A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is gi...A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is givento illustrate the application of this method.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
Social tagging is one of the most important characteristics of Web 2.0 services, and social tagging systems (STS) are becoming more and more popular for users to annotate, organize and share items on the Web. Moreov...Social tagging is one of the most important characteristics of Web 2.0 services, and social tagging systems (STS) are becoming more and more popular for users to annotate, organize and share items on the Web. Moreover, online social network has been incorporated into social tagging systems. As more and more users tend to interact with real friends on the Web, personalized user recommendation service provided in social tagging systems is very appealing. In this paper, we propose a personalized user recommendation method, and our method handles not only the users' interest networks, but also the social network information. We empirically show that our method outperforms a state-of-the-art method on real dataset from Last.fro dataset and Douban.展开更多
About 25,000 rice T-DNA insertional mutant lines were generated using the vector pCAS04 which has both promoter-trapping and activation-tagging function. Southern blot analysis revealed that about 40% of these mutants...About 25,000 rice T-DNA insertional mutant lines were generated using the vector pCAS04 which has both promoter-trapping and activation-tagging function. Southern blot analysis revealed that about 40% of these mutants were single copy integration and the average T-DNA insertion number was 2.28. By extensive phenotyping in the field, quite a number of agronomically important mutants were obtained. Histochemical GUS assay with 4,310 primary mutants revealed that the GUS-staining frequency was higher than that of the previous reports in various tissues and especially high in flowers. The T-DNA flanking sequences of some mutants were isolated and the T-DNA insertion sites were mapped to the rice genome. The flanking sequence analysis demonstrated the different integration pattern of the right border and left border into rice genome. Compared with Arabidopsis and poplar, it is much varied in the T-DNA border junctions in rice.展开更多
With emergence of Web 2.0,taxonomy and folksonomy have shown a trend of complementarity and integration,and a hybrid tax-folks navigation structure has become a new way to facilitate resource aggregation in social tag...With emergence of Web 2.0,taxonomy and folksonomy have shown a trend of complementarity and integration,and a hybrid tax-folks navigation structure has become a new way to facilitate resource aggregation in social tagging system.In this paper,the generation mechanism of tax-folks hybrid navigation model is analyzed,and the tax-folks hybrid navigation model,which consist of six modules:data preparation,concept lattice construction,concept lattice analysis,tax-folks mapping,tax-folks hybrid navigation tree and outputs& evaluation,is constructed with the theory of formal concept analysis.The study finds that tax-folks hybrid navigation model takes into account the advantages of taxonomy and folksonomy,achieves a tree-like resource aggregation,and effectively improves the resources-finding ability in social tagging system.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
When the radio frequency identification(RFID)system inventories multiple tags,the recognition rate will be seriously affected due to collisions.Based on the existing dynamic frame slotted Aloha(DFSA)algorithm,a sub-fr...When the radio frequency identification(RFID)system inventories multiple tags,the recognition rate will be seriously affected due to collisions.Based on the existing dynamic frame slotted Aloha(DFSA)algorithm,a sub-frame observation and cyclic redundancy check(CRC)grouping combined dynamic framed slotted Aloha(SUBF-CGDFSA)algorithm is proposed.The algorithm combines the precise estimation method of the quantity of large-scale tags,the large-scale tags grouping mechanism based on CRC pseudo-randomcharacteristics,and the Aloha anti-collision optimization mechanism based on sub-frame observation.By grouping tags and sequentially identifying themwithin subframes,it accurately estimates the number of remaining tags and optimizes frame length accordingly to improve efficiency in large-scale RFID systems.Simulation outcomes demonstrate that this proposed algorithmcan effectively break through the system throughput bottleneck of 36.8%,which is up to 30%higher than the existing DFSA standard scheme,and has more significant advantages,which is suitable for application in largescale RFID tags scenarios.展开更多
