A New Part-of-Speech Tagging System Based on Closed-words,Word Form and Rules

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.

Tax-folks hybrid navigation:A new model for resource aggregation in social tagging system

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.

A Novel RFID Localization Approach to Smart Self-Service Borrowing and Returning System

The misreading problem of a passive ultra-high-frequency(UHF)radio frequency identification(RFID)tag is a frequent problem arising in the field of librarianship.Unfortunately,existing solutions are something inefficient,e.g.,extra resource requirement,inaccuracy,and empiricism.To this end,under comprehensive analysis on the passive UHF RFID application in the librarianship scenario,a novel and judicious approach based on RFID localization is proposed to address such a misreading problem.Extensive simulation results show that the proposed approach can outperform the existing ones and can be an attractive candidate in practice.

Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.

Connotea中Social Tagging机制研究

选取Connotea为研究对象,统计分析标签、被标引资源、标引者两两关联关系,发现标签覆盖资源范围较广,标签共现现象突出,部分用户标引活跃,资源平均标签数较低,用户对内容关注度规律性转移,科研领域的用户比较多地使用规范词。提出增加标引词结构关联和细粒内容定位标引。

国外Social Tagging研究群体分析

基于抽取的国外知名数据库的学术文献,分析探讨Social Tagging研究群体的学科特征和研究视角。结果表明当前Social Tagging的研究群体主要局限于信息科学与计算机科学,且未形成居于统治权威地位的研究团体和研究人员。自从Social Tagging产生以来,"Social Tagging的组成功能"的研究一直是Social Tagging的基础性研究维度,不过随着应用深入发展,研究维度逐步转而融合信息检索和人机交互这两个相关领域知识分析"Tagger的行为及Social Tagging的界面设计"和"Social Tagging自身的组织和使用"这两个主要研究维度。

Analysis of quality-related proteins in golden pompano(Trachinotus ovatus)fillets with modified atmosphere packaging under superchilling storage

Here,we aimed to study the changes in proteome of golden pompano fillets during post-mortem storage.Tandem mass tags(TMT)-labeled quantitative proteomic strategy was applied to investigate the relationships between protein changes and quality characteristics of modified atmosphere packaging(MAP)fillets during superchilling(-3°C)storage.Scanning electron microscopy was used to show that the muscle histology microstructure of fillets was damaged to varying degrees,and low-field nuclear magnetic resonance was used to find that the immobilized water and free water in the muscle of fillets changed significantly.Total sulfhydryl content,TCA-soluble peptides and Ca2+-ATPase activity also showed that the fillet protein had a deterioration by oxidation and denaturation.The Fresh(FS),MAP,and air packaging(AP)groups were set.Total of 150 proteins were identified as differential abundant proteins(DAPs)in MAP/FS,while 209 DAPs were in AP/FS group.The KEGG pathway analysis indicated that most DAPs were involved in binding proteins and protein turnover.Correlation analysis found that 52 DAPs were correlated with quality traits.Among them,8 highly correlated DAPs are expected to be used as potential quality markers for protein oxidation and water-holding capacity.These results provide a further understanding of the muscle deterioration mechanism of packaging golden pompano fillets during superchilling.

Serum proteins differentially expressed in gestational diabetes mellitus assessed using isobaric tag for relative and absolute quantitation proteomics

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.

Differential Expression Analysis of Proteins Regulated by Rare Earth Cerium in Soybean Leaves at Seedling Stage

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.

34.TAG·西海美术馆:面朝大海的艺术长廊

设计:让·努维尔事务所地点:山东青岛西海岸新区时间:2012—2021年规模:17000 m^(2)TAG·西海美术馆位于一座半岛的海边,远离市区^([1,2])。从规划意图看,整个项目由美术馆和艺术工坊两部分组成,但由于工坊部分处于停工状态,艺术社区氛围尚未形成,作为主体建筑的美术馆便成了荒野中的孤独存在,公众可达性较差(图1)。尽管如此,从设计研究角度,这座美术馆仍有许多精彩看点值得关注。

Link Budget and Enhanced Communication Distance for Ambient Internet of Things

Backscatter communications will play an important role in connecting everything for beyond 5G(B5G)and 6G systems.One open challenge for backscatter communications is that the signals suffer a round-trip path loss so that the communication distance is short.In this paper,we first calculate the communication distance upper bounds for both uplink and downlink by measuring the tag sensitivity and reflection coefficient.It is found that the activation voltage of the envelope detection diode of the downlink tag is the main factor limiting the back-scatter communication distance.Based on this analysis,we then propose to implement a low-noise amplifier(LNA)module before the envelope detection at the tag to enhance the incident signal strength.Our experimental results on the hardware platform show that our method can increase the downlink communication range by nearly 20 m.

基于OPC Systems.NET智能建筑系统集成初探

论文以智能建筑集成的系统研发为应用背景,介绍OPC Systems.NET特性和智能客户端部署,分析与系统集成关联的技术,并深入探讨基于OPC Systems.NET平台的集成方法。

Global myocardial strain assessment by different imaging modalities to predict outcomes after ST-elevation myocardial infarction:A systematic review

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&#174; 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.

