Description Logic Research Articles

Extending the description logic [formula omitted] with threshold concepts induced by concept measures

In applications of AI systems where exact definitions of the important notions of the application domain are hard to come by, the use of traditional logic-based knowledge representation languages such as Description Logics may lead to very large and unintuitive definitions, and high complexity of reasoning. To overcome this problem, we define new concept constructors that allow us to define concepts in an approximate way. To be more precise, we present a family τEL(m) of extensions of the lightweight Description Logic EL that use threshold constructors for this purpose. To define the semantics of these constructors we employ graded membership functions m, which for each individual in an interpretation and concept yield a number in the interval [0,1] expressing the degree to which the individual belongs to the concept in the interpretation. Threshold concepts C⋈t for ⋈∈{<,≤,>,≥} then collect all the individuals that belong to C with degree ⋈t. The logic τEL(m) extends EL with threshold concepts whose semantics is defined relative to a function m. To construct appropriate graded membership functions, we show how concept measures ∼ (which are graded generalizations of subsumption or equivalence between concepts) can be used to define graded membership functions m∼. Then we introduce a large class of concept measures, called simi-d, for which the logics τEL(m∼) have good algorithmic properties. Basically, we show that reasoning in τEL(m∼) is NP/coNP-complete without TBox, PSpace-complete w.r.t. acyclic TBoxes, and ExpTime-complete w.r.t. general TBoxes. The exception is the instance problem, which is already PSpace-complete without TBox w.r.t. combined complexity. While the upper bounds hold for all elements of simi-d, we could prove some of the hardness results only for a subclass of simi-d. This article considerably improves on and generalizes results we have shown in three previous conference papers and it provides detailed proofs of all our results.

Living without Beth and Craig: Definitions and Interpolants in Description and Modal Logics with Nominals and Role Inclusions

The Craig interpolation property (CIP) states that an interpolant for an implication exists iff it is valid. The projective Beth definability property (PBDP) states that an explicit definition exists iff a formula stating implicit definability is valid. Thus, the CIP and PBDP reduce potentially hard existence problems to entailment in the underlying logic. Description (and modal) logics with nominals and/or role inclusions do not enjoy the CIP nor the PBDP, but interpolants and explicit definitions have many applications, in particular in concept learning, ontology engineering, and ontology-based data management. In this article, we show that, even without Beth and Craig, the existence of interpolants and explicit definitions is decidable in description logics with nominals and/or role inclusions such as 𝒜ℒ𝒞𝒪, 𝒜ℒ𝒞ℋ, and 𝒜ℒ𝒞ℋ𝒪ℐ and corresponding hybrid modal logics. However, living without Beth and Craig makes these problems harder than entailment: the existence problems become 2ExpTime -complete in the presence of an ontology or the universal modality, and coNExpTime -complete otherwise. We also analyze explicit definition existence if all symbols (except the one that is defined) are admitted in the definition. In this case, the complexity depends on whether one considers individual or concept names. Finally, we consider the problem of computing interpolants and explicit definitions if they exist and turn the complexity upper bound proof into an algorithm computing them, at least for description logics with role inclusions.

Postulate satisfaction for inconsistency measures in monotonic logics and databases

Inconsistency measures for propositional logic have been investigated in great detail for the past 20 years. Many such measures have been proposed. Rationality postulates, conditions about inconsistency measures, were defined to distinguish the measures that satisfy intuitively desirable properties. The satisfaction or violation of various postulates is known for many inconsistency measures. But propositional logic has many limitations and in many applications more complex logics are appropriate. We consider monotonic extensions of propositional logic such as modal, temporal, description, and first-order logic. We focus on a class of inconsistency measures whose computation depends only on the structure of the minimal inconsistent subsets. The definition of these inconsistency measures is the same for these logics as for propositional logic. The situation is similar for the rationality postulates. This paper studies the connection between the satisfaction or violation of the postulates for propositional logic and monotonic extensions of propositional logic. We show that the results are the same for the most prominent postulates. Additionally, we consider the same question for databases. We show that although the setting is substantially different from these logics, in general the results are the same.