With joint analysis based on the parents, F 1, F 2 and backcrosses, the authors found that the resistance of the maize inbred line Huangzaosi to the maize dwarf mosaic virus strain B was conditioned by a major gene ...With joint analysis based on the parents, F 1, F 2 and backcrosses, the authors found that the resistance of the maize inbred line Huangzaosi to the maize dwarf mosaic virus strain B was conditioned by a major gene and polygene, and identified a new major gene. Bulked segregate and microsatellite analysis of a F 2 progeny from the combination of Huangzaosi×Mo17 were used to identify the resistance gene, mdm1(t), on the long arm of chromosome 6. This new resistance gene is tightly linked to and located between the microsatellite markers loci, phi077 and bnlg391. The linkage distances between phi077-mdm1(t) and mdm1(t)-bnlg391 are 4.74 centiMorgan (cM) and 6.72 cM respectively.展开更多
This review article reports the recent progress in the development of a new group of molecule-based flow diagnostic techniques, which include molecular tag- ging velocimetry (MTV) and molecular tagging thermometry ...This review article reports the recent progress in the development of a new group of molecule-based flow diagnostic techniques, which include molecular tag- ging velocimetry (MTV) and molecular tagging thermometry (MTT), for both qualitative flow visualization of thermally induced flow structures and quantitative whole-field mea- surements of flow velocity and temperature distributions. The MTV and MTT techniques can also be easily combined to result in a so-called molecular tagging velocimetry and ther- mometry (MTV&T) technique, which is capble of achieving simultaneous measurements of flow velocity and temperature distribution in fluid flows. Instead of using tiny particles, the molecular tagging techniques (MTV, MTT, and MTV&T) use phosphorescent molecules, which can be turned into long-lasting glowing marks upon excitation by photons of appropriate wavelength, as the tracers for the flow veloc- ity and temperature measurements. The unique attraction and implementation of the molecular tagging techniques are demonstrated by three application examples, which include: (1) to quantify the unsteady heat transfer process from a heated cylinder to the surrounding fluid flow in order to exam- ine the thermal effects on the wake instabilities behind the heated cylinder operating in mixed and forced heat convec- tion regimes, (2) to reveal the time evolution of unsteady heat transfer and phase changing process inside micro-sized, icing water droplets in order to elucidate the underlying physics pertinent to aircraft icing phenomena, and (3) to achievesimultaneous droplet size, velocity and temperature measure- ments of "in-flight" droplets to characterize the dynamic and thermodynamic behaviors of flying droplets in spray flows.展开更多
The paper proposes a unified framework to combine the advantages of the fast one-at-a-time approach and the high-performance all-at-once approach to perform Chinese Word Segmentation(CWS) and Part-of-Speech(PoS) taggi...The paper proposes a unified framework to combine the advantages of the fast one-at-a-time approach and the high-performance all-at-once approach to perform Chinese Word Segmentation(CWS) and Part-of-Speech(PoS) tagging.In this framework,the input of the PoS tagger is a candidate set of several CWS results provided by the CWS model.The widely used one-at-a-time approach and all-at-once approach are two extreme cases of the proposed candidate-based approaches.Experiments on Penn Chinese Treebank 5 and Tsinghua Chinese Treebank show that the generalized candidate-based approach outperforms one-at-a-time approach and even the all-at-once approach.The candidate-based approach is also faster than the time-consuming all-at-once approach.The authors compare three different methods based on sentence,words and character-intervals to generate the candidate set.It turns out that the word-based method has the best performance.展开更多
In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language proc...In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language processing. The speaker independently continuous speech recognition experiments and the part-of-speech tagging experiments show that Markov family model has higher performance than hidden Markov model. The precision is enhanced from 94.642% to 96.214% in the part-of-speech tagging experiments, and the work rate is reduced by 11.9% in the speech recognition experiments with respect to HMM baseline system.展开更多
AIM: To conduct a systematic review relating myocardial strain assessed by different imaging modalities for prognostication following ST-elevation myocardial infarction(STEMI).METHODS: An online literature search was ...AIM: To conduct a systematic review relating myocardial strain assessed by different imaging modalities for prognostication following ST-elevation myocardial infarction(STEMI).METHODS: An online literature search was performed in Pub Med and OVID® electronic databases to identify any studies that assessed global myocardial strain parameters using speckle-tracking echocardiography(STE) and/or cardiac magnetic resonance imaging(CMR) techniques [either myocardial tagging or feature tracking(FT) software] in an acute STEMI cohort(days 0-14 post-event) to predict prognosis [either development