Current Issue : July - September Volume : 2020 Issue Number : 3 Articles : 5 Articles
The Radio Frequency Identification (RFID) data acquisition rate used for monitoring is so high that the RFID data stream contains\na large amount of redundant data, which increases the system overhead. To balance the accuracy and real-time performance of\nmonitoring, it is necessary to filter out redundant RFID data. We propose an algorithm called Time-Distance Bloom Filter\n(TDBF) that takes into account the read time and read distance of RFID tags, which greatly reduces data redundancy. In\naddition, we have proposed a measurement of the filter performance evaluation indicators. In experiments, we found that the\nperformance score of the TDBF algorithm was 5.2, while the Time Bloom Filter (TBF) score was only 0.03, which indicates that\nthe TDBF algorithm can achieve a lower false negative rate, lower false positive rate, and higher data compression rate.\nFurthermore, in a dynamic scenario, the TDBF algorithm can filter out valid data according to the actual scenario requirements....
Earthquakes cause significant damage to bridges, which have a very strategic location in transportation services. Thedestruction of\na bridge will seriously hinder emergency rescue. Rapid assessment of bridge seismic damage can help relevant departments to\nmake judgments quickly after earthquakes and save rescue time. This paper proposed a rapid assessment method for bridge\nseismic damage based on the random forest algorithm (RF) and artificial neural networks (ANN). This method evaluated the\nrelative importance of each uncertain influencing factor of the seismic damage to the girder bridges and arch bridges, respectively.\nThe input variables of the ANN model were the factors with higher importance value, and the output variables were damage states.\nThe data of the Wenchuan earthquake were used as a testing set and a training set, and the data of the Tangshan earthquake were\nused as a validation set. The bridges under serious and complete damage states are not accessible after earthquakes and should be\noverhauled and reinforced before earthquakes. The results demonstrate that the proposed approach has good performance for\nassessing the damage states of the two bridges. It is robust enough to extend and improve emergency decisions, to save time for\nrescue work, and to help with bridge construction....
Traditional calibration method is usually performed with expensive equipments such\nas three-axis turntable in a laboratory environment. However in practice, in order to ensure the\naccuracy and stability of the inertial navigation system (INS), it is usually necessary to recalibrate\nthe inertial measurement unit (IMU) without external equipment in the field. In this paper, a\nnew in-field recalibration method for triaxial accelerometer based on beetle swarm antenna search\n(BSAS) algorithm is proposed. Firstly, as a new intelligent optimization algorithm, BSAS algorithm\nand its improvements based on basic beetle antennae search (BAS) algorithm are introduced in\ndetail. Secondly, the nonlinear mathematical model of triaxial accelerometer is established for\nhigher calibration accuracy, and then 24 optimal measurement positions are designed by theoretical\nanalysis. In addition, the calibration procedures are improved according to the characteristics of BSAS\nalgorithm, then 15 calibration parameters in the nonlinear method are optimized by BSAS algorithm.\nBesides, the results of BSAS algorithm and basic BAS algorithm are compared by simulation, which\nshows the priority of BSAS algorithm in calibration field. Finally, two experiments demonstrate that\nthe proposed method can achieve high precision in-field calibration without any external equipment,\nand meet the accuracy requirements of the INS....
In this work, we propose a channel allocation and power control algorithm for energy harvesting (EH) device-to-device (D2D)\ncommunication based on nonorthogonal multiple access (NOMA). The algorithm considers usersâ?? quality of service (QoS) and\nenergy causality constraint to maximize the total capacity of D2D groups. The optimal offline allocation of channel and power is\nrealized firstly. Then, the offline optimization results are taken as the training dataset to train the neural network to obtain the\noptimal model of the transmission power. The online power allocation optimization algorithm is further proposed. Simulation\nresults show that the offline algorithm can improve the total capacity of D2D groups, and the performance of the online algorithm\nis close to the offline algorithm....
The Virgo cluster of galaxies is of great importance to study the development\nof the universe due to its close distance from the earth as well as being the\ncenter of the local super cluster. The problem that faces Virgo cluster studies\nis that it shares the same right ascension (RA) and Declination (DEC) ranges\nwith large number of background as well as foreground galaxies. This study\naims to geometrically and statistically estimate Virgo cluster membership.\nThe study employs Virgo cluster data, prepared by Harvard University. The\nradial velocity (RV) data of the Virgo cluster were treated and employed in\nexchange of missing galaxiesâ?? third dimension, taking advantage of their\nproportionality. The data were treated by K-means algorithm, using Matlab\n2014, and visual and logical exclusion of extremity galaxies to determine the\nrational center of the Virgo galaxies cluster. Results were presented, compared\nand discussed. Finally distances of galaxies from the Virgo cluster center\nwere employed along with normal probability distribution characteristics\nto identify the most probable Virgo cluster members from the range of Virgo\ncluster of galaxies. The results showed that out of 17,466 objects surveyed in\nVirgo galaxy range, only few of galaxies were estimated to be genuine Virgo\nmembers....
Loading....