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  • Few-Shot Learning with Generative Adversarial Networks Based on WOA13 Data
  • Abstract In recent years, extreme weather events accompanying the global warming have occurred frequently, which brought significant impact on national economic and social development. The ocean is an important member of the climate system and plays an important role in the occurrence of climate anomalies. With continuous improvement of sensor technology, we use sensors to acquire the ocean data for the study on resource detection and disaster prevention, etc. However, the data acquired by the sensor is not enough to be used directly by researchers, so we use the Generative Adversarial Network (GAN) to enhance the ocean data. We use GAN…
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  • Attention-Aware Network with Latent Semantic Analysis for Clothing Invariant Gait Recognition
  • Abstract Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes and capturing the relationships from…
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  • Non-Contact Real-Time Heart Rate Measurement Algorithm Based on PPG-Standard Deviation
  • Abstract Heart rate is an important physiological parameter for clinical diagnosis, it can infer the health of the human body. Thus, efficient and accurate heart rate measurement is important for disease diagnosis and health monitoring. There are two ways to measure heart rate. One is contact type and the other is non-contact. Contact measurement methods include pulse cutting, electrocardiogram, etc. Because of the inconvenience of this method, a non-contact heart rate method has been proposed. Traditional non-contact measurement method based on image is collecting RGB three-channel signals in continuous video and selecting the average value of the green channel pixels as…
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  • Research on Public Opinion Propagation Model in Social Network Based on Blockchain
  • Abstract With the emergence and development of blockchain technology, a new type of social networks based on blockchain had emerged. In these social networks high quality content creators, filters and propagators can all be reasonably motivated. Due to the transparency and traceability brought by blockchain technology, the public opinion propagation in such social networks presents new characteristics and laws. Based on the theory of network propagation and blockchain, a new public opinion propagation model for this kind of social network based on blockchain technology is proposed in this paper. The model considers the effect of incentive mechanism produced by reasonably quantifying…
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  •   Views:1222       Downloads:805        Download PDF
  • A Recommendation System Based on Fusing Boosting Model and DNN Model
  • Abstract In recent years, the models combining traditional machine learning with the deep learning are applied in many commodity recommendation practices. It has been proved better performance by the means of the neural network. Feature engineering has been the key to the success of many click rate estimation model. As we know, neural networks are able to extract high-order features automatically, and traditional linear models are able to extract low-order features. However, they are not necessarily efficient in learning all types of features. In traditional machine learning, gradient boosting decision tree is a typical representative of the tree model, which can…
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  •   Views:1054       Downloads:780        Download PDF
  • Research on Sensor Network Coverage Enhancement Based on Non-Cooperative Games
  • Abstract Coverage is an important issue for resources rational allocation, cognitive tasks completion in sensor networks. The mobility, communicability and learning ability of smart sensors have received much attention in the past decade. Based on the deep study of game theory, a mobile sensor non-cooperative game model is established for the sensor network deployment and a local information-based topology control (LITC) algorithm for coverage enhancement is proposed. We both consider revenue of the monitoring events and neighboring sensors to avoid nodes aggregation when formulating the utility function. We then prove that the non-cooperative game is an exact potential game in which…
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  • GaiaWorld: A Novel Blockchain System Based on Competitive PoS Consensus Mechanism
  • Abstract The birth of blockchain has promoted the development of electronic currencies such as Bitcoin and Ethereum. Blockchain builds a financial system based on cryptology instead of credit, which allows parties to complete the transaction on their own without the need for credible third-party intermediaries. So far, the application scenario of blockchain is mainly confined to the peer-to-peer electronic financial system, which obviously does not fully utilize the potential of blockchain.
    In this paper, we introduce GaiaWorld, a new system for decentralized application. To solve the problem of resource waste and mismatch between nodes and computing power in traditional PoW…
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  • An Efficient Greedy Traffic Aware Routing Scheme for Internet of Vehicles
  • Abstract A new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all connected vehicles to communicate with…
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  • High Precision SAR ADC Using CNTFET for Internet of Things
  • Abstract A high precision 10-bit successive approximation register analog to digital converter (ADC) designed and implemented in 32nm CNTFET process technology at the supply of 0.6V, with 73.24 dB SNDR at a sampling rate of 640 MS/s with the average power consumption of 120.2 μW for the Internet of things node. The key components in CNTFET SAR ADCs are binary scaled charge redistribution digital to analog converter using MOS capacitors, CNTFET based dynamic latch comparator and simple SAR digital code error correction logic. These techniques are used to increase the sampling rate and precision while ensuring the linearity, power consumption and…
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  •   Views:942       Downloads:1053        Download PDF
  • Failure Prediction, Lead Time Estimation and Health Degree Assessment for Hard Disk Drives Using Voting Based Decision Trees
  • Abstract Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the gradual change/deterioration of HDDs; they…
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  •   Views:1671       Downloads:1177        Download PDF
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