of major adverse cardiac events(MACE)] or adverse left ventricular(LV) remodelling at follow-up(≥ 6 mo for MACE,≥ 3 mo for remodelling). Search was restricted to studies within the last 20 years. All studies that matched the pre-defined search criteria were reviewed and their results interpreted. Due to considerable heterogeneity between studies,metaanalysis was not performed.RESULTS: A total of seven studies(n = 7) were identified that matched the search criteria. All studies used STE to evaluate strain parameters- five(n = 5) assessed global longitudinal strain(GLS)(n = 5),one assessed GLS rate(GLS-R)(n = 1) and one assessed both(n = 1). Three studies showed that GLS independently predicted the development of adverse LV remodelling by multivariate analysis- odds ratio between 1.19(CI: 1.04-1.37,P < 0.05) and 10(CI: 6.7-14,P < 0.001) depending on the study. Four studies showed that GLS predicted the development of MACE- hazard ratio(HR) between 1.1(CI: 1-1.1,P = 0.006) and 2.34(1.10-4.97,P < 0.05). One paper found that GLS-R could significantly predict MACEHR 18(10-35,P < 0.001)- whilst another showed it did not. GLS <-10.85% had sensitivity/specificity of 89.7%/91% respectively for predicting the development of remodelling whilst GLS <-13% could predict the development of MACE with sensitivity/specificity of 100%/89% respectively. No suitable studies were identified that assessed global strain by CMR tagging or FT techniques.CONCLUSION: GLS measured acutely post-STEMI by STE is a predictor of poor prognosis. Further research is needed to show that this is true for CMR-based techniques.展开更多
Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causin...Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causing a collision of message replies.In many practical scenarios,the number of blocked tags may vary,or even be small.For example,the attacker may only block the important customers or high-value items.To avoid the disclosure of privacy and economic losses,it is of great importance to fast pinpoint these blocked ones.However,existing works do not take into account the impact of the number of blocked tags on the execution time and suffer from incomplete identification of blocked tags,long identification time or privacy leakage.To overcome these limits,we propose a cross layer blocked tag identification protocol(CLBI).CLBI consists of multiple rounds,in which it enables multiple unblocked tags to select one time slot and concurrently verify them by using tag estimation in physical layer.Benefiting from the utilization of most collision slots,the execution time can be greatly reduced.Furthermore,for efficient identification of blocked tags under different proportions,we propose a hybrid protocol named adaptive cross layer blocked tag identification protocol(A-CLBI),which estimates the remaining blocked tag in each round and adjusts the identification strategy accordingly.Extensive simulations show that our protocol outperforms state-of-the-art blocked tags identification protocol.展开更多
Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequen...Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequency identification(RFID) has been widely used in warehouse for item identifying. Meanwhile, RFID technology also has great potential for pallets localization which is underutilized in warehouse management. RFID-based checking-in and inventory systems have been applied in warehouse management by many enterprises. Localization approach is studied, which is compatible with existing RFID checking-in and inventory systems. A novel RFID localization approach is proposed for pallets checking-in. Phase variation of nearby tags was utilized to estimate the position of added pallets. A novel inventory localization approach combing angle of arrival(AOA) measurement and received signal strength(RSS) is also proposed for pallets inventory. Experiments were carried out using standard UHF passive RFID system. Experimental results show an acceptable localization accuracy which can satisfy the requirement of warehouse management.展开更多
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
Purpose: Myocardial fibrosis causes cardiac dysfunction, arrhythmias, and sudden death. Tagging imaging on cardiovascular MR can measure the intra-myocardial motion from the dynamic deformation of lines superimposed o...Purpose: Myocardial fibrosis causes cardiac dysfunction, arrhythmias, and sudden death. Tagging imaging on cardiovascular MR can measure the intra-myocardial motion from the dynamic deformation of lines superimposed on the myocardium. The purpose of this study was to evaluate the detectability of myocardial fibrosis using tagging imaging and to compare this with conventional cine imaging. Materials and Methods: We reviewed 4 normal control (NML) subjects, 4 patients with myocarditis (MYO), and 4 patients with old myocardial infarction (ICM). We measured circumferential strain (Ecc) from tagging imaging, and regional wall thickening (rWT) from cine imaging. Fibrosis was determined from a late gadolinium enhancement (LGE) image. We evaluate diagnostic performance by comparing values of the area under curve (AUC) using ROC analysis. Results: Mean values of Ecc and rWT decreased in the area of LGE both in MYO and ICM patients. AUC values of Ecc and rWT in all subjects were 0.98 and 0.84, respectively (p < 0.0001). These values in MYO patients were 0.95 and 0.72 (p = 0.007), respectively, and 0.99 and 0.75, respectively, in ICM patients (p = 0.0008). Conclusions: Both Ecc and rWT decreased in the area with fibrosis in the patients with MYO and ICM. Tagging imaging showed better detectability of myocardial fibrosis than did cine imaging.展开更多
