Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people everywhere.Due to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the spine.The semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar diseases.It is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation accuracy.This work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra S1.Pseudo-colour mask images were generated and used as ground truth for training the model.The work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley Data.The proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

FusionNN:A Semantic Feature Fusion Model Based on Multimodal for Web Anomaly Detection

With the rapid development of the mobile communication and the Internet,the previous web anomaly detectionand identificationmodels were built relying on security experts’empirical knowledge and attack features.Althoughthis approach can achieve higher detection performance,it requires huge human labor and resources to maintainthe feature library.In contrast,semantic feature engineering can dynamically discover new semantic featuresand optimize feature selection by automatically analyzing the semantic information contained in the data itself,thus reducing dependence on prior knowledge.However,current semantic features still have the problem ofsemantic expression singularity,as they are extracted from a single semantic mode such as word segmentation,character segmentation,or arbitrary semantic feature extraction.This paper extracts features of web requestsfrom dual semantic granularity,and proposes a semantic feature fusion method to solve the above problems.Themethod first preprocesses web requests,and extracts word-level and character-level semantic features of URLs viaconvolutional neural network(CNN),respectively.By constructing three loss functions to reduce losses betweenfeatures,labels and categories.Experiments on the HTTP CSIC 2010,Malicious URLs and HttpParams datasetsverify the proposedmethod.Results show that compared withmachine learning,deep learningmethods and BERTmodel,the proposed method has better detection performance.And it achieved the best detection rate of 99.16%in the dataset HttpParams.

Description logics for fuzzy ontologies on semantic web

To enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web, a new fuzzy extension of description logics called the fuzzy description logics with comparison expressions （FCDLs） is presented. The syntax and semantics of FCDLs are formally defined, and the forms of axioms and assertions in FCDLs knowledge bases are specified. FCDLs combine both fuzzy concepts from the fuzzy description logics （FDLs） and cut concepts from the extended fuzzy description logics （EFDLs） in the same theory. Furthermore, cut concepts are extended into comparison cut concepts in FCDLs to represent comparison expressions between fuzzy membership degrees, which are often used in practice but not supported by the other fuzzy extensions of description logics. FCDLs have more expressive power than FDLs and EFDLs, and are able to represent expressive fuzzy knowledge and to perform reasoning tasks based on them. Therefore, FCDLs can enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web.

基于Semantic Web的个性化网络导航机制

缺乏信息空间的合理组织和有效的导航机制是网络中"迷航"现象的主要原因.本文将Semantic Web技术应用于网络导航中,利用概念化语义模型对信息内容进行形式化的描述,整合分布式异构信息源,在此基础上映射和建立了用户语义模型,从而构建了个性化、智能化的网络导航机制.

Ontology and metadata for online learning resource repository management based on semantic web

An ontology and metadata for online learning resource repository management is constructed. First, based on the analysis of the use-case diagram, the upper ontology is illustrated which includes resource library ontology and user ontology, and evaluated from its function and implementation; then the corresponding class diagram, resource description framework （RDF） schema and extensible markup language （XML） schema are given. Secondly, the metadata for online learning resource repository management is proposed based on the Dublin Core Metadata Initiative and the IEEE Learning Technologies Standards Committee Learning Object Metadata Working Group. Finally, the inference instance is shown, which proves the validity of ontology and metadata in online learning resource repository management.

Semantic Web研究综述

近年来 ,SemanticWeb逐渐成为WWW领域的研究热点以及智能化网络服务和应用开发中的关键技术之一。归纳了Se manticWeb技术的研究背景和主要发展历史。在分析了典型的SemanticWeb概念后 ,给出了SemanticWeb的定义。通过讨论SemanticWeb构想的层次框架模型 ,指出了各个层次扮演的角色 ,并着重分析了SemanticWeb的重要研究领域 ,指出了它们在SemanticWeb构架中的核心作用。通过分析SemanticWeb的应用领域和相关开发工具以及面临的问题和挑战 ,指明了SemanticWeb研究和实践的方向。作为总结 ,给出了SemanticWeb领域下一步的研究趋势。

Novel method for searching ontologies on semantic web

In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval （SIR） model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.