Ontology-Based Food Menu Recommender System for Patients with Coronary Heart Disease

Coronary heart disease is one of the leading causes of death. Knowledge of dietary patterns and proper food selection is an effort to address the risk and support coronary heart disease's healing process. Therefore, this study developed a food menu recommender system as a reference for patients with coronary heart disease. The recommender system is crucial in creating a proper dietary pattern for managing personalized meal plans. The system calculates the required nutritional needs of users. Ontology is used to represent knowledge about nutrition data and food intake. The ontology base with Semantic Web Rule Language (SWRL) enables the system to identify the most suitable foods for patients with coronary heart disease. We use SWRL rules to generate recommendation conclusions based on the existing ontology. Using this language enhances the descriptive logic capabilities, as the rules can overcome the limitations of the ontology language. Therefore, the system is built to find food menu options that match the required nutrition for patients. The nutritionist knowledge will be used to measure the system's performance compared to the recommendations made by nutritionists. From the user data sample, 150 recommended food menu data were obtained. The validation performance results obtained a precision 0.893, recall 1, and F_Score 94.3%.

Contributive Effect of Land Management Indicators to Farmers Farmland Conservation in Oyo State, Nigeria

Major problem facing tropical agriculture is the inherent low fertility status of most of the soils because of the predominant low-activity. The study explained the contributive effect of sustainable land management indicators to land use on farmers’ productivity in Oyo State Nigeria. A two-stage sampling technique was employed in selecting 330 farmers from the four agricultural zones in Oyo State. Structured questionnaire was used to obtain primary data. The data collected were analysed using descriptive and Fuzzy logic analysis (Fuzzy set theory). The result revealed that the result of Fuzzy Logic which was used to compute the composite indicators of unsustainable land use (IULU) showed that the total IULU of 0.26 obtained indicated that farmers’ land management practices in the study area are generally sustainable. Residue cover, land fallowing, compaction and rooting, salinity and crop rotations among others have the highest relative contributions of 3.2%, 3.2%, 3.2%, 3.2% and 3.2% respectively to land farmers land conservation, while other indicators contribute lower percentage to land conservation been unsustainable in the study with relative contributions of 2.1%, 2.3%, 2.3%, 2.0, 2.5% and 2.4% respectively also majority of the farmer (60%) are sustainable and contributed larger percentage (96.4%) to sustainability and had between 0.1-0.2 with minimum of 0.00004 and maximum of 0.95650 sustainable land index in the study. The study recommended among others that cultural practices for erosion prevention should be encouraged by planting of cover crops and planting of trees and other agronomic best practices which enhance soil conservation and improve more on their level of sustainable land use indicators. Keywords: Sustainable, Land, Conservation, Indicators, Aggregation, Fuzzy, Nigeria

PERLINDUNGAN HUKUM DALAM PENYELESAIAN SENGKETA PELANGGARAN TERHADAP DANA NASABAH DI PASAR MODAL

This research aims to analyze the form of legal protection for customers who suffer losses due to fraudulent funds in the capital market, the role and efforts of the Financial Services Authority in protecting customers in the capital market, and how Sharia economic law reviews in resolving disputes in the capital market.This type of research is normative legal research through a juridical approach which is carried out by examining various legal rules such as in Laws and Regulations No. 8 of 1995 concerning Capital Markets in Chapter X I concerning fraud, market manipulation and insider trading, as well as cases related to the capital market, namely the case of PT Sarijaya Permana Sekuritas. Related to dispute resolution in Islamic law explained in the Al-Quran surah Saad verse 26 Data collection techniques using Library Research techniques (literature study), namely a data collection technique that collects legal materials obtained from various sources such as books, journals, and online written media related to the object of discussion. The data analysis technique used is qualitative data analysis technique, namely analyzing data by collecting data, presenting data and drawing conclusions, then the data is arranged in descriptive form by describing the data that has been obtained in the form of logical sentence descriptions, then interpreted and given conclusions.The results of this study indicate that: First, legal protection of customers who suffer losses due to violations committed by securities companies can apply the return of unauthorized profits by the OJK to the Securities Company to provide loss compensation funds to customers. Second, based on Law Number 21 of 2011 OJK has a role in forming regulations for improvements in the field of capital markets including protecting customers as consumers. Third, dispute resolution in Islam can be through peace mechanisms (such), arbitration (tahkim), and courts (Al- qada).

