Semantic Description Research Articles

Integrating geological data in Europe to foster multidisciplinary research

The European Plate Observing System (EPOS, www.epos-eu.org) is a multidisciplinary pan-European research infrastructure for solid Earth science. It integrates a series of domain-specific service hubs (Thematic Core Service, TCS) such as the Geological Information and Modelling, which provides access to data, data products and services on European boreholes, geological maps, mineral occurrences, mines and 3D models. TCS GIM services are hosted by a group of European Geological Surveys and a couple of national research organizations. This paper presents novel data discovery and integration, facilitated using borehole logging information with on-demand web services to produce 3D geological structures. This domain interoperability across EPOS was created for the purpose of research, but it is also highly relevant for the response to societal grand challenges such as natural hazards and climate change. European and international interoperability implementation frameworks are well described and used (e.g., INSPIRE, ISO, OGC, and IUGS/CGI). It can be difficult for data providers to deploy web services that support the full semantic data definition (e.g., OGC Complex Feature) to expose several millions of geological entities through web-enabled data portals as required by pan-European projects. The TCS GIM group implemented and innovatively extended two standardized descriptions, i.e. GeoSciML-Lite and EarthResourceML-Lite, with an important reuse of content from Linked Data Registries. This approach was applied to design and implement the European Borehole Index and associated web services (View-WMS and Discovery-WFS), extended to 3D models, geological maps as well as mineral occurrences and mines. Results presented here apply the Linked Data approach ensuring optimal semantic description and enriching the data graphs, with complex descriptions and contents. In this way, it is now possible to traverse from one Borehole Index instance to linked richer information such as the borehole geological log, groundwater levels, rock sample description, analyses, etc. All this detailed information is served following international interoperability standards (Observations & Measurements, GroundWaterML 2.0, GeoSciML4, amongst others).

ОСМИ ФОРУМ „БЪЛГАРСКА ГРАМАТИКА“ / EIGHT FORUM ON BULGARIAN GRAMMAR

The Eighth Forum on Bulgarian Grammar titled Predication, Predicates, Predicatives was held on 21 and 22 October 2021. The Forum was organised by the Institute for Bulgarian Language Prof. Lyubomir Andreychin at the Bulgarian Academy of Sciences and the Department of Bulgarian Language of the Faculty of Slavic Studies at Sofia University St. Kliment Ohridski. The forum was dedicated to the 90th anniversary of one of the most renowned Bulgarian linguists of our time – Prof. DSc Yordan Penchev Penchev. The Forum’s topic encompassed a broad range of theoretical and applied issues related to the lexical peculiarities, the semantic description and the classification of (selected classes of) predicates and predicatives, the description of grammatical categories involved in the realisation of predication, the study of the syntactic patterns of argument expression and the identification of relevant semantic and grammatical features. The main focus of the discussion was centred around (though not limited to) the following issues: • Lexical and semantic characterisation of various classes of predicates and predicatives • Approaches to the description of valency and argument selection • The expression of predication at the morphological level • Semantic and syntactic structure of sentences with predicates and predicatives • Description of semantic and grammatical constraints on subject, complement and adjunct realisation. Following the established tradition, the papers presented at the Forum are published in Balgarski ezik’s Supplement.

Analysis of one lexicographic case: the Russian noun svist ‘whistle’

The subject of the article is the application of the case study method to the description of lexical semantics, in particular, to the analysis of a dictionary entry. The author considers the Russian noun SVIST ‘whistle’ as an object, namely, its description in the “Dictionary of the Russian language” (1984). Semantic analysis shows that the description of the word polysemy in the dictionary does not correspond to the nature of the semantic representations that are assigned to this lexeme. The author offers his own version of the semantic description of this noun, in particular, using the category of image-schematic structure. Special attention is devoted to the problem of the dictionary presentation of syntactic representations, i.e. combinatory of the word.

Russell versus Donnellan on Descriptions

The paper argues that Donnellan’s distinction between the referential and attributive uses of definite descriptions, whilst a genuine feature of language, does not count against Russell’s Theory of Descriptions where Russell’s theory is regarded as a theory of the semantics of descriptions and not the pragmatics of individual uses on a particular occasion. The argument I shall present is simple but decisive and ought to resolve once and for all the debate about the significance of Donnellan’s distinction for Russell’s theory, provided of course that Russell’s theory really does concern the semantics of definite descriptions rather than their use on particular occasions.

