In RFID(Radio Frequency IDentification)system,when multiple tags are in the operating range of one reader and send their information to the reader simultaneously,the signals of these tags are superimposed in the air,w...In RFID(Radio Frequency IDentification)system,when multiple tags are in the operating range of one reader and send their information to the reader simultaneously,the signals of these tags are superimposed in the air,which results in a collision and leads to the degrading of tags identifying efficiency.To improve the multiple tags’identifying efficiency due to collision,a physical layer network coding based binary search tree algorithm(PNBA)is proposed in this paper.PNBA pushes the conflicting signal information of multiple tags into a stack,which is discarded by the traditional anti-collision algorithm.In addition,physical layer network coding is exploited by PNBA to obtain unread tag information through the decoding operation of physical layer network coding using the conflicting information in the stack.Therefore,PNBA reduces the number of interactions between reader and tags,and improves the tags identification efficiency.Theoretical analysis and simulation results using MATLAB demonstrate that PNBA reduces the number of readings,and improve RFID identification efficiency.Especially,when the number of tags to be identified is 100,the average needed reading number of PNBA is 83%lower than the basic binary search tree algorithm,43%lower than reverse binary search tree algorithm,and its reading efficiency reaches 0.93.展开更多
For RFID tags, a Novel Tag Anti-collision Algorithm with Grouping (TAAG) is proposed. It divides tags into groups and adopts a deterministic method to identify tags within group. TAAG estimates the total number of tag...For RFID tags, a Novel Tag Anti-collision Algorithm with Grouping (TAAG) is proposed. It divides tags into groups and adopts a deterministic method to identify tags within group. TAAG estimates the total number of tags in systems from group identifying result and then adjusts the grouping method accordingly. The performance of the proposed TAAG algorithm is compared with the conventional tag anti-collision algorithms by simulation experiments. According to both the analysis and simulation result, the proposed algorithm shows better performance in terms of throughput, total slots used to identify and total cycles.展开更多
A tag-collision (or missed reads) in RFID system (Radio Frequency Identification) system degrades the identification efficiency. The so-called tag collision is that a reader cannot identify a tag when more than one ta...A tag-collision (or missed reads) in RFID system (Radio Frequency Identification) system degrades the identification efficiency. The so-called tag collision is that a reader cannot identify a tag when more than one tags respond to a reader at the same time. There are some major anti-collision protocols on resolving tag collision, e.g., ALOHA-based protocol, binary tree protocol, and Query Tree (QT) protocol. Up to date, most tag anti-collision protocols are QT protocols. QT protocols are categorized into M-ary query tree (QT). In the previous literature, choosing M = 3 (i.e., a ternary QT (TQT)) was proven to have the optimum performance for tag identification. Recently, Yeh et al. used parallel response approach to reduce the number of collisions. In this paper, we combine the partial response and TQT to propose an effective parallel response TQT (PRTQT) protocol. Simulation results reveal that our PRTQT outperforms Yeh et al.’s protocol and TQT protocol.展开更多
A radio frequency identification (RFID) reader will fail to identify tags if a collision occurs. This paper proposes a bi-slotted binary tree algorithm (BSBTA) with stack for RFID tag anti-collision to improve the per...A radio frequency identification (RFID) reader will fail to identify tags if a collision occurs. This paper proposes a bi-slotted binary tree algorithm (BSBTA) with stack for RFID tag anti-collision to improve the performance of binary tree algorithm (BTA). In BSBTA, the reader detects collisions by Manchester code and stores colliding prefixes in a stack. The query is composed of a two-bit prefix and an index value. Following every reader query, there are two timeslots for tags whose pointers and identities (IDs) match the query to respond, one for the tag whose next bit is 0 and the other for the tag with 1 as its next bit. Performance analysis and evaluation are also given. The time complexity and the communication complexity of BTA and BSBTA are derived. The simulation results compare the performance of BSBTA with several related anti-collision algorithms. It is shown that BSBTA outperforms BTA in terms of the average number of responded bits and timeslots for one tag identification.展开更多