Towards human-compatible XAI: Explaining data differentials with concept induction over background knowledge

Concept induction, which is based on formal logical reasoning over description logics, has been used in ontology engineering in order to create ontology (TBox) axioms from the base data (ABox) graph. In this paper, we show that it can also be used to explain data differentials, for example in the context of Explainable AI (XAI), and we show that it can in fact be done in a way that is meaningful to a human observer. Our approach utilizes a large class hierarchy, curated from the Wikipedia category hierarchy, as background knowledge. To make the explanations easily understandable for non-specialists, the complex description logic explanations generated by our concept induction system (ECII) were presented as a word list consisting of the concept names occurring in the highest rated system responses.

Enhancing learning and exploratory search with concept semantics in online healthcare knowledge management systems: An interactive knowledge visualization approach

Healthcare is a knowledge intensive process, which requires large amount of information from various healthcare knowledge providers. However, this growing information makes challengeable for users in finding useful healthcare information to support their healthcare decision making. Knowledge management and knowledge management systems are drawing increasing attention in healthcare community. This paper proposes an online healthcare knowledge management framework and system prototype, featured with integrating knowledge learning and exploratory search for solving problems efficiently. Inspired by the knowledge to action framework in healthcare and the iterative process in software engineering, an iterative and incremental knowledge management model is designed to organize the activities during the knowledge learning and searching procedure. Supported by the knowledge-enhanced infrastructure of online healthcare information designed, domain knowledge learning and task knowledge learning environment can work collaboratively and interactively to improve the result of learning and exploratory search. Knowledge base also provides helpful information in an interactive way for solving problems. Given exploiting probabilistic information retrieval model and concept semantics described in Description Logics, a search intent discovery method and search intent guided learning and searching mechanism are designed within this environment for achieving the learning and search goal. The results of the experiments have proved the efficacy of the methods and process model used in the leaning-focused healthcare knowledge management system.

Fuzzy ontology-based approach for liver fibrosis diagnosis

The domain of the digestive system is prone to severe chronic disease in the form of liver cirrhosis, which is currently a leading cause of mortality. This article presents a new intelligent system for predicting the severity of liver fibrosis in patients with chronic viral hepatitis C. The proposed system is based on the inference capabilities of fuzzy ontology and operates on semantic rule-based techniques. A fuzzy decision tree technique was employed to generate the ontology rule base using a dataset of real fibrosis cases from the Mansoura University Hospital, Egypt. These rules were then encoded into a set of fuzzy semantic rules using the fuzzy description logic format. To evaluate the system’s effectiveness, the proposed ontology was then tested on 47 chronic HCV cases, with an attempt made to see if this correctly diagnosed the patients’ conditions. The performance of the proposed system was compared with that of the now-standard Mamdani fuzzy inference system; while the latter achieved an accuracy of 95.7/%, the proposed fuzzy ontology-based system demonstrated higher performance, with 97.8% accuracy. Furthermore, the proposed system also supports semantic interoperability between clinical decision support systems and electronic health record ecosystems. The positive impacts of this system on the correct prediction of liver fibrosis severity thus suggest that it has the potential to assist medical professionals in diagnosing and treating this dangerous disease.