Research on the semantic web representation for building operation with Variable Refrigerant Flow systems

Building metadata is regarded as the signpost in organizing massive building data. The application of building metadata simplifies the creation of digital representations and provides portable data analytics. Typical metadata standards such as Brick and Haystack are used to describe the data of the building system. However, neither Haystack nor Brick has provided definitions of the Variable Refrigerant Flow system so far. With the growing market for the Variable Refrigerant Flow, it is needed to have semantic descriptions of Variable Refrigerant Flow systems in metadata standards for data analysis and management. Addressing this challenge, this paper developed and verified the semantic descriptions of the Variable Refrigerant Flow system in Brick Schema. With the semantic representation, a building data management framework including a backend and a frontend has also been developed. Then, the model and the service framework are tested in an office building. Results indicated using the semantic model and the service framework reduces manpower and data analysis time. This paper provides a possible solution for the expression of the Variable Refrigerant Flow systems in the building semantic web. The works in this paper will support the semantic web in automation strategies for building management and scalable building operation.

Semantic maps of causation: New hybrid approaches based on corpora and grammar descriptions

AbstractThe present paper discusses connectivity and proximity maps of causative constructions and combines them with different types of typological data. In the first case study, I show how one can create a connectivity map based on a parallel corpus. This allows us to solve many problems, such as incomplete descriptions, inconsistent terminology and the problem of determining the semantic nodes. The second part focuses on proximity maps based on Multidimensional Scaling and compares the most important semantic distinctions, which are inferred from a parallel corpus of film subtitles and from grammar descriptions. The results suggest that corpus-based maps of tokens are more sensitive to cultural and genre-related differences in the prominence of specific causation scenarios than maps based on constructional types, which are described in reference grammars. The grammar-based maps also reveal a less clear structure, which can be due to incomplete semantic descriptions in grammars. Therefore, each approach has its shortcomings, which researchers need to be aware of.

Russell Versus Donnellan on Descriptions

The paper argues that Donnellan's distinction between the referential and attributive uses of definite descriptions, whilst a genuine feature of language, does not count against Russell's Theory of Descriptions where Russell's theory is regarded as a theory of the semantics of descriptions and not the pragmatics of individual uses on a particular occasion. The argument I shall present is simple but decisive and ought to resolve once and for all the debate about the significance of Donnellan's distinction for Russell's theory, provided of course that Russell's theory really does concern the semantics of definite descriptions rather than their use on particular occasions.

IFC2INDOORGML: AN OPEN-SOURCE TOOL FOR GENERATING INDOORGML FROM IFC

Abstract. The interest in 3D indoor models has been continuously growing. Most such models are made available as point clouds or BIM (e.g., IFC), the former being generally provided as unstructured information while the latter comes highly structured and rich in semantic information. IFC models are consequently more suitable for direct use, but they can be very complex and contain too many details, which often raises privacy concerns. IndoorGML is one of the standards for describing 3D indoor space with the purpose of supporting Location Based Services (LBS). It relies on solid scientific concepts and offers a high flexibility with extension mechanisms. It provides a geometric, topological, and semantic description of the indoor which facilitates specifically applications like indoor navigation or facility management. Additionally, it can represent complex indoor environments without compromising privacy, thanks to its high level of abstraction. However, despite its solid conceptual basis, IndoorGML is suffering from a lack of practical tools and remains hard to produce, making it largely unavailable. In this project, we developed an open-source tool named ifc2indoorgml allowing to automatically generate IndoorGML models from IFC data. We discuss the workflow and the different development approaches. By making such tool available to the wider public, we expect more 3D IndoorGML models to be created and made freely available for research and development within the spatial community and beyond.