A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems.The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA(DFSA)and to adjust ...A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems.The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA(DFSA)and to adjust access probability in random access protocols.Conventional researches estimate the number of tags in MAC layer based on statistics of empty slots,collided slots and successful slots.Usually,a collision detection algorithm is employed to determine types of time slots.Only three types are distinguished because of lack of ability to detect the number of tags in single time slot.In this paper,a physical layer algorithm is proposed to detect the number of tags in a collided slot.Mean shift algorithm is utilized,and some properties of backscatter signals are investigated.Simulation results verify the effectiveness of the proposed solution in terms of low estimation error with a high SNR range,outperforming the existing MAC layer approaches.展开更多
Radio frequency identification(RFID)has been widespread used in massive items tagged domains.However,tag collision increases both time and energy consumption of RFID network.Tag collision can seriously affect the succ...Radio frequency identification(RFID)has been widespread used in massive items tagged domains.However,tag collision increases both time and energy consumption of RFID network.Tag collision can seriously affect the success of tag identification.An efficient anti-collision protocol is very crucially in RFID system.In this paper,an improved binary search anti-collision protocol namely BRTP is proposed to cope with the tag collision concern,which introduces a Bi-response mechanism.In Bi-response mechanism,two groups of tags allowed to reply to the reader in the same slot.According to Bi-response mechanism,the BRTP strengthens the tag identification of RFID network by reducing the total number of queries and exchanged messages between the reader and tags.Both theoretical analysis and numerical results verify the effectiveness of the proposed BRTP in various performance metrics including the number of total slots,system efficiency,communication complexity and total identification time.The BRTP is suitable to be applied in passive RFID systems.展开更多
In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniq...In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.展开更多
In the radio frequency identification (RFID) system based on surface acoustic wave (SAW) technique, some tags often locate in the field of a transceiver at the same time. These tags produce simultaneous echo signals w...In the radio frequency identification (RFID) system based on surface acoustic wave (SAW) technique, some tags often locate in the field of a transceiver at the same time. These tags produce simultaneous echo signals which "collide" when they arrive back at the transceiver, which leads to difficult identification. In this paper, smart antenna technique is presented to implement anti-collision in SAW RFID system. The direction of arrivals (DOAs) are used to denote the locations of tags, and genetic algorithm (GA) is suggested to find the optimal estimates of the DOAs in complex multimodal search spaces. Once the DOAs are obtained, the array weights are formed and the signals of tags are recovered to implement decoding. The experimental results show that the GA-based smart antenna technique works well in some occasions.展开更多
Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or d...Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.展开更多
This study was to explore the functional mechanism of rare earth regulating soybean leaves and the characteristics and functions of differentially expressed proteins under the regulation of rare earth. In this study, ...This study was to explore the functional mechanism of rare earth regulating soybean leaves and the characteristics and functions of differentially expressed proteins under the regulation of rare earth. In this study, Dongnong 42 was used as material, and 30 mg·L^(-1) CeCl_(3) solution was sprayed on soybean leaves at the seedling stage. Tandem mass tag(TMT) quantitative proteomics technique and bioinformatics analysis were used to identify soybean leaf proteins. A total of 8 510 proteins were identified, and 127 differentially expressed proteins(DEPs) in response to rare earth cerium regulation were identified, among which 64 were upregulated and 63 were down-regulated. The gene ontology(GO) annotation indicated that DEPs were mainly involved in metabolic process, cellular process, response to stimulus, biological regulation, and response to a stimulus;DEPs in cell module categories were mainly involved in cells, cell part, organelle, membrane, membrane part, organelle par, and protein-containing complex;DEPs in molecular functional categories were mainly involved in catalytic activity, binding and antioxidant activity. Kyoto encyclopedia of genes and genomes(KEGG) pathway significantly enriched starch and sucrose metabolism, glycolysis/gluconeogenesis, galactose metabolism, pentose phosphate pathway, and MAPK signaling pathway-plant. These DEPs were mainly involved in photosynthesis, glucose metabolism and stress response. Forty-six differential protein interaction networks were identified by protein interaction network analysis. This experiment provided a reference for studies of the mechanism of rare earth cerium regulating soybean leaf function from the proteomic perspective.展开更多
BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients a...BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.展开更多