Deploying OWL ontologies for semantic mediation of mixed-reality interactions for human–robot collaborative assembly

For effective human–robot collaborative assembly, it is paramount to view both robots and humans as autonomous entities in that they can communicate, undertake different roles, and not be bound to pre-planned routines and task sequences. However, with very few exceptions, most of recent research assumes static pre-defined roles during collaboration with centralised architectures devoid of runtime communication that can influence task responsibility and execution. Furthermore, from an information system standpoint, they lack the self-organisation needed to cope with today’s manufacturing landscape that is characterised by product variants. Therefore, this study presents collaborative agents for manufacturing ontology (CAMO), which is an information model based on description logic that maintains a self-organising team network between collaborating human–robot multi-agent system (MAS). CAMO is implemented using the Web Ontology Language (OWL). It models popular notions of net systems and represents the agent, manufacturing, and interaction contexts that accommodate generalisability to different assemblies and agent capabilities. As a novel element, a dynamic consensus-driven collaboration based on parametric validation of semantic representations of agent capabilities via runtime dynamic communication is presented. CAMO is instantiated as agent beliefs in a framework that benefits from real-time dynamic communication with the assembly design environment and incorporates a mixed-reality environment for use by the operator. The employment of web technologies to project scalable notions of intentions via mixed reality is discussed for its novelty from a technology standpoint and as an intention projection mechanism. A case study with a real diesel engine assembly provides appreciable results and demonstrates the feasibility of CAMO and the framework.

A knowledge-based system for supporting the soundness of digital forensic investigations

Performing a technically and legally sound digital forensic investigation leads to digital evidence that can be used in courts of law. However, there is no single model of a standardized procedure that investigators should abide by. This paper presents a knowledge-based system that formally specifies information about investigative procedures in accordance with standards and guidelines such as ISO/IEC 27037, ISO/IEC 27041, ISO/IEC 27042, ISO/IEC 27043, NIST’s Guide to Integrating Forensic Techniques into Incident Response and Interpol’s Guidelines for Digital Forensics First Responders. The knowledge base is created in a description logic and it represents an ontological model. The model unifies concepts from different standards and guidelines, thus enabling the system to aid investigators in executing investigative procedures that will result in admissible digital evidence. The paper uses network forensics as a case study, but it can be customized to other digital forensics domains.

Fuzzy Minimax Nets

We introduce fuzzy minimax nets as a novel tool to compute the greatest fuzzy bisimulation/simulation between two finite fuzzy labeled graphs. Fuzzy labeled graphs are a universal data structure for representing fuzzy systems such as fuzzy automata, fuzzy labeled transition systems, fuzzy Kripke models, fuzzy social networks and fuzzy interpretations in description logic. The greatest fuzzy bisimulation between two such systems characterizes the similarity between their states, actors or individuals. Using fuzzy minimax nets, we design the first algorithms for the mentioned computational problems in the case of using the product t-norm, as well as the first algorithms whose complexity order does not depend on the fuzzy values occurring in the inputs for those problems in the case of using the Łukasiewicz t-norm.

Flap/slat control lever signal algorithm based on potentiometer for civil aircraft

A design of flap/slat control lever signal calculation based on a potentiometer for civil aircraft is proposed. The design applies to the dual redundancy FSECU (Flaps Slat Electronic Control Unit) architecture. A range monitoring algorithm is first proposed to confirm the validity of the FSCL (Flap/Slat Control Lever). The value of a single potentiometer is used for one-channel FSCL detent calculation. To solve the difference in FSCL signals among channels, an algorithm for FSCL signal monitoring and voting is proposed. The core of this algorithm is presented by logical description and the flow diagram. The design is verified by modeling and simulation in the Simulink environment. The results are in line with expectations, which can provide a reference for the design of the FSCL signal algorithm.

Hemimetric-based λ-valued fuzzy rough sets

A λ-subset, or a [0,λ]-valued fuzzy subset, is a mapping from a nonempty set to the interval [0,λ]. In this paper, we use the notion of hemimetrics, a kind of distance functions, as the basic structure to define and study fuzzy rough set model of λ-subsets by using the usual addition and subtraction of real numbers. We define a pair of fuzzy upper/lower approximation operators and investigate their properties and interrelations. These two operators have nice logical descriptions by using the related Lukasiewicz logical systems. We show that upper definable sets, lower definable sets and definable sets are equivalent, and they form an Alexandrov fuzzy topology. A processing of a λ-subset via fuzzy upper/lower approximation operators can actually considered as a processing of the related image, and thus has potential applications in image processing.

