Using SVM to construct a Chinese dependency parser

In Chinese, dependency analysis has been shown to be a powerful syntactic parser because the order of phrases in a sentence is relatively free compared with English. Conventional dependency parsers require a number of sophisticated rules that have to be handcrafted by linguists, and are too cumbersome to maintain. To solve the problem, a parser using SVM (Support Vector Machine) is introduced. First, a new strategy of dependency analysis is proposed. Then some chosen feature types are used for learning and for creating the modification matrix using SVM. Finally, the dependency of phrases in the sentence is generated. Experiments conducted to analyze how each type of feature affects parsing accuracy, showed that the model can increase accuracy of the dependency parser by 9.2%.

An Efficient Way to Parse Logs Automatically for Multiline Events

In order to obtain information or discover knowledge from system logs,the first step is to performlog parsing,whereby unstructured raw logs can be transformed into a sequence of structured events.Although comprehensive studies on log parsing have been conducted in recent years,most assume that one event object corresponds to a single-line message.However,in a growing number of scenarios,one event object spans multiple lines in the log,for which parsing methods toward single-line events are not applicable.In order to address this problem,this paper proposes an automated log parsing method for multiline events(LPME).LPME finds multiline event objects via iterative scanning,driven by a set of heuristic rules derived from practice.The advantage of LPME is that it proposes a cohesion-based evaluation method for multiline events and a bottom-up search approach that eliminates the process of enumerating all combinations.We analyze the algorithmic complexity of LPME and validate it on four datasets from different backgrounds.Evaluations show that the actual time complexity of LPME parsing for multiline events is close to the constant time,which enables it to handle large-scale sample inputs.On the experimental datasets,the performance of LPME achieves 1.0 for recall,and the precision is generally higher than 0.9,which demonstrates the effectiveness of the proposed LPME.

Linear algorithm for lexicographic enumeration of CFG parse trees

We study CFG parse tree enumeration in this paper. By dividing the set of all parse trees into infinite hierarchies according to height of parse tree, the hierarchical lexicographic order on the set of parse trees is established. Then grammar-based algorithms for counting and enumerating CFG parse trees in this order are presented. To generate a parse tree of height n, the time complexity is O（n）. If τ is a lowest parse tree for its yield, then O（n） =O（｜｜τ｜｜ ＋ 1）, where ｜｜τ｜｜ is the length of the sentence （yield） generated by τ. The sentence can be obtained as a by-product of the parse tree. To compute sentence from its parse tree （needn＇t be lowest one）, the time complexity is O（node）＋O（｜｜τ｜｜ ＋ 1）, where node is the number of non-leaf nodes of parse tree τ. To generate both a complete lowest parse tree and its yield at the same time, the time complexity is O（｜｜τ｜｜ ＋ 1）.

Kernel-Based Semantic Relation Detection and Classification via Enriched Parse Tree Structure

This paper proposes a tree kernel method of semantic relation detection and classification （RDC） between named entities. It resolves two critical problems in previous tree kernel methods of RDC. First, a new tree kernel is presented to better capture the inherent structural information in a parse tree by enabling the standard convolution tree kernel with context-sensitiveness and approximate matching of sub-trees. Second, an enriched parse tree structure is proposed to well derive necessary structural information, e.g., proper latent annotations, from a parse tree. Evaluation on the ACE RDC corpora shows that both the new tree kernel and the enriched parse tree structure contribute significantly to RDC and our tree kernel method much outperforms the state-of-the-art ones.

Semantic Role Labeling of Chinese Nominal Predicates with Dependency-Driven Constituent Parse Tree Structure