Recently,object identification with radio frequency identification(RFID)technology is becoming increasingly popular.Identification time is a key performance metric to evaluate the RFID system.The present paper analyze...Recently,object identification with radio frequency identification(RFID)technology is becoming increasingly popular.Identification time is a key performance metric to evaluate the RFID system.The present paper analyzes the deficiencies of the state-of-the-arts algorithms and proposes a novel sub-frame-based algorithm with adaptive frame breaking policy to lower the tag identification time for EPC global C1 Gen2 UHF RFID standard.Through the observation of slot statistics in a sub-frame,the reader estimates the tag quantity and efficiently calculates an optimal frame size to fit the unread tags.Only when the expected average identification time in the calculated frame size is less than that in the previous frame size,the reader starts the new frame.Moreover,the estimation of the proposed algorithm is implemented by the look-up tables,which allows dramatically reduction in the computational complexity.Simulation results show noticeable throughput and time efficiency improvements of the proposed solution over the existing approaches.展开更多
In this paper, we develop a novel mathematical model to estimate the probability distribution function of the number of tags discovered after a certain number of interrogation rounds. In addition, the pdfs of the numb...In this paper, we develop a novel mathematical model to estimate the probability distribution function of the number of tags discovered after a certain number of interrogation rounds. In addition, the pdfs of the number of rounds needed to discover all the tags are also calculated. The estimation of such pdfs will be helpful in estimating the number of interrogation rounds and the optimal parameter configuration of the RFID system which in turn will be helpful in estimating the time needed to discover all tags. Our results show that the proposed model accurately predicts the tags detection probability. We then use the proposed model to optimally configure the reader parameters (i.e. the frame size and the number of interrogation rounds).展开更多
Auto anti-collision technology is one of the main research subjects of automobiles’ safety technology. Aiming at the key technology of Auto anti-collision, measuring the distance from obstacles, based on the theory o...Auto anti-collision technology is one of the main research subjects of automobiles’ safety technology. Aiming at the key technology of Auto anti-collision, measuring the distance from obstacles, based on the theory of phase laser distance ranging, Laser Diode (LD) distance-measuring system for auto anti-collision has been developed to solve the problem of on-line measuring distance technology in middle to long distance utilizing the good characteristics of LD when modulating its optical intensity and adopting typical kinds of filter techniques in this paper. By theoretical analysis, adopting typical kinds of filter techniques can reduce the interference of strong light, so distance-measuring range can be 0.5–100 m in daytime or 1–200 m at night. And more, from theoretical analysis and experiment result, it can guarantee the high measuring resolution which can be less than 24.5 mm, utilizing the method of two Laser Diode optical intensity modulating wavelength and complimenting precise calibration and revision. The idea of LD distance-measuring technology is novel and feasible and this technology can be applied in Auto anti-collision. Key words laser diode - phase laser distance ranging - filter techniques - auto anti-collision CLC number TH 161 Foundation item: Supported by the National Natural Science Foundation of China (59675080, 59805006) and Wuhan Chenguang Foundation (20025001001)Biography: Zhang Xin-bao (1965-), male, Associate professor, research direction: precise mechanism and instrument.展开更多
Multi-tag collision imposes a vital detrimental effect on reading performanceof an RFID system. In order to ameliorate such collision problem and to improve thereading performance, this paper proposes an efficient tag...Multi-tag collision imposes a vital detrimental effect on reading performanceof an RFID system. In order to ameliorate such collision problem and to improve thereading performance, this paper proposes an efficient tag identification algorithm termedas the Enhanced Adaptive Tree Slotted Aloha (EATSA). The key novelty of EATSA is toidentify the tags using grouping strategy. Specifically, the whole tag set is divided intogroups by a frame of size F. In cases multiple tags fall into a group, the tags of the groupare recognized by the improved binary splitting (IBS) method whereas the rest tags arewaiting in the pipeline. In addition, an early observation mechanism is introduced toupdate the frame size to an optimum value fitting the number of tags. Theoretical analysisand simulation results show that the system throughput of our proposed algorithm canreach as much as 0.46, outperforming the prior Aloha-based protocols.展开更多
