Digital Library[ Search Result ]
OWL-Horst Ontology Inference Engine Using Distributed Table Structure in Cloud Computing Environment
Min-Sung Kim, Min-Ho Lee, Wan-Gon Lee, Young-Tack Park
http://doi.org/10.5626/JOK.2020.47.7.674
Recently, many machine learning methods that extend ontology through data obtained from the web are being studied. As data from the web continues to increase, interest in large-capacity ontology inference methods is also increasing. However, the increasing amount of data decreases processing speeds. This paper describes how to improve the performance of large-scale OWL-Horst inference using distributed table structured data frames to solve the problem of the slow processing speed of large-capacity data. Also, a distributed parallel inference algorithm and optimization method used to improve the inference performance is described. To evaluate the performance of the inference system using the distributed table structured data frame proposed in this paper, experiments were conducted with LUBM1000, LUBM2000, LUBM3000, and LUBM4000. Our reasoning system showed the best performance.
Ontology and CNN-based Inference of the Threat Relationship Between UAVs and Surrounding Objects
MyungJoong Jeon, MinHo Lee, HyunKyu Park, YoungTack Park, Hyung-Sik Yoon, Yun-Geun Kim
http://doi.org/10.5626/JOK.2020.47.4.404
The technology that identifies the relationship between surrounding objects and recognizes the situation is considered as an important and necessary technology in various areas. Numerous methodologies are being studied for this purpose. Most of the studies have solved the problem by building the domain knowledge into ontology for reasoning of situation awareness. However, based on the existing approach; it is difficult to deal with new situations in the absence of domain experts due to the dependency of experts on relevant domain knowledge. In addition, it is difficult to build the knowledge to infer situations that experts have not considered. Therefore, this study proposes a model for using ontology and CNN for reasoning of the relationships between UAVs and surrounding objects to solve the existing problems. Based on the assumption that the accuracy of ontology reasoning is insufficient, first, the reasoning was performed using the information from the detected surrounding objects. Later, the results of ontology reasoning are revised by CNN inference. Due to the limitations of actual data acquisition, data generator was built to generate data similar to real data. For evaluation of this study, two models of relationships between two objects were built and evaluated; both the models showed over 90% accuracy.
An Approach for Recognition of Elderly Living Patterns Based on Event Calculus Using Percept Sequence
Hyun-Kyu Park, Young-Tack Park
http://doi.org/10.5626/JOK.2019.46.11.1149
This paper proposes a method for recognizing the intentions of human activity based on percept sequences that represent the activities of daily living (ADL) in a residential space. Based on the activity intention ontology, which represents actions and poses related to human activity intentions, the proposed method identifies the intention of a human activity by using event calculus when a percept sequence is entered. Based on the action intent identified, frequency and pattern analysis of the action intention is used to characterize the lifestyle patterns of the elderly. The intentions of everyday behavior occurring in an elderly living space are complex, and it is difficult to recognize the pattern of life through these intentions, which makes it difficult to recognize the intention of a complex occurrence. To solve these problems, this paper constructs an ontology of percept sequences expressed as daily behavioral information, and makes inferences to help recognize activity intent based on event calculus. When evaluating the techniques proposed in this paper, the results of the act intention cognition experiment based on the perceptual information recorded showed 84% precision and 85% recall.
An Autonomous Threat Situation Awareness System for UAV based on Ontology
MyungJoong Jeon, HyunKyu Park, YoungTack Park, Hyung-Sik Yoon, Yun-Geun Kim
http://doi.org/10.5626/JOK.2019.46.10.1044
An autonomous threat situational awareness system is necessary for Unmanned Aerial Vehicles(UAVs) in a variety of fields. Although various of approaches to autonomous threat situational awareness have been proposed, most of them involved reasoning of the semantic information of the object. Therefore, in this paper, based on the existing semantic information of an object, we propose a method to achieve threat situational awareness for a UAV based on reasoning of the relationship between the objects. In this paper, there are three main ways that are used to recognize a threat to a UAV: First, information on the recognized objects is expressed using an LOD(Level of Detail)-based grid map. Second, the concepts of objects around the UAV are defined as ontology while the relationships and situations between objects are defined as SWRL(Semantic Web Rule Language). Third, through the ontology reasoning, the simulator visualizes the recognition of the relationships of objects and threat situations for the UAV.