This paper explores a tree kernel based method for semantic role labeling （SRL） of Chinese nominal predicates via a convolution tree kernel. In particular, a new parse tree representation structure, called dependency-driven constituent parse tree （D-CPT）, is proposed to combine the advantages of both constituent and dependence parse trees. This is achieved by directly representing various kinds of dependency relations in a CPT-style structure, which employs dependency relation types instead of phrase labels in CPT （Constituent Parse Tree）. In this way, D-CPT not only keeps the dependency relationship information in the dependency parse tree （DPT） structure but also retains the basic hierarchical structure of CPT style. Moreover, several schemes are designed to extract various kinds of necessary information, such as the shortest path between the nominal predicate and the argument candidate, the support verb of the nominal predicate and the head argument modified by the argument candidate, from D-CPT. This largely reduces the noisy information inherent in D-CPT. Finally, a convolution tree kernel is employed to compute the similarity between two parse trees. Besides, we also implement a feature-based method based on D-CPT. Evaluation on Chinese NomBank corpus shows that our tree kernel based method on D-CPT performs significantly better than other tree kernel-based ones and achieves comparable performance with the state-of-the-art feature-based ones. This indicates the effectiveness of the novel D-CPT structure in representing various kinds of dependency relations in a CPT-style structure and our tree kernel based method in exploring the novel D-CPT structure. This also illustrates that the kernel-based methods are competitive and they are complementary with the feature- based methods on SRL.

Neural Parse Combination

Analyzing the syntactic structure of natural languages by parsing is an important task in artificial intelligence. Due to the complexity of natural languages, individual parsers tend to make different yet complementary errors. We propose a neural network based approach to combine parses from different parsers to yield a more accurate parse than individual ones. Unlike conventional approaches, our method directly transforms linearized candidate parses into the ground-truth parse. Experiments on the Penn English Treebank show that the proposed method improves over a state-of-the-art parser combination approach significantly.

ML-Parser:An Eficient and Accurate Online Log Parser

A log is a text message that is generated in various services,frameworks,and programs.The majority of log data mining tasks rely on log parsing as the first step,which transforms raw logs into formatted log templates.Existing log parsing approaches often fail to effectively handle the trade-off between parsing quality and performance.In view of this,in this paper,we present Multi-Layer Parser(ML-Parser),an online log parser that runs in a streaming manner.Specifically,we present a multi-layer structure in log parsing to strike a balance between efficiency and effectiveness.Coarse-grained tokenization and a fast similarity measure are applied for efficiency while fine-grained tokenization and an accurate similarity measure are used for effectiveness.In experiments,we compare ML-Parser with two existing online log parsing approaches,Drain and Spell,on ten real-world datasets,five labeled and five unlabeled.On the five labeled datasets,we use the proportion of correctly parsed logs to measure the accuracy,and ML-Parser achieves the highest accuracy on four datasets.On the whole ten datasets,we use Loss metric to measure the parsing quality.ML-Parse achieves the highest quality on seven out of the ten datasets while maintaining relatively high efficiency.

Effectiveness and safety of early lens extraction during par plana vitrectomy for proliferative diabetes retinopathy with mild cataract:a randomized clinical trial

●AIM:To evaluate the effectiveness and safety of early lens extraction during pars plana vitrectomy(PPV)for proliferative diabetic retinopathy(PDR)compared to those of PPV with subsequent cataract surgery.●METHODS:This multicenter randomized controlled trial was conducted in three Chinese hospitals on patients with PDR,aged>45y,with mild cataracts.The participants were randomly assigned to the combined(PPV combined with simultaneously cataract surgery,i.e.,phacovitrectomy)or subsequent(PPV with subsequent cataract surgery 6mo later)group and followed up for 12mo.The primary outcome was the change in best-corrected visual acuity(BCVA)from baseline to 6mo,and the secondary outcomes included complication rates and medical expenses.●RESULTS:In total,129 patients with PDR were recruited and equally randomized(66 and 63 in the combined and subsequent groups respectively).The change in BCVA in the combined group[mean,36.90 letters;95%confidence interval(CI),30.35–43.45]was significantly better(adjusted difference,16.43;95%CI,8.77–24.08;P<0.001)than in the subsequent group(mean,22.40 letters;95%CI,15.55–29.24)6mo after the PPV,with no significant difference between the two groups at 12mo.The overall surgical risk of two sequential surgeries was significantly higher than that of the combined surgery for neovascular glaucoma(17.65%vs 3.77%,P=0.005).No significant differences were found in the photocoagulation spots,surgical time,and economic expenses between two groups.In the subsequent group,the duration of work incapacity(22.54±9.11d)was significantly longer(P<0.001)than that of the combined group(12.44±6.48d).●CONCLUSION:PDR patients aged over 45y with mild cataract can also benefit from early lens extraction during PPV with gratifying effectiveness,safety and convenience,compared to sequential surgeries.