In this paper,a dynamic multi-ary query tree(DMQT)anti-collision protocol for Radio Frequency Identification(RFID)systems is proposed for large scale passive RFID tag identification.The proposed DMQT protocol is based...In this paper,a dynamic multi-ary query tree(DMQT)anti-collision protocol for Radio Frequency Identification(RFID)systems is proposed for large scale passive RFID tag identification.The proposed DMQT protocol is based on an iterative process between the reader and tags which identifies the position of collision bits through map commands and dynamically encodes them to optimize slots allocation through query commands.In this way,the DMQT completely eliminates empty slots and greatly reduces collision slots,which in turn reduces the identification time and energy costs.In addition and differently to other known protocols,the DMQT does not need to estimate the number of tags,reducing the protocol implementation complexity and eliminating the uncertainty caused by the estimation algorithm.A numerical analysis shows that DMQT has better performance than other algorithms for a number of tags larger than 300.Meanwhile,when the number of tags is 2000 and the tag identity(ID)length is 128 bits,the total identification time is 2.58 s and the average energy cost for a tag identification is 1.2 mJ,which are 16.9%and 10.4%less than those of state-of-the-art algorithms,respectively.In addition,a DMQT extension based on ACK command has also been presented to deal with capture effect and avoid missing identification.展开更多
基金the National Natural Science Foundation of China under Grant 61502411Natural Science Foundation of Jiangsu Province under Grant BK20150432 and BK20151299+7 种基金Natural Science Research Project for Universities of Jiangsu Province under Grant 15KJB520034China Postdoctoral Science Foundation under Grant 2015M581843Jiangsu Provincial Qinglan ProjectTeachers Overseas Study Program of Yancheng Institute of TechnologyJiangsu Provincial Government Scholarship for Overseas StudiesTalents Project of Yancheng Institute of Technology under Grant KJC2014038“2311”Talent Project of Yancheng Institute of TechnologyOpen Fund of Modern Agricultural Resources Intelligent Management and Application Laboratory of Huzhou Normal University.
文摘In RFID(Radio Frequency IDentification)system,when multiple tags are in the operating range of one reader and send their information to the reader simultaneously,the signals of these tags are superimposed in the air,which results in a collision and leads to the degrading of tags identifying efficiency.To improve the multiple tags’identifying efficiency due to collision,a physical layer network coding based binary search tree algorithm(PNBA)is proposed in this paper.PNBA pushes the conflicting signal information of multiple tags into a stack,which is discarded by the traditional anti-collision algorithm.In addition,physical layer network coding is exploited by PNBA to obtain unread tag information through the decoding operation of physical layer network coding using the conflicting information in the stack.Therefore,PNBA reduces the number of interactions between reader and tags,and improves the tags identification efficiency.Theoretical analysis and simulation results using MATLAB demonstrate that PNBA reduces the number of readings,and improve RFID identification efficiency.Especially,when the number of tags to be identified is 100,the average needed reading number of PNBA is 83%lower than the basic binary search tree algorithm,43%lower than reverse binary search tree algorithm,and its reading efficiency reaches 0.93.
文摘For RFID tags, a Novel Tag Anti-collision Algorithm with Grouping (TAAG) is proposed. It divides tags into groups and adopts a deterministic method to identify tags within group. TAAG estimates the total number of tags in systems from group identifying result and then adjusts the grouping method accordingly. The performance of the proposed TAAG algorithm is compared with the conventional tag anti-collision algorithms by simulation experiments. According to both the analysis and simulation result, the proposed algorithm shows better performance in terms of throughput, total slots used to identify and total cycles.
文摘A tag-collision (or missed reads) in RFID system (Radio Frequency Identification) system degrades the identification efficiency. The so-called tag collision is that a reader cannot identify a tag when more than one tags respond to a reader at the same time. There are some major anti-collision protocols on resolving tag collision, e.g., ALOHA-based protocol, binary tree protocol, and Query Tree (QT) protocol. Up to date, most tag anti-collision protocols are QT protocols. QT protocols are categorized into M-ary query tree (QT). In the previous literature, choosing M = 3 (i.e., a ternary QT (TQT)) was proven to have the optimum performance for tag identification. Recently, Yeh et al. used parallel response approach to reduce the number of collisions. In this paper, we combine the partial response and TQT to propose an effective parallel response TQT (PRTQT) protocol. Simulation results reveal that our PRTQT outperforms Yeh et al.’s protocol and TQT protocol.
