Nhan Le Thanh

Semantic Web Approach to Ease Regulation Compliance Checking in Construction Industry

Regulations in the Building Industry are becoming increasingly complex and involve more than one technical area, covering products, components and project implementations. They also play an important role in ensuring the quality of a building, and to minimize its environmental impact. Control or conformance checking are becoming more complex every day, not only for industrials, but also for organizations charged with assessing the conformity of new products or processes. This paper will detail the approach taken by the CSTB (Centre Scientifique et Technique du Bâtiment) in order to simplify this conformance control task. The approach and the proposed solutions are based on semantic web technologies. For this purpose, we first establish a domain-ontology, which defines the main concepts involved and the relationships, including one based on OWL (Web Ontology Language) [1]. We rely on SBVR (Semantics of Business Vocabulary and Business Rules) [2] and SPARQL (SPARQL Protocol and RDF Query Language) [3] to reformulate the regulatory requirements written in natural language, respectively, in a controlled and formal language. We then structure our control process based on expert practices. Each elementary control step is defined as a SPARQL query and assembled into complex control processes “on demand”, according to the component tested and its semantic definition. Finally, we represent in RDF (Resource Description Framework) [4] the association between the SBVR rules and SPARQL queries representing the same regulatory constraints.

Towards an Algebraic Modeling of Emotional States

In this study, we present a new vision of modeling emotional states. Indeed, the proposed model is different from traditional approaches like ontological representation. It is based on an algebraic representation of emotions. We represent every emotion as a vector in a space of 8 dimensions where every axis represents a basic emotion. This multidimensional model provides to represent infinity of emotion and provides powerful mathematical tools for the analysis and the processing of these emotions. Therefore, our model permits to model not only the basic emotions (e.g., anger, sadness, fear) but also different types of complex emotions like simulated and masked emotions. Moreover, it permits the exchange of emotional states between heterogeneous applications regardless to the modalities and sensors used in the detection step.

Enforcing Access Control to Web Databases

The insider threat against database management systems is a very dangerous and common security problem. Authorized users may compromise database security by abusing legitimate privileges to masquerade as another user or to gather data for malicious purposes. This problem is aggravated for databases made available over the web through web applications since the DBMS recognizes only the database user and ignores end users. It is important for the DBMS to have an idea of who exactly has access to data. Much research on mitigating insider threats focuses on detection. In this paper, we consider the prevention of attacks using access control and we propose (RBAC+), an extension of the NIST RBAC (Role-Based Access Control) standard with the notions of application, application profile and sub-application session. The importance of our solution is that, on the one hand, it enforces access control to the web database, and, on the other hand, it is able to identify malicious activities carried out by legitimate users of the system and prevent insider attacks.

Towards the Knowledge Capitalisation and Organisation in the Model of Conformity-Checking Process in Construction

This paper presents an ontological method aimed at the capitalization of expert knowledge in the context of semi-automatic checking model of the conformity of construction projects against a set of construction norms. The efficiency of our ontology-based reasoning model relies on two keystones. First, it is based on the matching of construction projects represented by RDF graphs to technical conformity queries formalized as SPARQL queries. Second, our reasoning model integrates the meta-knowledge on conformity checking process. Our approach of capitalizing such knowledge is based on the development of semantic annotations of conformity queries and organizing them into a query base. This helps to formalize the expert knowledge in form of expert rules scheduling the matching operations of the checking process. Semantic annotations of conformity queries also help to generate a structured conformity report, which interprets the results of reasoning in terms of conformity checking in construction.

Knowledge capitalisation and organisation for conformance checking model in construction

This paper presents an ontological method aimed at the capitalisation and organisation of conformance-related knowledge for semi-automatic checking model of the conformance of construction projects against a set of conformance requirements. We start by developing a method for knowledge representation of explicit knowledge taking part in checking, and capitalisation of tacit knowledge defining checking practices. Then we explain our approach for classification, organisation and retrieval of conformance requirements and propose an approach for scheduling these requirements to optimise the checking process. Finally, we introduce our reasoning model that is based on matching graph representations of construction projects and conformance queries, and interpret the acquired results in terms of conformance checking in construction. To validate our approach, we describe a prototype illustrating its feasibility, and discuss ongoing works and perspectives of our research.

RBAC+: Dynamic Access Control for RBAC-Administered Web-Based Databases

In a clear contrast with the phenomenal growth of Web database applications, access control issues related to data stored in the back-end databases have largely been neglected. Current approaches to access control on databases do not fit web databases because they are mostly based on individual user identities. In this paper, we propose (RBAC+), a dynamic access control model to enforce fine-grained access control to web databases. It extends the Role-Based Access Control model standard with the notions of application, application profile and sub-application session. The proposed dynamic access control model enhances the ability of detecting malicious transactions, the dominant cause that demolishes database system, by tracking application users throughout a whole session. Hence, attacks caused by malicious transactions can be detected and canceled timely before they succeed.

Adaptation of the Domain Ontology for Different User Profiles: Application to Conformity Checking in Construction

This paper presents a method for the adaptation of domain ontologies to different contexts and user profiles. It is applied to the modeling of conformity checking in construction. Considering a method we have developed to acquire and represent the expert knowledge involved in the conformity checking process, we highlight the need to reduce the gap between the expert knowledge primary captured in the domain ontology and the end user knowledge. We propose a method to contextualize the ontological knowledge initially acquired and to adapt it to different user profiles.

Modeling ORM Schemas in Description Logics

In recent years, there has been a growing interest in integration of semantics into the Semantic Web environment, whose goal is to access, relate and combine information from multiple sources. With regard to this tendency, our work studies a mechanism to model ORM schemas in the Description Logic language SHOINK (D), the underpinning of a Web ontology language. This mechanism meets the key feature required by ORM schemas (i.e. identification and functional dependency constraints). It can be applied to integrate information not only from systems described in ORM schemas but also from relational databases into the Semantic Web environment.

Emotion recognition using KNN classification for user modeling and sharing of affect states

In this study, we propose a new method of recognizing emotional states from physiological signals. Our proposal uses signal processing techniques to analyze physiological signals. It permits to recognize not only the basic emotions (e.g., anger, sadness, fear) but also any kind of complex emotion, including simultaneous superposed or masked emotions. This method consists of two main steps: the training step and the detection step. In the First step, our algorithm extracts the features of emotion from the data to generate an emotion training data base. Then in the second step, we apply the k-nearest-neighbor classifier to assign the predefined classes to instances in the test set. The final result is defined as an eight components vector representing emotion in multidimensional space. Experiments show the efficiency of the proposed method in detecting basic emotion by giving hight recognition rate.

An ontological approach for modeling technical standards for compliance checking

This paper gives an overview of a formal semantic-based approach of modeling some regulations in the photovoltaic field to help the delivering of technical assessments at the French scientific center on Building Industry (CSTB). Starting from regulatory texts, we first explicit SBVR rules and then formalize them into ontology-based rules in the SPARQL language. These are exploited in the modeling of the compliance checking process required for the delivering of technical assessments.