Internal limiting membrane peeling combined with silicone oil or air tamponade for highly myopic foveoschisis

AIM:To compare the efficacy of pars plana vitrectomy(PPV)combined with internal limiting membrane(ILM)and silicone oil or sterile air tamponade for the treatment of myopic foveoschisis(MF)in highly myopic eyes.METHODS:This retrospective study included 48 myopic eyes of 40 patients with MF and axial lengths(ALs)ranging from 26-32 mm treated between January 2020 and January 2022.All patients were underwent PPV combined with ILM peeling followed by sterile air or silicone oil tamponade and followed up at least 12mo.Based on the features on spectral-domain optical coherence tomography(SD-OCT),the eyes were divided into the MF-only group(Group A,n=15 eyes),MF with central foveal detachment group(Group B,n=20 eyes),and MF with lamellar macular hole group(Group C,n=13 eyes).According to AL,eyes were further divided into three groups:Group D(26.01-28.00 mm,n=12 eyes),Group E(28.01-30.00 mm,n=26 eyes),and Group F(30.01-32.00 mm,n=10 eyes).The best-corrected visual acuity(BCVA),central foveal thickness(CFT),and complications were recorded.RESULTS:The patients included 16 males and 24 females with the mean age of 56±9.82y.The BCVA and CFT improved in all groups after surgery(P<0.01),while there was no significant difference of the CFT in Group A,B,and C postoperatively(P>0.05).The intergroup differences of BCVA and CFT postoperatively were statistically significant in Group D,E,and F.Twenty eyes were injected with sterile air,and 28 eyes were injected with silicone oil for tamponade based on the AL.However,there was no statistically significant difference among Groups D,E,and F in terms of the results of sterile air or silicone oil tamponade.The mean recovery time was 5.9mo for MF patients subjected to silicone oil tamponade and 7.7mo for patients subjected to sterile air tamponade,and the difference was not statistically significant.CONCLUSION:PPV and ILM peeling combined with silicone oil or sterile air tamponade can achieve good results for MF in highly myopic eyes with ALs≤32 mm.

Endophthalmitis in silicone oil-filled eye: A case report

BACKGROUND Endophthalmitis occurring in silicone oil-filled eyes is a very rare occurrence,with reported incidence rates ranging between 0.07%and 0.039%.Traditional methods of management of infectious endophthalmitis include the removal of silicone oil,washout of the vitreous cavity,administration of intravitreal antibiotics,and reinjection of silicone oil.CASE SUMMARY Herein,we report the case of a 39-year-old man with unilateral endophthalmitis after pars plana vitrectomy and silicone oil tamponade.Intravitreal injections of full-dose antibiotics and anterior chamber washout were used to treat the patient.No signs of retinal toxicity were observed during the follow-up period.CONCLUSION Intravitreal full-dose antibiotic injections and anterior chamber washout are promising alternatives to traditional therapies for endophthalmitis in silicone oilfilled eyes.

Performance Enhancement of XML Parsing Using Regression and Parallelism

The Extensible Markup Language(XML)files,widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications.With the existing Document Object Model(DOM)based parsing,the performance degrades due to sequential processing and large memory requirements,thereby requiring an efficient XML parser to mitigate these issues.In this paper,we propose a Parallel XML Tree Generator(PXTG)algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework(RXPF)that analyzes and predicts performance through profiling,regression,and code generation for efficient parsing.The PXTG algorithm is based on dividing the XML file into n parts and producing n trees in parallel.The profiling phase of the RXPF framework produces a dataset by measuring the performance of various parsing models including StAX,SAX,DOM,JDOM,and PXTG on different cores by using multiple file sizes.The regression phase produces the prediction model,based on which the final code for efficient parsing of XML files is produced through the code generation phase.The RXPF framework has shown a significant improvement in performance varying from 9.54%to 32.34%over other existing models used for parsing XML files.

