically positioned closer to Interne...
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In edge computing (EC) scenarios such as traffic flow prediction and social relationship recommendations, the emerging Graph Neural Networks (GNNs) is the promising deep learning model to tackle these applications. Ho...
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Farming is cultivating the soil,producing crops,and keeping *** agricultural sector plays a crucial role in a country’s economic *** research proposes a two-stage machine learning framework for agriculture to improve...
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Farming is cultivating the soil,producing crops,and keeping *** agricultural sector plays a crucial role in a country’s economic *** research proposes a two-stage machine learning framework for agriculture to improve efficiency and increase crop *** the first stage,machine learning algorithms generate data for extensive and far-flung agricultural areas and forecast *** recommended crops are based on various factors such as weather conditions,soil analysis,and the amount of fertilizers and pesticides *** the second stage,a transfer learningbased model for plant seedlings,pests,and plant leaf disease datasets is used to detect weeds,pesticides,and diseases in the *** proposed model achieved an average accuracy of 95%,97%,and 98% in plant seedlings,pests,and plant leaf disease detection,*** system can help farmers pinpoint the precise measures required at the right time to increase yields.
The application of the Internet of things (IOT) in industry and mining enterprises is analyzed in this paper. A new type of IOT application layer reader with functions of RFID and data transfer by wireless sensor is d...
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In this paper, an extended multi-dimensional N-coupled higher-order nonlinear Schr¨odinger equation (NCHNLSE), which can describe the propagation of the ultrashort pulses in wavelength division multiplexing (WDM)...
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In this paper, an extended multi-dimensional N-coupled higher-order nonlinear Schr¨odinger equation (NCHNLSE), which can describe the propagation of the ultrashort pulses in wavelength division multiplexing (WDM)systems, is investigated. By the bilinear method, we construct the breather solutions for the extended (1+1),(2+1) and(3+1)-dimensional N-CHNLSE. The rogue waves are derived as a limiting form of breathers with the aid of symbolic computation. The effect of group velocity dispersion (GVD), third-order dispersion (TOD) and nonlinearity on breathers and rogue waves solutions are discussed in the optical communication systems.
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