Climbing the Ladder in Crafting A Professionalism Framework for Nursing Students in South Africa

Introduction: Globally, higher education institutions are faced with training nursing students to meet the healthcare demands of an ever-changing society. In nursing education, innovative ways are essential to instil professionalism among nursing students to prepare them for managing complex practice issues without compromising the professional standards of nursing. This paper concentrates on developing a conceptual framework, for the facilitation of professionalism among undergraduate nursing students at a higher education institution in South Africa.&#x0D; Methods: This study was a constructive paradigm research with qualitative descriptive approach. Data was collected by focus group interviews with participants (three cases). Different phases were followed in the framework development using the case method. In Case 1, focus groups (n=8) were held with student nurses from each of the levels of a four-year degree program (n=42). In Case 2, focus groups (n=3) and unstructured interviews (n=1) were conducted with purposively selected nurse educators (n=20), representing academics and clinical facilitators. Case 3 comprised of semi-structured individual interviews (n=5) and focus groups (n=5), a total of 29 preceptors in professional practice. An analysis of a within-case followed by cross-case data analysis, resulted in merged themes of three cases that emerged as an overall case study.&#x0D; Results: Actual accounts of the participants` experiences on nursing professionalism during theory and practice education were captured in the six concepts of the Practice Orientated Theory that structured the developed framework.&#x0D; Conclusion: A logical methodological description of creating a framework on nursing professionalism was outlined and the conceptual framework can be evaluated for transferability to other similar nursing education training environments.

Ontology-based detection and identification of complex event of illegal parking using SPARQL and description logic queries

Dynamic monitoring and management of traffic is a significant challenge which requires a mobile surveillance system which is becoming feasible with the evolution of 5G and related technologies. With the advent of 5G, huge amount of data can be transferred over long distance. Furthermore, the evolution of Multi-access Edge Computing (MEC) offers the processing near the edge, resulting in quick response which can cater to mobile surveillance. The mobile surveillance can be performed through a vehicle (Unmanned Aerial Vehicle (UAV)/mobile vehicle) which collects the multi-modal data and sends to nearest edge server over the 5G network. The server sends response quickly to the control center from where the appropriate action can be taken to mitigate its effect on the individuals in real-time. Furthermore, the analysis of multi-modal data captured by surveillance systems must be integrated and efficiently represented. Therefore, in this work, an ontology-based approach is proposed by integrating unstructured video data and structured sensor data for detecting and identifying the complex event of illegal parking. Identifying illegally parked vehicles needs dynamic and strict monitoring; which require the deployment of surveillance systems across the entire city. However, installing a video camera at each place is not feasible. Therefore, the surveillance thorough mobile vehicle is presented to identify illegal parked vehicle for traffic management over the 5G network. In addition, an ontology is developed to represent and reason over the roadside video data while integrating it with sensor data to form a knowledge graph. The knowledge graph retrieves semantic information about the events using SPARQL queries and Description Logics (DL) queries. Thus, a complete video is not required and the extracted information is stored in Resource Description Framework (RDF) format to reduce space requirement significantly. The approach is evaluated by recognizing the complex events of detecting illegally parked vehicles on a real-time dataset recorded using the experimental setup. Furthermore, the framework represents the surveillance video data of parked vehicles captured using the camera installed in a mobile vehicle to cover the road, including the vehicle information location, position, time, etc., as a knowledge graph that can be used later for further analysis.

An ontology design for validating childhood cancer registry data.

Ontologies can provide a valuable role in the work of cancer registration, particularly as a tool for managing and navigating the various classification systems and coding rules. Further advantages accrue from the ability to formalise the coding rule base using description logics and thereby benefit from the associated automatic reasoning functionality. Drawing from earlier work that showed the viability of applying ontologies in the data validation tasks of cancer registries, an ontology was created using a modular approach to handle the specific checks for childhood cancers. The ontology was able to handle successfully the various inter-variable checks using the axiomatic constructs of the web ontology language. Application of an ontological approach for data validation can greatly simplify the maintenance of the coding rules and facilitate the federation of any centralised validation process to the local level. It also provides an improved means of visualising the rule interdependencies from different perspectives. Performance of the automatic reasoning process can be a limiting issue for very large datasets and will be a focus for future work. Results are provided showing how the ontology is able to validate cancer case records typical for childhood tumours.