Differential distribution of fibrovascular proliferative membranes in 25-gauge vitrectomy for proliferative diabetic retinopathy

AIM:To analyze the distribution of fibrovascular proliferative membranes(FVPMs)in proliferative diabetic retinopathy(PDR)patients that treated with pars plana vitrectomy(PPV),and to evaluate the outcomes separately.METHODS:This was a retrospective and cross-sectional study.Consecutive 25-gauge(25-G)PPV cases operated for PDR from May 2018 to April 2020.According to the FVPMs images outlined after operations,subjects were assigned into three groups:arcade type group,juxtapapillary type group,and central type group.All patients were followed up for over one year.General characteristics,operation-related variables,postoperative parameters and complications were recorded.RESULTS:Among 103 eyes recruited,the FVPMs distribution of nasotemporal and inferiosuperioral was significantly different(both P<0.01),with 95(92.23%)FVPMs located in the nasal quadrants,and 74(71.84%)in the inferior.The eyes with a central FVPM required the longest operation time,with silicon oil used in most patients,generally combined with tractional retinal detachment(RD)and rhegmatogenous RD,the worst postoperative bestcorrected visual acuity(BCVA)and the highest rates of recurrent RD(all P<0.05).FVPM type,age of onset diabetes mellitus,preoperative BCVA,and combined with tractional RD and rhegmatogenous RD were significantly associated with BCVA improvement(all P<0.05).Compared with the central type group,the arcade type group had higher rates of BCVA improvement.CONCLUSION:FVPMs are more commonly found in the nasal and inferior mid-peripheral retina in addition to the area of arcade vessels.Performing 25-G PPV for treating PDR eyes with central FVPM have relatively worse prognosis.

Certis: Cloud Asset Management & Threat Evaluation Using Behavioral Fingerprinting at Application Layer

This paper introduces Certis, a powerful framework that addresses the challenges of cloud asset tracking, management, and threat detection in modern cybersecurity landscapes. It enhances asset identification and anomaly detection through SSL certificate parsing, cloud service provider integration, and advanced fingerprinting techniques like JARM at the application layer. Current work will focus on cross-layer malicious behavior identification to further enhance its capabilities, including minimizing false positives through AI-based learning techniques. Certis promises to offer a powerful solution for organizations seeking proactive cybersecurity defenses in the face of evolving threats.

PostgreSQL分析器的研究

介绍了对象关系数据库系统 ＰｏｓｔｇｒｅＳＱＬ的内部结构、查询处理的过程及 ＰｏｓｔｇｒｅＳＱＬ语法／词法分析器的实现，并通过一个 ＳＱＬ语句实例，分析了 ＰｏｓｔｇｒｅＳＱＬ语法／词法分析器的内部结构，最后给出Ｑｕｅｒｙ树的详细数据结构图示．

Multi-Plate Microbial Monitoring Terminal Based on Raspberry Pi 4B

We utilized Raspberry Pi 4B to develop a microbial monitoring system to simplify the microbial image-capturing process and facilitate the informatization of microbial observation results.The Raspberry Pi 4B firmware,developed under Python on the Linux platform,achieves sum verification of serial data,file upload based on TCP protocol,control of sequence light source and light valve,real-time self-test based on multithreading,and an experiment-oriented file management method.The system demonstrated improved code logic,scheduling,exception handling,and code readability.

PARS评分法在麻醉恢复室的应用

目的探讨PARS评分法在麻醉恢复室(PACU)中的应用价值。方法将收入PACU的2 562例全麻术后患者分成老年组、中年组和青年组三组,运用PARS评分法分别对患者进行出室和入室评分,同时观察、记录患者在PACU期间的相关生命指征和留室时间。结果老、中、青三组入室时的评分分别为2.1±1.5、3.2±1.6和4.1±1.4,出室时的评分则分别提高至7.3±1.3、8.4±0.8和8.6±0.5,差异有显著意义(t1=6.28,t2=6.16,t3=5.75,P<0.01)。老年组留室时间最长。指标的相关性分析显示,出室评分与入室评分呈显著正相关(r=0.446,P<0.01),与留室时间呈负相关(r=-0.392,P<0.05)。ASA评级分别与入室、出室评分呈显著负相关(r=-0.362,P<0.01和r=-0.413,P<0.01),与留室时间呈正相关(r=0.370,P<0.05)。结论PARS评分法可以定量地判断患者的恢复情况,提高PACU护理工作的预见性,对于指导治疗、保障全麻术后病人的安全具有十分重要的意义,是一种科学、有效的评估方法。