Capability matchmaking of semantic web services with preconditions and effects

In order to solve the problem that the current matchmaking methods for semantic web service mainly focus on the matchmaking of IO （inputs, outputs） descriptions which may result in one-sidedness, a description-logic-based IOPE （inputs, outputs, preconditions, effects） description and matchmaking method is proposed for semantic web service. The description logic concept is used to annotate service IO and the description logic assertion is employed to describe service PE（preconditions, effects）. TBox subsumption checking is used to measure the subsumption relationship between IO descriptions of service request and advertising; ABox consistency checking is used for checking the logical implication between PE descriptions of service request and advertising. Based upon the logical implication, four kinds of PE matching degrees are proposed to measure and compare the pros and cons of the results of matchmaking. They are the exact, perfect, side-effect and common match. Experiments show that the method has a higher precision rate under the same recall rate compared with the existing method.

Reducing semantic bias of annotations for semantic web service discovery

In order to improve the effectiveness of semantic web service discovery, the semantic bias between an interface parameter and an annotation is reduced by extracting semantic restrictions for the annotation from the description context and generating refined semantic annotations, and then the semantics of the web service is refined. These restrictions are dynamically extracted from the parsing tree of the description text, with the guide of the restriction template extracted from the ontology definition. New semantic annotations are then generated by combining the original concept with the restrictions and represented via refined concept expressions. In addition, a novel semantic similarity measure for refined concept expressions is proposed for semantic web service discovery. Experimental results show that the matchmaker based on this method can improve the average precision of discovery and exhibit low computational complexity. Reducing the semantic bias by utilizing restriction information of annotations can refine the semantics of the web service and improve the discovery effectiveness.

Semantic Web与基于语义的网络信息检索

本文描述网络环境语义检索的需求 ,分析SemanticWeb的组成框架 ,探讨概念集 (ontologies)及其定义和标记语言 ,并介绍基于概念集的信息资源语义标注和语义推理基本过程。

New method for query answering in semantic web

To promote the efficiency of knowledge base retrieval based on description logic, the concept of assertional graph （AG）, which is directed labeled graph, is defined and a new AG-based retrieval method is put forward. This method converts the knowledge base and query clause into knowledge AG and query AG by making use of the given rules and then makes use of graph traversal to carry out knowledge base retrieval. The experiment indicates that the efficiency of this method exceeds, respectively, the popular RACER and KAON2 system by 0.4% and 3.3%. This method can obviously promote the efficiency of knowledge base retrieval.

Configuration knowledge modeling of customizable products based on semantic web technologies

In order to solve the problem of modeling product configuration knowledge at the semantic level to successfully implement the mass customization strategy, an approach of ontology-based configuration knowledge modeling, combining semantic web technologies, was proposed. A general configuration ontology was developed to provide a common concept structure for modeling configuration knowledge and rules of specific product domains. The OWL web ontology language and semantic web rule language （SWRL） were used to formally represent the configuration ontology, domain configuration knowledge and rules to enhance the consistency, maintainability and reusability of all the configuration knowledge. The configuration knowledge modeling of a customizable personal computer family shows that the approach can provide explicit, computerunderstandable knowledge semantics for specific product configuration domains and can efficiently support automatic configuration tasks of complex products.

Supporting web services reuse by semantic service component and composition pattern

Due to the fact that the existing web service description methods cannot address the issue of service reuse of various levels of granularity, the concept of service component is introduced, which packages together web services and choreography, and their operations and properties are presented in a consistent and uniform manner. Service components are published externally as normal web services and can thus be employed by webbased applications. In order to improve reusability and testability of service components, the concept of composition pattern is also proposed, which presents the relationships among service components. The relationships and relationship compositions have a rigorous semantic, so that composite components can be validated at the configuration stage. The composition patterns support to integrate service components of various levels of granularity. Experience indicates that the application assembly can effectively be conducted by understanding, selecting, and reusing components easily.

