This paper presents an analysis of the harmonic influence of an electric vehicle charging station (EVCS) on the harmonic distortion of the voltage in a low-voltage (LV) distribution network. The analysis was performed...
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The use of technology in supporting the education sector can improve the quality of education and human resources. The dissemination of learning content and the use of video conferencing technology in the distance lea...
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How to properly align the extracted visual features with certain semantic embeddings of unseen objects is crucial to the problem of Zero-Shot Object Detection (ZSD). To give a better guess of those unseen visual featu...
How to properly align the extracted visual features with certain semantic embeddings of unseen objects is crucial to the problem of Zero-Shot Object Detection (ZSD). To give a better guess of those unseen visual features, a partitioned contrast strategy is proposed in this paper to train the visual and attribute feature alignment networks. To be specific, four types of contrast are considered, including the visual-to-visual, visual-to-attribute, attribute-to-visual and attribute-to-attribute contrasts. Combining with two cross-batch memory banks of the visual features and unseen attribute features, it is effective to adjust the alignment rules for unseen visual features. Experimental results on the MS-COCO dataset show the superiority of the proposed model. Our code is available at: https://***/lihh1023/PCFA-ZSD.
When considering motion planning for a swarm of n labeled robots, we need to rearrange a given start configuration into a desired target configuration via a sequence of parallel, continuous, collision-free robot motio...
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Light field (LF) cameras usually capture dense angular samples, but suffer from low spatial resolution. Existing single-LF super-resolution methods struggle with textures at larger scales (e.g., 8×). To address t...
Light field (LF) cameras usually capture dense angular samples, but suffer from low spatial resolution. Existing single-LF super-resolution methods struggle with textures at larger scales (e.g., 8×). To address this issue, this paper proposes a novel hybrid domain learning-based method to enhance LF spatial resolution from heterogeneous imaging (integrating an LF camera and a 2D digital camera). The proposed method consists of two core modules, namely LF feature alignment module and cross-domain multi-scale fusion module. The former combines optical flow and deformable convolution to gradually align the 2D high-resolution features with the low-resolution LF features. The latter progressively fuses the aligned multi-resolution LF features to enable high-quality reconstruction. Experimental results show the proposed method recovers fine textures and preserves accurate angular consistency, and outperforms the state-of-the-art methods in both quantitative and qualitative comparisons.
We demonstrate the significant i nfluence of th e il lumination co herence on diffractive networks, and propose a framework for network optimization with any prescribed degree of spatial and temporal coherence. We ana...
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Integrated high-linearity modulators are crucial for high dynamic-range microwave photonic(MWP)*** linearization schemes usually involve the fine tuning of radio-frequency(RF)power distribution,which is rather inconve...
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Integrated high-linearity modulators are crucial for high dynamic-range microwave photonic(MWP)*** linearization schemes usually involve the fine tuning of radio-frequency(RF)power distribution,which is rather inconvenient for practical applications and can hardly be implemented on the integrated photonics *** this paper,we propose an elegant scheme to linearize a silicon-based modulator in which the active tuning of RF power is *** device consists of two carrier-depletion-based Mach-Zehnder modulators(MZMs),which are connected in series by a 1×2 thermal optical switch(OS).The OS is used to adjust the ratio between the modulation depths of the two *** a proper ratio,the complementary third-order intermodulation distortion(IMD3)of the two sub-MZMs can effectively cancel each other *** measured spurious-free dynamic ranges for IMD3 are 131,127,118,110,and 109 d B·Hz^(6∕7)at frequencies of 1,10,20,30,and 40 GHz,respectively,which represent the highest linearities ever reached by the integrated modulator chips on all available material platforms.
The emergence of multimedia services has meant a substantial increase in the number of devices in mobile networks and driving the demand for higher data transmission *** result is that,cellular networks must technical...
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The emergence of multimedia services has meant a substantial increase in the number of devices in mobile networks and driving the demand for higher data transmission *** result is that,cellular networks must technically evolve to support such higher rates,to be equipped with greater capacity,and to increase the spectral and energy *** with 4G technology,the 5G networks are being designed to transmit up to 100 times more data volume with devices whose battery life is 10 times ***,this new generation of networks has adopted a heterogeneous and ultra-dense architecture,where different technological advances are combined such as device-to-device(D2D)communication,which is one of the key elements of 5G *** has immediate applications such as the distribution of traffic load(data offloading),communications for emergency services,and the extension of cellular coverage,*** this communication model,two devices can communicate directly if they are close to each other without using a base station or a remote access ***,eliminating the interference between theD2Dand cellular communication in the *** interference management has become a hot issue in current *** order to address this problem,this paper proposes a joint resource allocation algorithm based on the idea of mode selection and resource *** results showthat the proposed algorithm effectively improves the systemperformance and reduces the interference as compared with existing algorithms.
In this paper, battery charge and discharge simulation are shown for one battery energy storage system. For this purpose, the two-stage bidirectional power converter is used to achieve power conversion from battery st...
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At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhance...
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At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system ***,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative *** addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the SPSS tool,and respective graphical illustrations were *** results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten *** in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved *** EDLA algorithm introduces novelty concerning its performance and particular activation *** proposed method will be utilized effectively in brain tumor detection in a precise and accurate *** algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses *** the quantity of dataset records is enormous,then themethod’s computation power has to be updated.
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