Using ontology and rules to retrieve the semantics of disaster remote sensing data

Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing data.To improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and disasters.The prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.

Enhancing Deep Learning Semantics:The Diffusion Sampling and Label-Driven Co-Attention Approach

The advent of self-attention mechanisms within Transformer models has significantly propelled the advancement of deep learning algorithms,yielding outstanding achievements across diverse domains.Nonetheless,self-attention mechanisms falter when applied to datasets with intricate semantic content and extensive dependency structures.In response,this paper introduces a Diffusion Sampling and Label-Driven Co-attention Neural Network(DSLD),which adopts a diffusion sampling method to capture more comprehensive semantic information of the data.Additionally,themodel leverages the joint correlation information of labels and data to introduce the computation of text representation,correcting semantic representationbiases in thedata,andincreasing the accuracyof semantic representation.Ultimately,the model computes the corresponding classification results by synthesizing these rich data semantic representations.Experiments on seven benchmark datasets show that our proposed model achieves competitive results compared to state-of-the-art methods.

A Natural Language Generation Algorithm for Greek by Using Hole Semantics and a Systemic Grammatical Formalism

This work is about the progress of previous related work based on an experiment to improve the intelligence of robotic systems,with the aim of achieving more linguistic communication capabilities between humans and robots.In this paper,the authors attempt an algorithmic approach to natural language generation through hole semantics and by applying the OMAS-III computational model as a grammatical formalism.In the original work,a technical language is used,while in the later works,this has been replaced by a limited Greek natural language dictionary.This particular effort was made to give the evolving system the ability to ask questions,as well as the authors developed an initial dialogue system using these techniques.The results show that the use of these techniques the authors apply can give us a more sophisticated dialogue system in the future.

Real-time collaborative design based on operation semantics in distributed CAD environment

This paper proposes a collaborative design model based on operation semantics in a distributed computer-aided design (CAD) environment. The goal is to reduce time consumption in data format conversion and the requirement of network bandwidth so as to improve the cooperative ability and the synchronization efficiency. Firstly, real-time collaborative design is reviewed and three kinds of real-time collaborative design models are discussed. Secondly, the concept of operation semantics is defined and the framework of an operation semantics model is presented. The operation semantics carries the original design data and actual operation process to express design intent and operation activity in conventional CAD systems. Finally, according to the operation semantics model, a CAD operation primitive is defined which can be retrieved from and mapped to the local CAD system operation commands; a distributed CAD collaborative architecture based on the model is presented, and an example is given to verify the model.

利奇Semantics“语义类型”术语群的汉译——兼谈Leech语义分类的逻辑

利奇(Geoffrey Leech)的《语义学》(Semantics)关于语义类型的术语形成一个"术语群",学界关于该术语群给出的汉语翻译分歧较大,在综合考量已有翻译和研究成果的基础上,结合Leech语义分类的逻辑,笔者倾向于译为:理性意义(Conceptual Meaning)、内涵意义(Connotative Meaning)、搭配意义(Collocative Meaning)、情感意义(Affective Meaning)、社会意义(Social Meaning)、反应意义(Reflected Meaning)、主位意义(Thematic Meaning)。"语义类型"术语群的汉译存在一定分歧有文本内外原因。

Universal Semantics in Translation

What and how we translate are questions often argued about. No matter what kind of answers one may give, priority in translation should be granted to meaning, especially those meanings that exist in all concerned languages. This research defines them as universal sememes, and the study of them as universal semantics, of which applications are also briefly looked into.

A Contrastive Study on Folk Custom Semantics of Chinese and English Words of Plants and Animals

This paper attempts to make a comparison of folk custom semantics on Chinese and English words of plants and animals.

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.

Spatio-temporal GIS Data Model Based on Event Semantics

There are mainly four kinds of models to record and deal with historical information. By taking them as reference, the spatio-temporal model based on event semantics is proposed. In this model, according to the way for describing an event, all the information are divided into five domains. This paper describes the model by using the land parcel change in the cadastral information system, and expounds the model by using five tables corresponding to the five domains. With the aid of this model, seven examples are given on historical query, trace back and recurrence. This model can be implemented either in the extended relational database or in the object-oriented database.

Marine spatio-temporal process semantics and its applications-taking the El Nio Southern Oscilation process and Chinese rainfall anomaly as an example

Spatio-temporal semantics based on ＂object views＂ or ＂event views＂ has few abilities to represent and model the continuity and gradual oceanic phenomena or objects, which seriously limits the specific marine applications and knowledge discovery and data mining, so this paper proposes a hierarchical abstraction semantics with ＂marine spatio-temporal process-life span phases-evolution sequences--state units＂ and process objects included by level with ＂marine process objects--phase objects--sequence object---state objects＂ with the oceanic process characteristics into the marine process semantics. In addition, this paper designs the storage and representation of marine process objects using the backus normal forms （BNF） and abstract data type （ADT）. Base on E1 Nifio Southern Oscilation （ENSO） index and Chinese rain gauging station data, this paper also gives a case of study. The spatio-temporal analysis between ENSO process and Chinese rainfall anomalies shows that the marine spatio-temporal semantics not only can illustrate the spatial distribution of Chinese rainfall anomalies in different time scales at ENSO process, life span phases and state units, but also analyze the dynamic changes of Chinese rainfall anomalies in different life span phases or state units within ENSO evolution.