Hidden Markov Model(HMM) is a main solution to ambiguities in Chinese segmentation anti POS (part-of-speech) tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS infor...Hidden Markov Model(HMM) is a main solution to ambiguities in Chinese segmentation anti POS (part-of-speech) tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS informatiou in contexts, they do not utilize lexieal information which is crucial for resoMng certain morphologieal ambiguity. This paper proposes a method which incorporates lexieal information and wider context information into HMM. Model induction anti related smoothing technique are presented in detail. Experiments indicate that this technique improves the segmentation and tagging accuracy by nearly 1%.展开更多
文摘A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is givento illustrate the application of this method.
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supported by the National Basic Research Program of China (2009CB320505)the Hi-Tech Research and Development Program of China (20011AA 01A102)+2 种基金the Nuclear High-Based Project of China (2012ZX01039004-008)the National Nature Science Foundation of China (61002011)the Electronic Information Industry Development Fund Program 'The Development and Industrialization of Key Supporting Software in Cloud Computing (Cloud Storage Service)'
文摘Social tagging is one of the most important characteristics of Web 2.0 services, and social tagging systems (STS) are becoming more and more popular for users to annotate, organize and share items on the Web. Moreover, online social network has been incorporated into social tagging systems. As more and more users tend to interact with real friends on the Web, personalized user recommendation service provided in social tagging systems is very appealing. In this paper, we propose a personalized user recommendation method, and our method handles not only the users' interest networks, but also the social network information. We empirically show that our method outperforms a state-of-the-art method on real dataset from Last.fro dataset and Douban.
基金supported by the National High Technology Research and Development Program of China (No.2002AAZ2001)the National Natural Sciences Foundation of China (No.30270758 and 30621001)
文摘About 25,000 rice T-DNA insertional mutant lines were generated using the vector pCAS04 which has both promoter-trapping and activation-tagging function. Southern blot analysis revealed that about 40% of these mutants were single copy integration and the average T-DNA insertion number was 2.28. By extensive phenotyping in the field, quite a number of agronomically important mutants were obtained. Histochemical GUS assay with 4,310 primary mutants revealed that the GUS-staining frequency was higher than that of the previous reports in various tissues and especially high in flowers. The T-DNA flanking sequences of some mutants were isolated and the T-DNA insertion sites were mapped to the rice genome. The flanking sequence analysis demonstrated the different integration pattern of the right border and left border into rice genome. Compared with Arabidopsis and poplar, it is much varied in the T-DNA border junctions in rice.
基金an outcome of the project "Research on resource multi-dimensional aggregation and navigation in social tagging system"(No.13YJC870032) supported by MOE(Ministry of Education in China) Youth Project of Humanities and Social Sciencesthe project "Complementation and integration of ontology and folksonomy under Web 2.0"(No.14YS007) supported by Innovation Program of Shanghai Municipal Education Commission
文摘With emergence of Web 2.0,taxonomy and folksonomy have shown a trend of complementarity and integration,and a hybrid tax-folks navigation structure has become a new way to facilitate resource aggregation in social tagging system.In this paper,the generation mechanism of tax-folks hybrid navigation model is analyzed,and the tax-folks hybrid navigation model,which consist of six modules:data preparation,concept lattice construction,concept lattice analysis,tax-folks mapping,tax-folks hybrid navigation tree and outputs& evaluation,is constructed with the theory of formal concept analysis.The study finds that tax-folks hybrid navigation model takes into account the advantages of taxonomy and folksonomy,achieves a tree-like resource aggregation,and effectively improves the resources-finding ability in social tagging system.