Інтеграція та композиція сервісів на основі моделі

In the paper we would like to introduce a frame- work for designing and developing Semantic Web Service application that integrates a several enterprises and composes results from a different services by applying techniques, methodologies and notations provided by Software Engineering and Business process modeling. We propose to use existing business modeling techniques (BPMN, BPLWS, OWL-S, WSDL, WebML) for modeling the cross enterprise processes, for enterprise integrations and web service compositions. The main purpose is to designing and developing semantically rich Web applications, with semiautomatic defining semantic descriptions from the business process model that increase the efficiency of design and decrease the extra work necessary for processing semantically annotated information which passing through the enterprises.

TwinNet: Twin Structured Knowledge Transfer Network for Weakly Supervised Action Localization

Action recognition and localization in untrimmed videos is important for many applications and have attracted a lot of attention. Since full supervision with frame-level annotation places an overwhelming burden on manual labeling effort, learning with weak video-level supervision becomes a potential solution. In this paper, we propose a novel weakly supervised framework to recognize actions and locate the corresponding frames in untrimmed videos simultaneously. Considering that there are abundant trimmed videos publicly available and well-segmented with semantic descriptions, the instructive knowledge learned on trimmed videos can be fully leveraged to analyze untrimmed videos. We present an effective knowledge transfer strategy based on inter-class semantic relevance. We also take advantage of the self-attention mechanism to obtain a compact video representation, such that the influence of background frames can be effectively eliminated. A learning architecture is designed with twin networks for trimmed and untrimmed videos, to facilitate transferable self-attentive representation learning. Extensive experiments are conducted on three untrimmed benchmark datasets (i.e., THUMOS14, ActivityNet1.3, and MEXaction2), and the experimental results clearly corroborate the efficacy of our method. It is especially encouraging to see that the proposed weakly supervised method even achieves comparable results to some fully supervised methods.

A formal analysis method for composition protocol based on model checking

Protocol security in a composition protocol environment has always been an open problem in the field of formal analysis and verification of security protocols. As a well-known tool to analyze and verify the logical consistency of concurrent systems, SPIN (Simple Promela Interpreter) has been widely used in the analysis and verification of the security of a single protocol. There is no special research on the verification of protocol security in a composition protocol environment. To solve this problem, firstly, a formal analysis method for composition protocol based on SPIN is proposed, and a formal description of protocol operation semantics is given. Then the attacker model is formalized, and a message specification method based on field detection and component recognition is presented to alleviate the state explosion problem. Finally, the NSB protocol and the NSL protocol are used as examples for compositional analysis. It is demonstrated that the proposed method can effectively verify the security of the protocol in a composition protocol environment and enhance the efficiency of composition protocol verification.

CHARACTERISTICS COGNITION OF TYPICAL SURFACE GEOHAZARDS SCENE IN MINING AREAS AND REPRESENTATION OF GEO-INFOGRAPHICS SPECTRUM

Abstract. The concept of surface geohazards in mining area is put forward, and the surface geohazards in mining area are divided into three categories: first is surface subsidence fissures, collapse, second is instability of structures, slope deformation hazards (high and steep slopes, landslides and collapses) , debris flows (debris flows, tailings reservoir dam break), third is vegetation cover degradation and environmental and ecological damage in mining area. Author analyses the research status of spatio-temporal characteristics of surface geohazards in mining areas and the representation of geo-infographics Spectrum. Characteristics of typical surface geohazards scene in mining areas can be recognized using multi-resource spatial data, adopting abstract generalization, visualization and analysis of the various features and phenomena from four aspects: geographical environment, geological environment, engineering activity and geohazards. The field presentations of spatial morphological structure and geo-environmental conditions and spatio-temporal process in surface geohazards characteristic area are summarized as data fields, which express the shape, structure, location and distribution of geohazard bodies, action and physical fields which is all fields affected the data field and the coupled field which is scalar or vector field formed by the coupling of two or more fields. By using spatial location, semantic description, attribute characteristics, geometric shape, evolution process and the information of the relationship between features, taking into account the characteristics of object structure, distribution and coupling, the geohazard infographics spectrum is constructed and characterize the multi-field geo-infographics spectrum of surface geohazards in mining areas. It is a composite analysis method of time and space. A preliminary example of geo-infographics spectrum is given.