ST-SIGMA:Spatio-temporal semantics and interaction graph aggregation for multi-agent perception and trajectory forecasting

Scene perception and trajectory forecasting are two fundamental challenges that are crucial to a safe and reliable autonomous driving(AD)system.However,most proposed methods aim at addressing one of the two challenges mentioned above with a single model.To tackle this dilemma,this paper proposes spatio-temporal semantics and interaction graph aggregation for multi-agent perception and trajectory forecasting(STSIGMA),an efficient end-to-end method to jointly and accurately perceive the AD environment and forecast the trajectories of the surrounding traffic agents within a unified framework.ST-SIGMA adopts a trident encoder-decoder architecture to learn scene semantics and agent interaction information on bird’s-eye view(BEV)maps simultaneously.Specifically,an iterative aggregation network is first employed as the scene semantic encoder(SSE)to learn diverse scene information.To preserve dynamic interactions of traffic agents,ST-SIGMA further exploits a spatio-temporal graph network as the graph interaction encoder.Meanwhile,a simple yet efficient feature fusion method to fuse semantic and interaction features into a unified feature space as the input to a novel hierarchical aggregation decoder for downstream prediction tasks is designed.Extensive experiments on the nuScenes data set have demonstrated that the proposed ST-SIGMA achieves significant improvements compared to the state-of-theart(SOTA)methods in terms of scene perception and trajectory forecasting,respectively.Therefore,the proposed approach outperforms SOTA in terms of model generalisation and robustness and is therefore more feasible for deployment in realworld AD scenarios.

Annotation and Retrieval System of CAD Models Based on Functional Semantics

CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs（AAG） is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System（FSMARS）, is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.

Location and Its Semantics in Location-Based Services

Starting with a simple presentation of location determination techniques, physical location and geographic location as two common kinds of location description methods are discussed. The semantic location concept is then introduced and a correction is given, which especially emphasizes that location property is an important part of semantic location. By analyzing the connotation and extension of every geographic location, what should be contained in a location property is determined. Using a hierarchical model, the relations and associations among locations are clearly described. To realize a formalized description of semantic location, an ontology technique that can adequately describe semantic information of location is used. Organized by ontology web language, a location ontology model allows semantic location to be read and processed by computer. The location ontology model realizes the knowledge description of location information and establishes an important foundation to personalized preference services in location based services.

Improving Chinese Word Representation with Conceptual Semantics

The meaning of a word includes a conceptual meaning and a distributive meaning.Word embedding based on distribution suffers from insufficient conceptual semantic representation caused by data sparsity,especially for low-frequency words.In knowledge bases,manually annotated semantic knowledge is stable and the essential attributes of words are accurately denoted.In this paper,we propose a Conceptual Semantics Enhanced Word Representation(CEWR)model,computing the synset embedding and hypernym embedding of Chinese words based on the Tongyici Cilin thesaurus,and aggregating it with distributed word representation to have both distributed information and the conceptual meaning encoded in the representation of words.We evaluate the CEWR model on two tasks:word similarity computation and short text classification.The Spearman correlation between model results and human judgement are improved to 64.71%,81.84%,and 85.16%on Wordsim297,MC30,and RG65,respectively.Moreover,CEWR improves the F1 score by 3%in the short text classification task.The experimental results show that CEWR can represent words in a more informative approach than distributed word embedding.This proves that conceptual semantics,especially hypernymous information,is a good complement to distributed word representation.

Semantics Analytics of Origin-Destination Flows from Crowd Sensed Big Data

Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used to mine the semantics of OD flows.In this paper,we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China.The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows.Then based on a novel complex network model,a semantics mining method of OD flows is proposed through compounding Points of Interests(POI)network and public transport network to the OD flows network.The propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.

The Formal Semantics of an UML Activity Diagram

Due to lack of strictly defined formal semantics, an UML activity diagram is unsuitable for the tasks of formal analysis, verification and assertion on the system it describes. In this paper, Petri net is used to define the formal semantics of an UML activity diagram containing object flow states, laying a foundation for the precise description and analysis of a workflow system.

Approximate Failures Semantics for Polynomial Labelled Transition Systems

Labelled transition systems(LTSs) are widely used to formally describe system behaviour.The labels of LTS are extended to offer a more satisfactory description of behaviour by refining the abstract labels into multivariate polynomials.These labels can be simplified by numerous numerical approximation methods.Those LTSs that can not apply failures semantics equivalence in description and verification may have a chance after using approximation on labels.The technique that combines approximation and failures semantics equivalence effectively alleviates the computational complexity and minimizes LTS.

Formal Semantics of OWL-S with Rewrite Logic

SOA is built upon and evolving from older concepts of distributed computing and modular programming, OWL-S plays a key role in describing behaviors of web services, which are the essential of the SOA software. Although OWL-S has given semantics to concepts by ontology technology, it gives no semantics to control-flow and data-flow. This paper presents a formal semantics framework for OWL-S sub-set, including its abstraction, syntax, static and dynamic seman-tics by rewrite logic. Details of a consistent transformation from OWL-S SOS of control-flow to corresponding rules and equations, and dataflow semantics including “Precondition”, “Result” and “Binding” etc. are explained. This paper provides a possibility for formal verification and reliability evaluation of software based on SOA.

The “Prototype and Stereotype” Theory in Lexical Semantics Teaching Methodology

Cognitive linguistics studies the relationship between language and cognition,which claims that semantics structures reflect the mental categories which people have formed their experiences of growing up and acting in the world.The lexical and semantics combined together to be the foundations of language which makes into people' s communication.As the main branch of cognition,the prototype and stereotype theory have a close relationship to the lexical semantics.Thus,it is essential and useful to make a research on the lexical semantics under the influence of the "prototype and stereotype theory" and it will help a lot in teaching methodology.

On The Distinction between Semantics and Pragmatics

The close relationship between semantics and pragmatics has made it difficult to set a clear boundary between them.Dicussion of the relationship can date back to Morris, whose semiotic trichotomy was taken up by Carnap. Leech, Levinson, Bach and Huang also tried to make a distinction between the two, but no consensus has been reached.