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 in part by National Natural Science Foundation of China(U22B2004,62371106)in part by the Joint Project of China Mobile Research Institute&X-NET(Project Number:2022H002)+6 种基金in part by the Pre-Research Project(31513070501)in part by National Key R&D Program(2018AAA0103203)in part by Guangdong Provincial Research and Development Plan in Key Areas(2019B010141001)in part by Sichuan Provincial Science and Technology Planning Program of China(2022YFG0230,2023YFG0040)in part by the Fundamental Enhancement Program Technology Area Fund(2021-JCJQ-JJ-0667)in part by the Joint Fund of ZF and Ministry of Education(8091B022126)in part by Innovation Ability Construction Project for Sichuan Provincial Engineering Research Center of Communication Technology for Intelligent IoT(2303-510109-04-03-318020).
文摘When the radio frequency identification(RFID)system inventories multiple tags,the recognition rate will be seriously affected due to collisions.Based on the existing dynamic frame slotted Aloha(DFSA)algorithm,a sub-frame observation and cyclic redundancy check(CRC)grouping combined dynamic framed slotted Aloha(SUBF-CGDFSA)algorithm is proposed.The algorithm combines the precise estimation method of the quantity of large-scale tags,the large-scale tags grouping mechanism based on CRC pseudo-randomcharacteristics,and the Aloha anti-collision optimization mechanism based on sub-frame observation.By grouping tags and sequentially identifying themwithin subframes,it accurately estimates the number of remaining tags and optimizes frame length accordingly to improve efficiency in large-scale RFID systems.Simulation outcomes demonstrate that this proposed algorithmcan effectively break through the system throughput bottleneck of 36.8%,which is up to 30%higher than the existing DFSA standard scheme,and has more significant advantages,which is suitable for application in largescale RFID tags scenarios.
文摘With joint analysis based on the parents, F 1, F 2 and backcrosses, the authors found that the resistance of the maize inbred line Huangzaosi to the maize dwarf mosaic virus strain B was conditioned by a major gene and polygene, and identified a new major gene. Bulked segregate and microsatellite analysis of a F 2 progeny from the combination of Huangzaosi×Mo17 were used to identify the resistance gene, mdm1(t), on the long arm of chromosome 6. This new resistance gene is tightly linked to and located between the microsatellite markers loci, phi077 and bnlg391. The linkage distances between phi077-mdm1(t) and mdm1(t)-bnlg391 are 4.74 centiMorgan (cM) and 6.72 cM respectively.
基金supported by the National Aeronauticaland Space Administration(NASA)(Grant NNX12AC21A)The support of the National Science Foundation(NSF)under award numbers of CBET-1064196,IIA-1064235 and CBET-1435590
文摘This review article reports the recent progress in the development of a new group of molecule-based flow diagnostic techniques, which include molecular tag- ging velocimetry (MTV) and molecular tagging thermometry (MTT), for both qualitative flow visualization of thermally induced flow structures and quantitative whole-field mea- surements of flow velocity and temperature distributions. The MTV and MTT techniques can also be easily combined to result in a so-called molecular tagging velocimetry and ther- mometry (MTV&T) technique, which is capble of achieving simultaneous measurements of flow velocity and temperature distribution in fluid flows. Instead of using tiny particles, the molecular tagging techniques (MTV, MTT, and MTV&T) use phosphorescent molecules, which can be turned into long-lasting glowing marks upon excitation by photons of appropriate wavelength, as the tracers for the flow veloc- ity and temperature measurements. The unique attraction and implementation of the molecular tagging techniques are demonstrated by three application examples, which include: (1) to quantify the unsteady heat transfer process from a heated cylinder to the surrounding fluid flow in order to exam- ine the thermal effects on the wake instabilities behind the heated cylinder operating in mixed and forced heat convec- tion regimes, (2) to reveal the time evolution of unsteady heat transfer and phase changing process inside micro-sized, icing water droplets in order to elucidate the underlying physics pertinent to aircraft icing phenomena, and (3) to achievesimultaneous droplet size, velocity and temperature measure- ments of "in-flight" droplets to characterize the dynamic and thermodynamic behaviors of flying droplets in spray flows.
