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  • Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity
  • Abstract The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel disease and b) resource limitations…
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  • Self-Certificating Root: A Root Zone Security Enhancement Mechanism for DNS
  • Abstract As a critical Internet infrastructure, domain name system (DNS) protects the authenticity and integrity of domain resource records with the introduction of security extensions (DNSSEC). DNSSEC builds a single-center and hierarchical resource authentication architecture, which brings management convenience but places the DNS at risk from a single point of failure. When the root key suffers a leak or misconfiguration, top level domain (TLD) authority cannot independently protect the authenticity of TLD data in the root zone. In this paper, we propose self-certificating root, a lightweight security enhancement mechanism of root zone compatible with DNS/DNSSEC protocol. By adding the TLD public…
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  • A Fast Filling Algorithm for Image Restoration Based on Contour Parity
  • Abstract Filling techniques are often used in the restoration of images. Yet the existing filling technique approaches either have high computational costs or present problems such as filling holes redundantly. This paper proposes a novel algorithm for filling holes and regions of the images. The proposed algorithm combines the advantages of both the parity-check filling approach and the region-growing inpainting technique. Pairing points of the region’s boundary are used to search and to fill the region. The scanning range of the filling method is within the target regions. The proposed method does not require additional working memory or assistant colors, and…
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  • Recommender System Combining Popularity and Novelty Based on One-Mode Projection of Weighted Bipartite Network
  • Abstract Personalized recommendation algorithms, which are effective means to solve information overload, are popular topics in current research. In this paper, a recommender system combining popularity and novelty (RSCPN) based on one-mode projection of weighted bipartite network is proposed. The edge between a user and item is weighted with the item’s rating, and we consider the difference in the ratings of different users for an item to obtain a reasonable method of measuring the similarity between users. RSCPN can be used in the same model for popularity and novelty recommendation by setting different parameter values and analyzing how a change in…
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  • Sliding-Mode PID Control of UAV Based on Particle Swarm Parameter Tuning
  • Abstract Due to the coupled motion between the rotor unmanned aerial vehicle (UAV) and the manipulator, the underactuation characteristics of the system itself, and the influence of external uncertainties, the stability of the rotor UAV’s manipulator control system is difficult to control. Based on the dynamic model of the rotor UAV, the stability of the whole UAV manipulator control system is improved by using the piecewise cost function, the compression factor particle swarm optimization (PSO) algorithm and the sliding mode PID to establish the sliding mode PID control stability method based on the PSO. Compared with the sliding mode PID control…
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  • Method to Appraise Dangerous Class of Building Masonry Component Based on DC-YOLO Model
  • Abstract This DC-YOLO Model was designed in order to improve the efficiency for appraising dangerous class of buildings and avoid manual intervention, thereby making the appraisal results more objective. It is an automated method designed based on deep learning and target detection algorithms to appraise the dangerous class of building masonry component. Specifically, it (1) adopted K-means clustering to obtain the quantity and size of the prior boxes; (2) expanded the grid size to improve identification to small targets; (3) introduced in deformable convolution to adapt to the irregular shape of the masonry component cracks. The experimental results show that, comparing…
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  • Detection of Number of Wideband Signals Based on Support Vector Machine
  • Abstract In array signal processing, number of signals is often a premise of estimating other parameters. For the sake of determining signal number in the condition of strong additive noise or a little sample data, an algorithm for detecting number of wideband signals is provided. First, technique of focusing is used for transforming signals into a same focusing subspace. Then the support vector machine (SVM) can be deduced by the information of eigenvalues and corresponding eigenvectors. At last, the signal number can be determined with the obtained decision function. Several simulations have been carried on verifying the proposed algorithm.
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  • Intent Inference Based Trajectory Prediction and Smooth for UAS in Low-Altitude Airspace with Geofence
  • Abstract In order to meet the higher accuracy requirement of trajectory prediction for Unmanned Aircraft System (UAS) in Unmanned Aircraft System Traffic Management (UTM), an Intent Based Trajectory Prediction and Smooth Based on Constrained State-dependent-transition Hybrid Estimation (CSDTHE-IBTPS) algorithm is proposed. Firstly, an intent inference method of UAS is constructed based on the information of ADS-B and geofence system. Moreover, a geofence layering algorithm is proposed. Secondly, the Flight Mode Change Points (FMCP) are used to define the relevant mode transition parameters and design the guard conditions, so as to generate the mode transition probability matrix and establish the continuous state-dependent-transition…
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  • Analysis of Underlay Cognitive Radio Networks Based on Interference Cancellation Mechanism
  • Abstract In this paper, we investigate the performance of secondary transmission scheme based on Markov ON-OFF state of primary users in Underlay cognitive radio networks. We propose flexible secondary cooperative transmission schemewith interference cancellation technique according to the ON-OFF status of primary transmitter. For maximal ratio combining (MRC) at destination, we have derived exact closed-form expressions of the outage probability in different situations. The numerical simulation results also reveal that the proposed scheme improve the secondary transmission performance compared with traditional mechanism in terms of secondary outage probability and energy efficiency.
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  • An Encrypted Image Retrieval Method Based on SimHash in Cloud Computing
  • Abstract With the massive growth of images data and the rise of cloud computing that can provide cheap storage space and convenient access, more and more users store data in cloud server. However, how to quickly query the expected data with privacy-preserving is still a challenging in the encryption image data retrieval. Towards this goal, this paper proposes a ciphertext image retrieval method based on SimHash in cloud computing. Firstly, we extract local feature of images, and then cluster the features by K-means. Based on it, the visual word codebook is introduced to represent feature information of images, which hashes the…
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