IL-29对胰蛋白酶诱导的肥大细胞PARs表达的调节作用

目的:检测白细胞介素29(Interleukin-29,IL-29)对胰蛋白酶引起的肥大细胞蛋白酶激活受体(Protease activated receptor,PAR)-1,2,3,4表达的调节作用。方法:P815肥大细胞培养后,用不同浓度的IL-29、胰蛋白酶单独或联合激发肥大细胞,在不同时间点收集激发细胞,用流式细胞术(FCM)及实时定量PCR检测P815肥大细胞蛋白酶激活受体的表达。结果:IL-29单独作用能够下调肥大细胞PAR-1蛋白及mRNA水平的表达,上调PAR-3、PAR-4 mRNA的表达,与对照组相比差异有统计学意义(P<0.05);以IL-29预处理肥大细胞后,IL-29对胰蛋白酶诱导的肥大细胞PAR-2、PAR-3、PAR-4表达起促进作用,与对照组相比差异具有统计学意义(P<0.05)。结论:IL-29能够调节胰蛋白酶引起的肥大细胞PARs表达,从而参与肥大细胞相关的炎症反应。

百万千瓦级压水堆严重事故下氢气源项及氢气控制有效性分析

针对百万千瓦级压水堆核电厂大型干式安全壳在严重事故情况下的氢气风险控制,建立了一体化事故分析模型,分别对大破口失水事故(LB-LOCA)、中破口失水事故(MB-LOCA)、小破口失水事故(SB-LOCA)、全厂断电事故(SBO)、蒸汽发生器(SG)传热管破裂事故(SGTR)以及主蒸汽管道破裂事故(MSLB)进行事故进程计算以及氢气源项分析。相对于其他事故序列,LB-LOCA下堆芯快速熔化,锆-水反应产生氢气的速率快,可以作为安全壳内氢气风险控制有效性分析的代表性事故序列。分析表明,严重事故情况下在安全壳中安装一定数量的非能动氢气复合器(PARs)能够有效去除安全壳中的氢气,消除氢气燃烧或爆炸的风险,保持安全壳的完整性。

麻醉恢复评分联合预见性护理在麻醉病人恢复中的应用

[目的]探讨麻醉恢复评分(PARS)联合预见性护理在麻醉病人恢复护理中的应用。[方法]选取麻醉恢复室病人423例,按住院号单双号分为试验组和对照组,对病人入室及出室时进行麻醉恢复评分,试验组依据麻醉恢复评分给予预见性护理及常规护理,对照组仅给予常规护理。比较两组病人麻醉恢复评分、并发症的发生及留室时间的差异,并分析麻醉恢复评分与美国麻醉师协会(ASA)评级及留室时间的相关性。[结果]试验组病人出室时麻醉恢复评分明显高于对照组(P<0.05),并发症的发生及留室时间均低于对照组,麻醉恢复评分入室得分与ASA评级及留室时间均呈负相关。[结论]麻醉恢复评分可以定量地反映病人的生理功能变化,以麻醉恢复评分为基础的预见性护理的实施可减少并发症的发生,缩短病人留室时间。

维持性血透对慢性肾衰患者疗效及血小板受体PARS的影响

目的探讨维持性血透治疗对慢性肾功能衰竭患者疗效及血小板受体PAR_S的影响。方法回顾性分析2010年8月至2013年9月我院住院治疗的慢性肾功能衰竭患者110例,根据干预方法的不同分为治疗组与对照组,各55例。对照组给予常规治疗,治疗组在对照组基础上加用维持性血液透析治疗,每周透析3次,每次4h。两组治疗疗程均1月。结果治疗组有效率(94.5%)高于对照组(78.2%),两组比较差异有统计学意义(P<0.05)。治疗后两组血肌酐、尿素氮、PAR_1和PAR_4值较治疗前均降低,差异有统计学意义(P<0.05),同时组间对比差异有统计学意义(P<0.05)。结论维持性血透治疗能有效改善慢性肾功能衰竭患者的肾功能,提高治疗有效率,同时降低血小板PAR_S受体水平,减低血小板粘附聚集功能,改善凝血功能。