基金supported by the National Natural Science Foundation of China under GrantNo.60873174
文摘The paper proposes a unified framework to combine the advantages of the fast one-at-a-time approach and the high-performance all-at-once approach to perform Chinese Word Segmentation(CWS) and Part-of-Speech(PoS) tagging.In this framework,the input of the PoS tagger is a candidate set of several CWS results provided by the CWS model.The widely used one-at-a-time approach and all-at-once approach are two extreme cases of the proposed candidate-based approaches.Experiments on Penn Chinese Treebank 5 and Tsinghua Chinese Treebank show that the generalized candidate-based approach outperforms one-at-a-time approach and even the all-at-once approach.The candidate-based approach is also faster than the time-consuming all-at-once approach.The authors compare three different methods based on sentence,words and character-intervals to generate the candidate set.It turns out that the word-based method has the best performance.
基金Project(60763001)supported by the National Natural Science Foundation of ChinaProjects(2009GZS0027,2010GZS0072)supported by the Natural Science Foundation of Jiangxi Province,China
文摘In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language processing. The speaker independently continuous speech recognition experiments and the part-of-speech tagging experiments show that Markov family model has higher performance than hidden Markov model. The precision is enhanced from 94.642% to 96.214% in the part-of-speech tagging experiments, and the work rate is reduced by 11.9% in the speech recognition experiments with respect to HMM baseline system.
基金funded by the University of Leicester and the National Institute for Health Research (NIHR) in the United Kingdom
文摘AIM: To conduct a systematic review relating myocardial strain assessed by different imaging modalities for prognostication following ST-elevation myocardial infarction(STEMI).METHODS: An online literature search was performed in Pub Med and OVID® electronic databases to identify any studies that assessed global myocardial strain parameters using speckle-tracking echocardiography(STE) and/or cardiac magnetic resonance imaging(CMR) techniques [either myocardial tagging or feature tracking(FT) software] in an acute STEMI cohort(days 0-14 post-event) to predict prognosis [either development of major adverse cardiac events(MACE)] or adverse left ventricular(LV) remodelling at follow-up(≥ 6 mo for MACE,≥ 3 mo for remodelling). Search was restricted to studies within the last 20 years. All studies that matched the pre-defined search criteria were reviewed and their results interpreted. Due to considerable heterogeneity between studies,metaanalysis was not performed.RESULTS: A total of seven studies(n = 7) were identified that matched the search criteria. All studies used STE to evaluate strain parameters- five(n = 5) assessed global longitudinal strain(GLS)(n = 5),one assessed GLS rate(GLS-R)(n = 1) and one assessed both(n = 1). Three studies showed that GLS independently predicted the development of adverse LV remodelling by multivariate analysis- odds ratio between 1.19(CI: 1.04-1.37,P < 0.05) and 10(CI: 6.7-14,P < 0.001) depending on the study. Four studies showed that GLS predicted the development of MACE- hazard ratio(HR) between 1.1(CI: 1-1.1,P = 0.006) and 2.34(1.10-4.97,P < 0.05). One paper found that GLS-R could significantly predict MACEHR 18(10-35,P < 0.001)- whilst another showed it did not. GLS <-10.85% had sensitivity/specificity of 89.7%/91% respectively for predicting the development of remodelling whilst GLS <-13% could predict the development of MACE with sensitivity/specificity of 100%/89% respectively. No suitable studies were identified that assessed global strain by CMR tagging or FT techniques.CONCLUSION: GLS measured acutely post-STEMI by STE is a predictor of poor prognosis. Further research is needed to show that this is true for CMR-based techniques.