Development of Web-Oriented Systems: Ontological Approach

The purpose of the article is to study, analyze the possibilities and substantiate the creation of a web-oriented system of a catering establishment (pizzeria) based on the ontological approach, as well as to develop the corresponding software. Achieving the aim of the study involves the following tasks: forming a multi-level ontological model of the subject area (catering establishment – pizzeria) and developing an appropriate web-oriented system on its basis. The research methods are the main methodological approaches and technological tools for web-based systems development based on the use of an appropriate multi-level ontological model. Such methods include, in particular, systemic and comparative analyses (to identify the features of web-oriented systems of catering establishments) and the expert evaluation method (in determining the objects of the subject area and the relations between them). The scientific novelty is the study and analysis of modern technologies for the development of web-oriented systems and multi-level ontological modelling of various subject areas, including catering establishments (e.g., pizzerias), the results of which can be used in the development of their software product – a web-oriented system of a catering establishment. Conclusions. The paper investigates the known views on the modern approach to the development of web-oriented systems based on the implementation of the ontological approach. The proposed ontological model of a catering establishment (pizzeria) is described as a formal specification of knowledge about the selected subject area, its objects and the relationship between them (for a clear and complete representation of the subject area), which plays a significant role at different stages of creating and modifying a web-oriented system. The proposed ontological approach, which involves the development of an appropriate multi-level ontological model, has been used in the design of a web-based system for a restaurant (pizzeria). The use of an ontological model in the development of a web-based system of a catering establishment (pizzeria) helps to reduce the risk of errors in the structure of the system, the component and elemental composition of the system and its information base; more accurate perception of the subject area (catering establishments specializing in different cuisines of the peoples of the world (for example, Ukrainian, Japanese, American, but preferring Italian); use in the model representation of the subject area not only formalized means (formal grammar, descriptive logic, etc.) but also natural languages; making more precise queries to the system’s information base (database and the corresponding knowledge base).

Using Conceptual Graph modeling and inference to support the assessment and monitoring of bridge structural health

Effective bridge maintenance requires sufficient and accurate knowledge on structural health. However, despite the development of structural health monitoring (SHM) and inspection aids, bridge structural health monitoring remains challenging. This work proposes a comprehensive predictive description based on Conceptual Graphs (CG), of the bridge condition deterioration mechanism, with the formalization of the inspection history. The model combines formalized​ assumptions with several deterioration factors and expert knowledge to assess the evolution of the structural condition. The model is based on logical and graphical descriptions of the deterioration of the structural condition thanks to the use of the CG modeling. Through the graphical inference, the evolution of the apparent condition and the deterioration time can be assessed. The application to two bridge cases highlights the interest of this approach to help understanding the sequence of deterioration. The actual condition obtained and the formalized inspection history allow a better decision.

Autonomica: Ontological Modeling and Analysis of Autonomous Behavior

AbstractModel‐based system autonomy is a complex integration of planning from high‐level goals to low‐level command sequences whose execution controls a system. The need for autonomy has accelerated in recent years to enable complex missions in automotive, space, and defense. During system development, understanding the relationship between system autonomy and the physical environment (including hardware) is critical to supporting trade studies, developing concepts of operations, characterizing risk, and performing testing. This paper describes the initial results of developing Autonomica, an ontology‐based methodology and a framework for autonomous behavior modeling and analysis. This methodology formalizes an architectural pattern for specifying model‐based autonomy as a vocabulary with description logic semantics and provides authoring and analysis capabilities (reasoning, querying, and simulation) for the architectures. The framework implements the methodology in an integrated workbench. A running example of a hypothetical spacecraft mission to a small space body illustrates the ideas.