The efficiency for the detection and identification of photons with the ALICE PHOton Spectrometer PHOS has been studied with the Monte-Carlo generated data. In particular, the influence on the efficiency of the PHOS-m...The efficiency for the detection and identification of photons with the ALICE PHOton Spectrometer PHOS has been studied with the Monte-Carlo generated data. In particular, the influence on the efficiency of the PHOS-module edge-effect and of the material in front of PHOS have been examined.展开更多
The identification of deuterons with momenta in the range of 0.52−0.72 GeV/c is studied with specific ionization energy loss information using a data sample collected by the BESIII detector at center-of-mass energies ...The identification of deuterons with momenta in the range of 0.52−0.72 GeV/c is studied with specific ionization energy loss information using a data sample collected by the BESIII detector at center-of-mass energies between 4.009 and 4.946 GeV.Clean deuteron samples are selected using time of flight information.For all data samples,the deuteron identification efficiencies are higher than 95%,with a maximum difference of%between data and Monte Carlo simulation.This verifies the effectiveness of the deuteron identification method based on specific ionization energy loss and provides valuable information for future studies on processes involving deuterons in the final state at BESIII.展开更多
In radio frequency identification （RFID） systems, tag collision arbitration is a significant issue for fast tag identification. This article proposes a novel tag anti-collision algorithm called framed slotted ALOHA ...In radio frequency identification （RFID） systems, tag collision arbitration is a significant issue for fast tag identification. This article proposes a novel tag anti-collision algorithm called framed slotted ALOHA with grouping tactic and binary selection （GB-FSA）. The novelty of GB-FSA algorithm is that the reader uses binary tree algorithm to identify the tags according to the collided slot counters information. Furthermore, to save slots, tags are randomly divided into several groups based on the number of collided binary bits in the identification codes （IDs） of tags, and then only the number of the first group of tags is estimated. Performance analysis and simulation results show that the GB-FSA algorithm improves the identification efficiency by 9.9%-16.3% compared to other ALOHA-based tag anti-collision algorithms when the number of tags is 1000.展开更多
基金Supported by Ministry of Science & Technology of China(2008CB317106)National Natural Science Foundation of China(10575044,10635020)Key Project of Chinese Ministry of Education(306022,IRT0624)
文摘The efficiency for the detection and identification of photons with the ALICE PHOton Spectrometer PHOS has been studied with the Monte-Carlo generated data. In particular, the influence on the efficiency of the PHOS-module edge-effect and of the material in front of PHOS have been examined.
基金Supported by the National Natural Science Foundation of China(11975118,12205141,12375071)。
文摘The identification of deuterons with momenta in the range of 0.52−0.72 GeV/c is studied with specific ionization energy loss information using a data sample collected by the BESIII detector at center-of-mass energies between 4.009 and 4.946 GeV.Clean deuteron samples are selected using time of flight information.For all data samples,the deuteron identification efficiencies are higher than 95%,with a maximum difference of%between data and Monte Carlo simulation.This verifies the effectiveness of the deuteron identification method based on specific ionization energy loss and provides valuable information for future studies on processes involving deuterons in the final state at BESIII.
基金supported by the Program for New Century Excellent Talents in University, China (NCET-06-0510)
文摘In radio frequency identification （RFID） systems, tag collision arbitration is a significant issue for fast tag identification. This article proposes a novel tag anti-collision algorithm called framed slotted ALOHA with grouping tactic and binary selection （GB-FSA）. The novelty of GB-FSA algorithm is that the reader uses binary tree algorithm to identify the tags according to the collided slot counters information. Furthermore, to save slots, tags are randomly divided into several groups based on the number of collided binary bits in the identification codes （IDs） of tags, and then only the number of the first group of tags is estimated. Performance analysis and simulation results show that the GB-FSA algorithm improves the identification efficiency by 9.9%-16.3% compared to other ALOHA-based tag anti-collision algorithms when the number of tags is 1000.