基金This work was supported in part by the National Natural Science Foundation of China under project contracts Nos.61701082,61701116,61601093,61971113 and 61901095in part by National Key R&D Program under project Nos.2018YFB1802102 and 2018AAA0103203+3 种基金in part by Guangdong Provincial Research and Development Plan in Key Areas under project contract Nos.2019B010141001 and 2019B010142001in part by Sichuan Provincial Science and Technology Planning Program under project contracts Nos.2018HH0034,2019YFG0418,2019YFG0120 and 2018JY0246in part by the fundamental research funds for the Central Universities under project contract No.ZYGX2016J004in part by Science and Technology on Electronic Information Control Laboratory.
文摘Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causing a collision of message replies.In many practical scenarios,the number of blocked tags may vary,or even be small.For example,the attacker may only block the important customers or high-value items.To avoid the disclosure of privacy and economic losses,it is of great importance to fast pinpoint these blocked ones.However,existing works do not take into account the impact of the number of blocked tags on the execution time and suffer from incomplete identification of blocked tags,long identification time or privacy leakage.To overcome these limits,we propose a cross layer blocked tag identification protocol(CLBI).CLBI consists of multiple rounds,in which it enables multiple unblocked tags to select one time slot and concurrently verify them by using tag estimation in physical layer.Benefiting from the utilization of most collision slots,the execution time can be greatly reduced.Furthermore,for efficient identification of blocked tags under different proportions,we propose a hybrid protocol named adaptive cross layer blocked tag identification protocol(A-CLBI),which estimates the remaining blocked tag in each round and adjusts the identification strategy accordingly.Extensive simulations show that our protocol outperforms state-of-the-art blocked tags identification protocol.
基金Project(2009BADB9B09)supported by the National Key Technologies R&D Program of China
文摘Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequency identification(RFID) has been widely used in warehouse for item identifying. Meanwhile, RFID technology also has great potential for pallets localization which is underutilized in warehouse management. RFID-based checking-in and inventory systems have been applied in warehouse management by many enterprises. Localization approach is studied, which is compatible with existing RFID checking-in and inventory systems. A novel RFID localization approach is proposed for pallets checking-in. Phase variation of nearby tags was utilized to estimate the position of added pallets. A novel inventory localization approach combing angle of arrival(AOA) measurement and received signal strength(RSS) is also proposed for pallets inventory. Experiments were carried out using standard UHF passive RFID system. Experimental results show an acceptable localization accuracy which can satisfy the requirement of warehouse management.
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Purpose: Myocardial fibrosis causes cardiac dysfunction, arrhythmias, and sudden death. Tagging imaging on cardiovascular MR can measure the intra-myocardial motion from the dynamic deformation of lines superimposed on the myocardium. The purpose of this study was to evaluate the detectability of myocardial fibrosis using tagging imaging and to compare this with conventional cine imaging. Materials and Methods: We reviewed 4 normal control (NML) subjects, 4 patients with myocarditis (MYO), and 4 patients with old myocardial infarction (ICM). We measured circumferential strain (Ecc) from tagging imaging, and regional wall thickening (rWT) from cine imaging. Fibrosis was determined from a late gadolinium enhancement (LGE) image. We evaluate diagnostic performance by comparing values of the area under curve (AUC) using ROC analysis. Results: Mean values of Ecc and rWT decreased in the area of LGE both in MYO and ICM patients. AUC values of Ecc and rWT in all subjects were 0.98 and 0.84, respectively (p < 0.0001). These values in MYO patients were 0.95 and 0.72 (p = 0.007), respectively, and 0.99 and 0.75, respectively, in ICM patients (p = 0.0008). Conclusions: Both Ecc and rWT decreased in the area with fibrosis in the patients with MYO and ICM. Tagging imaging showed better detectability of myocardial fibrosis than did cine imaging.
基金国家高技术研究发展计划(863计划),the National Natural Science Foundation of China
文摘Hidden Markov Model(HMM) is a main solution to ambiguities in Chinese segmentation anti POS (part-of-speech) tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS informatiou in contexts, they do not utilize lexieal information which is crucial for resoMng certain morphologieal ambiguity. This paper proposes a method which incorporates lexieal information and wider context information into HMM. Model induction anti related smoothing technique are presented in detail. Experiments indicate that this technique improves the segmentation and tagging accuracy by nearly 1%.