基金the National Natural Science Foundation of China (No. 61071078)
文摘A radio frequency identification (RFID) reader will fail to identify tags if a collision occurs. This paper proposes a bi-slotted binary tree algorithm (BSBTA) with stack for RFID tag anti-collision to improve the performance of binary tree algorithm (BTA). In BSBTA, the reader detects collisions by Manchester code and stores colliding prefixes in a stack. The query is composed of a two-bit prefix and an index value. Following every reader query, there are two timeslots for tags whose pointers and identities (IDs) match the query to respond, one for the tag whose next bit is 0 and the other for the tag with 1 as its next bit. Performance analysis and evaluation are also given. The time complexity and the communication complexity of BTA and BSBTA are derived. The simulation results compare the performance of BSBTA with several related anti-collision algorithms. It is shown that BSBTA outperforms BTA in terms of the average number of responded bits and timeslots for one tag identification.
基金This work was supported in part by the National Natural Science Foundation of China under project contracts[NOS.61601093,61791082,61701116,61371047]in part by Sichuan Provincial Science and Technology Planning Program of China under project contracts No.2016GZ0061 and No.2018HH0044+2 种基金in part by Guangdong Provincial Science and Technology Planning Program of China under project contracts No.2015B090909004 and No.2016A010101036in part by the fundamental research funds for the Central Universities under project contract No.ZYGX2016Z011in part by Science and Technology on Electronic Information Control Laboratory.
文摘A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems.The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA(DFSA)and to adjust access probability in random access protocols.Conventional researches estimate the number of tags in MAC layer based on statistics of empty slots,collided slots and successful slots.Usually,a collision detection algorithm is employed to determine types of time slots.Only three types are distinguished because of lack of ability to detect the number of tags in single time slot.In this paper,a physical layer algorithm is proposed to detect the number of tags in a collided slot.Mean shift algorithm is utilized,and some properties of backscatter signals are investigated.Simulation results verify the effectiveness of the proposed solution in terms of low estimation error with a high SNR range,outperforming the existing MAC layer approaches.
基金This work was partially supported by the Key-Area Research and Development Program of Guangdong Province(2019B010136001,20190166)the Basic and Applied Basic Research Major Program for Guangdong Province(2019B030302002)the Science and Technology Planning Project of Guangdong Province LZC0023 and LZC0024.
文摘Radio frequency identification(RFID)has been widespread used in massive items tagged domains.However,tag collision increases both time and energy consumption of RFID network.Tag collision can seriously affect the success of tag identification.An efficient anti-collision protocol is very crucially in RFID system.In this paper,an improved binary search anti-collision protocol namely BRTP is proposed to cope with the tag collision concern,which introduces a Bi-response mechanism.In Bi-response mechanism,two groups of tags allowed to reply to the reader in the same slot.According to Bi-response mechanism,the BRTP strengthens the tag identification of RFID network by reducing the total number of queries and exchanged messages between the reader and tags.Both theoretical analysis and numerical results verify the effectiveness of the proposed BRTP in various performance metrics including the number of total slots,system efficiency,communication complexity and total identification time.The BRTP is suitable to be applied in passive RFID systems.
基金supported by the National Natural Science Foundation of China(No.62271274).
文摘In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.
基金The National Natural Science Foundation ofChina(No10304012)
文摘In the radio frequency identification (RFID) system based on surface acoustic wave (SAW) technique, some tags often locate in the field of a transceiver at the same time. These tags produce simultaneous echo signals which "collide" when they arrive back at the transceiver, which leads to difficult identification. In this paper, smart antenna technique is presented to implement anti-collision in SAW RFID system. The direction of arrivals (DOAs) are used to denote the locations of tags, and genetic algorithm (GA) is suggested to find the optimal estimates of the DOAs in complex multimodal search spaces. Once the DOAs are obtained, the array weights are formed and the signals of tags are recovered to implement decoding. The experimental results show that the GA-based smart antenna technique works well in some occasions.