Semantic Web、Agent和网络虚拟社会

This paper tries to discuss one realizable mode of SW(Semantic Web). It is called NVS(Network-Virtual Society). SW is regarded as the next-generation Web. By adding semantics into Web,SW provides interoperability between applications and facilities to enable automated processing of Web resources. Agent will be the executer in the automated process. After analyzing relational theories and technologies, we put forward the concept and mode of NVS,and gives our reason.

Task-oriented web service discovery algorithm using semantic similarity for adaptive service composition

In order to achieve adaptive and efficient service composition, a task-oriented algorithm for discovering services is proposed. The traditional process of service composition is divided into semantic discovery and functional matching and makes tasks be operation objects. Semantic similarity is used to discover services matching a specific task and then generate a corresponding task-oriented web service composition （TWC） graph. Moreover, an algorithm for the new service is designed to update the TWC. The approach is applied to the composition model, in which the TWC is searched to obtain an optimal path and the final service composition is output. Also, the model can implement realtime updating with changing environments. Experimental results demonstrate the feasibility and effectiveness of the algorithm and indicate that the maximum searching radius can be set to 2 to achieve an equilibrium point of quality and quantity.

Web services selection based on semantic similarity

Services discovery based on syntactic matching cannot adapt to the open and dynamic environment of the web. To select the proper one from the web services candidate set provided by syntactic matching, a service selection method based on semantic similarity is proposed. First, this method defines a web services ontology including QoS and context as semantic supporting, which also provides a set of terms to describe the interfaces of web services. Secondly, the similarity degree of two web services is evaluated by computing the semantic distances of those terms used to describe interfaces. Compared with existing methods, interfaces of web services can be interpreted under ontology, because it provides a formal and semantic specification of conceptualization. Meanwhile, efficiency and accuracy of services selection are improved.

信息服务的趋势:Semantic WEB

Web 发展造成了“信息爆炸”和“知识贫乏”的矛盾,基于 XML 和 RDF 发展的语义网是解决这一问题的关键。变“机器可读”为“机器可理解”是语义网的目标,信息服务可以应用语义网的模式和成果,提高搜索的准确率,提供高相关度的个性化服务,构建全新的数字图书馆门户。

Efficient semantic web service matching using common ontology

To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain partition and allocate system resources automatically.The characteristics of this mechanism are analyzed,including scalability,self-organization and adaptability.In this mechanism,semantic web service discovery is separated into two parts.First,under balance tree topology,registry proxy can rapidly forward requests to the objective registry center,and avoid the bottleneck problem.Secondly,a semantic distance based service matching algorithm is proposed to promote the effect of service searching.The results of simulation experiments show that the proposed mechanism can serve as a scalable solution for semantic web service publication and discovery.And the improved matching algorithm has higher recall and precision than other algorithms.

Semantic web-based networked manufacturing knowledge retrieval system

To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of tools for supporting the sharing of knowledge and promoting NM collaboration. A 5-tuple based semantic information retrieval model is proposed, which includes the interoperation on the semantic layer, and a test process is given for this model. The recall ratio and the precision ratio of manufacturing knowledge retrieval are proved to be greatly improved by evaluation. Thus, a practical and reliable approach based on the semantic web is provided for solving the correlated concrete problems in regional networked manufacturing.

Web services composition based on global semantics and QoS-aware aspect

A global semantics matching and QoS-awareness service selection are proposed when aimed at a web services composition process.Both QoS-aware matching and global semantic matching are considered during the global matching.When there are demands for global semantic matching and QoS of service composition,a concrete service set which meets the demands is selected for the whole service composition process and an optimal solution is also achieved.A QoS model is built and the corresponding evaluation method is given for the matching of the service composition process.Based on them,a genetic algorithm is proposed to achieve the maximal global semantic matching degree and fulfill the QoS requirements for the whole service composition process.Experimental results and analysis show that the algorithm is feasible and effective for semantics and QoS-aware service matching.