Scene-graph-driven semantic feature matching for monocular digestive endoscopy

Background and objectiveRegistration of the preoperative 3D model with the video of the digestive tract is the key task in endoscopy surgical navigation. Accurate 3D reconstruction of soft tissue surfaces is essential to complete registration. However, existing feature matching methods still fall short of desirable performance, due to the soft tissue deformation and smooth but less-textured surface. MethodsIn this paper, we present a new semantic description based on the scene graph to integrate contour features and SIFT features. Firstly, we construct the semantic feature descriptor using the SIFT features and dense points in the contour regions to obtain more dense point feature matching. Secondly, we design a clustering algorithm based on the proposed semantic feature descriptor. Finally, we apply the semantic description to the structure from motion (SfM) reconstruction framework. ResultsOur techniques are validated by the phantom tests and real surgery videos. We compare our approaches with other typical methods in contour extraction, feature matching, and SfM reconstruction. On average, the feature matching accuracy reaches 75.6% and improves 16.6% in pose estimation. In addition, 39.8% of sparse points are increased in SfM results, and 35.31% more valid points are obtained for the DenseDescriptorNet training in 3D reconstruction. ConclusionsThe new semantic feature description has the potential to reveal more accurate and dense feature correspondence and provides local semantic information in feature matching. Our experiments on the clinical dataset demonstrate the effectiveness and robustness of the novel approach.

TagSeq: Malicious behavior discovery using dynamic analysis.

In recent years, studies on malware analysis have noticeably increased in the cybersecurity community. Most recent studies concentrate on malware classification and detection or malicious patterns identification, but as to malware activity, it still relies heavily on manual analysis for high-level semantic descriptions. We develop a sequence-to-sequence (seq2seq) neural network, called TagSeq, to investigate a sequence of Windows API calls recorded from malware execution, and produce tags to label their malicious behavior. We propose embedding modules to transform Windows API function parameters, registry, filenames, and URLs into low-dimension vectors, while still preserving the closeness property. Moreover, we utilize an attention mechanism to capture the relations between generated tags and certain API invocation calls. Results show that the most possible malicious actions are identified by TagSeq. Examples and a case study demonstrate that the proposed embedding modules preserve semantic-physical relations and that the predicted tags reflect malicious intentions. We believe this work is suitable as a tool to help security analysts recognize malicious behavior and intent with easy-to-understand tags.

Towards a new semantic middleware for service description, discovery, selection, and composition in the Internet of Things

AbstractThe emergence of the Internet of Things (IoT) allows the integration of everyday devices such as tags, sensors, and actuators into the Internet. IoT also provides handy and automatic techniques to interoperate ad‐hoc, heterogeneous, and mobile networks and simplify data sharing among devices by abstracting their capabilities as services. Nevertheless, the large number and heterogeneity of encompassed networks/devices and the diversity of the offered resources/services make the IoT service description, discovery, selection, and composition a challenging task. To deal with these issues, we introduce, in this article, a semantic middleware for IoT applications based on service composition. Such a solution supports the semantic description of IoT resources, including services and user requests, and provides a modular, end‐to‐end, and loosely coupled request resolution process that comprises a context‐aware service discovery, a semantic service selection, and an automatic lightweight service composition. The proposal is illustrated and extensively evaluated on a restricted smart‐city scenario. Obtained results show that the proposed service discovery, selection, and composition sub‐processes improve the scalability of equivalent state‐of‐the‐art solutions by around 15, 20, and 40, respectively.

Pseudo-Reduplication in Lukisa Dialect

Reduplication is a grammatical aspect found in a wide range of African languages and it is sometimes interchangeably used with repetition. Reduplication is both a morphological and a phonological process of forming a compound word by repeating all or part of the word. Morphological reduplication involves semantic change through another word formation process while phonological reduplication is where the copying pics the closest phonological input restricted to cases of phonological necessity. Lukisa, a Luhya dialect is expected to exhibit a range of patterns in reduplication which varies from a single segment being copied to an entire phrase. Although linguistic forms of reduplication have been explored at lexical and functional levels, there is need to validate morphological doubling involving the creation of new stem type reduplication as a limitless linguistic resource, a central meaning making strategy and a naturally integrated facility in language. Therefore, the objective of this study is to establish how pseudo reduplication manifests in Lukisa reduplication. Inkelas and Zoll (2005) Morphological Doubling Theory was adopted for this study where morphology calls twice for a constituent of a given semantic description with possible phonological modification of either or both constituents. MDT is a native identity theory in the sense that the surface phonological identity between the two copies occurs as a side effect of semantic identity.