基金supported by Yunnan Provincial Major Science and Technology Special Plan Projects(Grant Nos.202202AD080003,202202AE090008,202202AD080004,202302AD080003)National Natural Science Foundation of China(Grant Nos.U21B2027,62266027,62266028,62266025)Yunnan Province Young and Middle-Aged Academic and Technical Leaders Reserve Talent Program(Grant No.202305AC160063).
文摘Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.
基金Supported by the National Natural Science Foundation of China(31471440)。
文摘This study was to explore the functional mechanism of rare earth regulating soybean leaves and the characteristics and functions of differentially expressed proteins under the regulation of rare earth. In this study, Dongnong 42 was used as material, and 30 mg·L^(-1) CeCl_(3) solution was sprayed on soybean leaves at the seedling stage. Tandem mass tag(TMT) quantitative proteomics technique and bioinformatics analysis were used to identify soybean leaf proteins. A total of 8 510 proteins were identified, and 127 differentially expressed proteins(DEPs) in response to rare earth cerium regulation were identified, among which 64 were upregulated and 63 were down-regulated. The gene ontology(GO) annotation indicated that DEPs were mainly involved in metabolic process, cellular process, response to stimulus, biological regulation, and response to a stimulus;DEPs in cell module categories were mainly involved in cells, cell part, organelle, membrane, membrane part, organelle par, and protein-containing complex;DEPs in molecular functional categories were mainly involved in catalytic activity, binding and antioxidant activity. Kyoto encyclopedia of genes and genomes(KEGG) pathway significantly enriched starch and sucrose metabolism, glycolysis/gluconeogenesis, galactose metabolism, pentose phosphate pathway, and MAPK signaling pathway-plant. These DEPs were mainly involved in photosynthesis, glucose metabolism and stress response. Forty-six differential protein interaction networks were identified by protein interaction network analysis. This experiment provided a reference for studies of the mechanism of rare earth cerium regulating soybean leaf function from the proteomic perspective.
基金This study was reviewed and approved by the Maternal and child health hospital of Hubei Province(Approval No.20201025).
文摘BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.
文摘Recently,object identification with radio frequency identification(RFID)technology is becoming increasingly popular.Identification time is a key performance metric to evaluate the RFID system.The present paper analyzes the deficiencies of the state-of-the-arts algorithms and proposes a novel sub-frame-based algorithm with adaptive frame breaking policy to lower the tag identification time for EPC global C1 Gen2 UHF RFID standard.Through the observation of slot statistics in a sub-frame,the reader estimates the tag quantity and efficiently calculates an optimal frame size to fit the unread tags.Only when the expected average identification time in the calculated frame size is less than that in the previous frame size,the reader starts the new frame.Moreover,the estimation of the proposed algorithm is implemented by the look-up tables,which allows dramatically reduction in the computational complexity.Simulation results show noticeable throughput and time efficiency improvements of the proposed solution over the existing approaches.
文摘In this paper, we develop a novel mathematical model to estimate the probability distribution function of the number of tags discovered after a certain number of interrogation rounds. In addition, the pdfs of the number of rounds needed to discover all the tags are also calculated. The estimation of such pdfs will be helpful in estimating the number of interrogation rounds and the optimal parameter configuration of the RFID system which in turn will be helpful in estimating the time needed to discover all tags. Our results show that the proposed model accurately predicts the tags detection probability. We then use the proposed model to optimally configure the reader parameters (i.e. the frame size and the number of interrogation rounds).