The Detectability for the Myocardial Fibrosis by Tagging Imaging on Cardiovascular Magnetic Resonance

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.

Tag与Tagging

Tag,直译标签,是一种由用户自定义的、用于描述信息的关键词。Tagging是用户为信息赋予Tag的行为。Delicious,Flickr等Web2.0网站的发展促进了它的流行,使之成为社会化书签、相册服务、博客等网站的常见功能。从目前网络发展形势而言——个人自生成内容(博文、图片、视频等)迅速增加,各类信息海量涌来——Tag可谓信息管理的强大利器。

A Cross Layer Protocol for Fast Identification of Blocked Tags in Large-Scale RFID Systems

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.

Recommender Systems Based on Tensor Decomposition

Recommender system is an effective tool to solve the problems of information overload.The traditional recommender systems,especially the collaborative filtering ones,only consider the two factors of users and items.While social networks contain abundant social information,such as tags,places and times.Researches show that the social information has a great impact on recommendation results.Tags not only describe the characteristics of items,but also reflect the interests and characteristics of users.Since the traditional recommender systems cannot parse multi-dimensional information,in this paper,a tensor decomposition model based on tag regularization is proposed which incorporates social information to benefit recommender systems.The original Singular Value Decomposition(SVD)model is optimized by mining the co-occurrence and mutual exclusion of tags,and their features are constrained by the relationship between tags.Experiments on real dataset show that the proposed algorithm achieves superior performance to existing algorithms.

Hacking Anti-Shoplifting System to Hide Data within Clothes

Steganography has been used to prevent unauthorized access to private information during transmission.It is the scheme of securing sensitive information by concealing it within carriers such as digital images,videos,audio,or text.Current steganography methods are working by assigning a cover le then embed the payload within it by making some modications,creating the stego-le.However,the left traces that are caused by these modications will make steganalysis algorithms easily detect the hidden payload.Aiming to solve this issue,a novel,highly robust steganography method based on hacking anti-shoplifting systems has proposed to hide data within clothes.The anti-Shoplifting system is an anti-theft security system that protects goods and products,leaving the store in an illegal way(i.e.,without paying for them).The proposed method works by modifying the default anti-shoplifting system by changing its built-in soft RFID(radio-frequency identication)tags sewn in clothes into NFC(Near Field Communication)tags.These NFC tags are smart tags that can communicate with NFC-Enabled smart-phones using NDEF(NFC Data Exchange Format).NDEF is one of the advancements added to RFID technology by NFC,which allows the data exchange.Every NDEF message has one/more NDEF records that contain record type,a unique ID,a length,and a payload of data that contains the secret message content that can be any type of data that ts in a byte stream.Based on NDEF and NFC-enabled smart-phones,the proposed method will take the secret message from the sender,make use of his NFC-enabled smart-phone to communicate with the NFC tag,then hide the secret message within the NDEF’s payload of the NFC tag stuck in clothes.Finally,to evaluate the proposed method,it has been compared with default(digital)steganography weak points.Such as time,lockable,robustness,attacks,capacity,and a few more points.The results and comparisons showed that the proposed method is more efcient than default(digital)steganography and has many advantages.

Jointly Part-of-Speech Tagging and Semantic Role Labeling Using Auxiliary Deep Neural Network Model

Previous studies have shown that there is potential semantic dependency between part-of-speech and semantic roles.At the same time,the predicate-argument structure in a sentence is important information for semantic role labeling task.In this work,we introduce the auxiliary deep neural network model,which models semantic dependency between part-of-speech and semantic roles and incorporates the information of predicate-argument into semantic role labeling.Based on the framework of joint learning,part-of-speech tagging is used as an auxiliary task to improve the result of the semantic role labeling.In addition,we introduce the argument recognition layer in the training process of the main task-semantic role labeling,so the argument-related structural information selected by the predicate through the attention mechanism is used to assist the main task.Because the model makes full use of the semantic dependency between part-of-speech and semantic roles and the structural information of predicate-argument,our model achieved the F1 value of 89.0%on the WSJ test set of CoNLL2005,which is superior to existing state-of-the-art model about 0.8%.

Identifying the Unknown Tags in a Large RFID System

Radio frequency identification(RFID) technology has been extensively used in various practical applications, such as inventory management and logistics control, with its outstanding features(e.g. non-line-ofsight reading and fast identification). And in a large RFID system, unknown tag identification uses total execution time as the performance criterion. However, the performance of existing protocols in terms of execution time is not ideal. To get better time efficiency, a novel unknown tag identification protocol(NUTIP) is proposed. The novelty of NUTIP is demonstrated mainly in two aspects: i) NUTIP deactivates some known tags and identifies or labels some unknown tags during its first phase to prevent these tags from interfering unknown tag identification. ii) We optimize the parameter settings to minimize the total execution time. Simulation experiments show that the proposed protocol is far superior to other relevant protocols and suitable for both sparse unknown tags environment and dense unknown tags environment.