Clustering- and Transformer-Based Networks for the Style Analysis of Logo Images.

In the design field, designers need to investigate and collect logo materials before designing logos and search a large number of design materials on well-known logo websites to find logos with similar styles as reference images. However, manual work is time-consuming and labor-intensive. To solve this problem, we propose a clustering method that uses K-Means clustering and visual transformer model to group the styles of the logo database. Specifically, we use the visual transformer model as a feature extractor to convert logo images into feature vectors and perform K-Means clustering, use the clustering results as pseudo-labels to further train the feature extractor, and continue to iterate the above process to finally obtain reliable clustering results. We validate our approach by creating the logo image dataset JN Logo, a proposed database for image quality and style attributes, containing 14922 logo design images. Our proposed deep transformer-based cluster (DTCluster) automatic style grouping method is used in JN Logo; the DBI reaches 0.904, and the DI reaches 0.189, which are better than those of other K-Means clustering methods and other clustering algorithms. We perform a subjective analysis of five features of the clustering results to obtain a semantic description of the clusters. Finally, we provide six styles and five semantic descriptions for the logo database.

Data Analysis Deep Learning Research on Spatiotemporal Preposition Construction Network

Chinese space-time prepositions (CSTPs) are a class of function words used to introduce space-time relations into motion or state, which have experienced the process of evolution from ancient Chinese. In recent years, the research on modern CTSPs shows the trend of grammaticalization research, cognitive semantic research, and research based on constructionalization and lexicalization. At present, there are few studies on the systematic semantic description of CTSPs in cognitive linguistics, and their semantic extension is closely related to the cognitive mechanism. This study is aimed at describing and explaining the functions of CSTPs in constructional networks, aiming to provide clearer semantic information for nonnative language learners. This is a comprehensive study combining qualitative and quantitative analysis. Qualitative analysis includes exploration of cognitive mechanisms, description of semantic networks, misinterpretation, and establishment of lexicographically definition model. Quantitative analysis includes data analysis of the Chinese corpus. The importance of qualitative analysis is far greater than that of quantitative analysis. It does not mean that quantitative analysis is not important. Quantitative analysis is important, and qualitative analysis is relatively more important.

Question answering system for chemistry—A semantic agent extension

This paper introduces an extension of a previously developed question answering (QA) system for chemistry, operating on a knowledge graph (KG) called Marie. This extension enables the automatic invocation of semantic agents to answer questions when static data is absent from the KG. The agents are semantically described using the agent ontology, OntoAgent, to enable automated agent discovery and invocation.The natural language processing (NLP) models of the QA system need to be trained in order to interpret questions to be answered by new agents. For this purpose, we extend OntoAgent so that it becomes possible to automatically create training material for the NLP models.We evaluate the extended QA system with two example chemistry-related agents and an evaluation question set. The evaluation result shows that the extension allows the QA system to discover the suitable agent and to invoke the agent by automatically constructing requests from the semantic agent description, thereby increasing the range of questions the QA system can answer.

A catalogue with semantic annotations makes multilabel datasets FAIR

Multilabel classification (MLC) is a machine learning task where the goal is to learn to label an example with multiple labels simultaneously. It receives increasing interest from the machine learning community, as evidenced by the increasing number of papers and methods that appear in the literature. Hence, ensuring proper, correct, robust, and trustworthy benchmarking is of utmost importance for the further development of the field. We believe that this can be achieved by adhering to the recently emerged data management standards, such as the FAIR (Findable, Accessible, Interoperable, and Reusable) and TRUST (Transparency, Responsibility, User focus, Sustainability, and Technology) principles. We introduce an ontology-based online catalogue of MLC datasets originating from various application domains following these principles. The catalogue extensively describes many MLC datasets with comprehensible meta-features, MLC-specific semantic descriptions, and different data provenance information. The MLC data catalogue is available at: http://semantichub.ijs.si/MLCdatasets.