文摘Auto anti-collision technology is one of the main research subjects of automobiles’ safety technology. Aiming at the key technology of Auto anti-collision, measuring the distance from obstacles, based on the theory of phase laser distance ranging, Laser Diode (LD) distance-measuring system for auto anti-collision has been developed to solve the problem of on-line measuring distance technology in middle to long distance utilizing the good characteristics of LD when modulating its optical intensity and adopting typical kinds of filter techniques in this paper. By theoretical analysis, adopting typical kinds of filter techniques can reduce the interference of strong light, so distance-measuring range can be 0.5–100 m in daytime or 1–200 m at night. And more, from theoretical analysis and experiment result, it can guarantee the high measuring resolution which can be less than 24.5 mm, utilizing the method of two Laser Diode optical intensity modulating wavelength and complimenting precise calibration and revision. The idea of LD distance-measuring technology is novel and feasible and this technology can be applied in Auto anti-collision. Key words laser diode - phase laser distance ranging - filter techniques - auto anti-collision CLC number TH 161 Foundation item: Supported by the National Natural Science Foundation of China (59675080, 59805006) and Wuhan Chenguang Foundation (20025001001)Biography: Zhang Xin-bao (1965-), male, Associate professor, research direction: precise mechanism and instrument.
文摘Multi-tag collision imposes a vital detrimental effect on reading performanceof an RFID system. In order to ameliorate such collision problem and to improve thereading performance, this paper proposes an efficient tag identification algorithm termedas the Enhanced Adaptive Tree Slotted Aloha (EATSA). The key novelty of EATSA is toidentify the tags using grouping strategy. Specifically, the whole tag set is divided intogroups by a frame of size F. In cases multiple tags fall into a group, the tags of the groupare recognized by the improved binary splitting (IBS) method whereas the rest tags arewaiting in the pipeline. In addition, an early observation mechanism is introduced toupdate the frame size to an optimum value fitting the number of tags. Theoretical analysisand simulation results show that the system throughput of our proposed algorithm canreach as much as 0.46, outperforming the prior Aloha-based protocols.
基金The authors received funding for this study from the National Key R&D Program(https://chinainnovationfunding.eu/national-key-rd-programmes/),project contract No.2018YFB1802102(G.W.)and 2018AAA0103203(W.T,F.X,G.W.)from the National Natural Science Foundation of China(https://www.nsfc.gov.cn/),project contracts No.61971113(G.W.)and 61901095(D.I.)+6 种基金from the Guangdong Provincial Research and Development Plan in Key Areas(https://chinainnovationfunding.eu/funding-programmes-guangdong-province-2/)project contracts No.2019B010141001(G.W.)and 2019B010142001(G.W.)from the Sichuan Provincial Science and Technology Planning Program(https://www.sc.gov.cn/10462/10758/10759/10763/2010/10/28/10147629.shtml)project contracts No.2020YFG0039(G.W.),2021YFG0013(G.W.),and 2021YFH0133(D.I.)from the Ministry of Education(http://en.moe.gov.cn/)and China Mobile(http://www.chinamobileltd.com)Joint Fund Program,project contract No.MCM20180104(G.W.,G.L.)from the fundamental research funds for the Central Universities(managed by Department of Finance,https://www.fmprc.gov.cn/mfa_eng/wjb_663304/zzjg_663340/cws_665320/)project contract no.YGX2019Z022(G.W.,G.L.,D.I.).
文摘In this paper,a dynamic multi-ary query tree(DMQT)anti-collision protocol for Radio Frequency Identification(RFID)systems is proposed for large scale passive RFID tag identification.The proposed DMQT protocol is based on an iterative process between the reader and tags which identifies the position of collision bits through map commands and dynamically encodes them to optimize slots allocation through query commands.In this way,the DMQT completely eliminates empty slots and greatly reduces collision slots,which in turn reduces the identification time and energy costs.In addition and differently to other known protocols,the DMQT does not need to estimate the number of tags,reducing the protocol implementation complexity and eliminating the uncertainty caused by the estimation algorithm.A numerical analysis shows that DMQT has better performance than other algorithms for a number of tags larger than 300.Meanwhile,when the number of tags is 2000 and the tag identity(ID)length is 128 bits,the total identification time is 2.58 s and the average energy cost for a tag identification is 1.2 mJ,which are 16.9%and 10.4%less than those of state-of-the-art algorithms,respectively.In addition,a DMQT extension based on ACK command has also been presented to deal with capture effect and avoid missing identification.