Sports Broadcasting with Deep Learning
http://doi.org/10.5626/JOK.2019.46.10.1020
Sports broadcasting requires understanding and reasoning of a current situation based on information regarding sports scenes, players, and past knowledge. In this paper, we introduced how scene classifier, player detector, motion recognizer could be used to obtain information on sports images and understand current situations. We created three types of commentaries. One was from web data, another was from 13 scenes with scene classifier, and the other was generated by the position of the players, eight motions, and the ontology. Data from the KBO (Korea Baseball Organization League) games from April 1, 2018, to April 14, 2018, were directly labeled to learn the model.
A UAV Situational Awareness Method through the Threat-Related Relation Reasoning between UAV and Surrounding Objects
Seok-Hyun Bae, Myung-Joong Jeon, Hyun-Kyu Park, Young-Tack Park, Hyung-Sik Yoon, Yun-Geun Kim
http://doi.org/10.5626/JOK.2019.46.2.141
As the technological capabilities of UAV(Unmanned Aerial Vehicles) improves, studies are being carried out to intelligently analyze and understand the situation of UAV in order to gain access to the target area while recognizing and avoiding various risks. To achieve the mission of UAV, it is necessary to judge the situation accurately and quickly. To do this, this paper proposes ways to infer the threat-related relationship between an UAV and perceived surrounding objects through a 3 step approach and provide abstract information about the situation of UAV. The first step is to instantiate the object data recognized by UAV to be utilized for ontology and rule-based reasoning. The second step is to define the priority of instantiated object data and to infer the threat-related relationship between them. Finally, recognizing the situation through the relationship inference that takes into account the association between current and past inferred relationships. To evaluation the performance of the proposed method, a virtual UAV environment simulator was built and tested the data 1,000 times that were randomly generated through five sequential UAV moving point paths. Eight kinds of objects could be recognized in UAV path and ten kinds of relationships can be inferred. Overall performance of situation Awareness was an average of 91 percent.
Weather Ontology System in IoT Middleware
Yujin Kim, Soobin Jeon, Inbum Jung
http://doi.org/10.5626/JOK.2019.46.1.97
With the growing importance of weather information, the number of weather information application systems has been increased. Unfortunately, the weather application systems that currently exist neither efficiently store nor manage the vast amount of weather data obtained from various weather sensors. Additionally, they do not utilize the properties contained in the weather data making it difficult to perform intelligent searches using the semantic information present in the weather data. In this paper as a solution to the challenges mentioned, an ontology system for weather information management is constructed using IoT middleware MinT. Based on weather ontology, it is possible to efficiently and easily manage large amounts of weather sensing data by applying ontology in the Internet of Things middleware. Moreover, since inference engine and rule-base information are used, semantic properties are applied to the sensing data collected. The implemented weather ontology uses sensing data and easily provides search results to users through a UI. The usability to search results is selected as the metric for performance evaluation. In the experiments, the proposed weather ontology system exhibited high usability to search results.
Ontology-based Approach to Determine the Conflicts between Security and Usability Requirements in the Requirements Engineering Process
http://doi.org/10.5626/JOK.2018.45.11.1142
Considering the trade-offs or conflicts between security and usability during the requirements engineering (RE) process is a complicated task. This is due to the contrary characteristics of security and usability as well as a lack of research on finding a consensus on the semantics of quality attributes, especially for security and usability. Furthermore, the number of security experts available is decreasing, while a methodology to determine the conflicts between security and usability during the RE process has not yet been developed. We, therefore, propose a novel approach to construct a three-layer ontological knowledge base by linking the keywords from definitions, criteria, and metrics of security and usability. In addition, we discuss the applicability of this knowledge base by examining two case studies with software engineering (SE) students. These case studies show that the participants using the proposed approach (Team A) can derive conflicts that are more precise compared to the participants who did not use the knowledge base (Team B). Moreover, the number of conflicts derived by Team A is half that by Team B. Regardless of the knowledge level, the proposed approach can determine the conflicts between security and usability during the RE process. Also, while practical RE studies have often been considered difficult to handle, the proposed approach can show the applicability of RE research.
Analysis of Case Scenario to Develop a System of Systems Meta-model for Ontology Representation
Young-Min Baek, Sumin Park, Yong-Jun Shin, Doo-Hwan Bae
http://doi.org/10.5626/JOK.2018.45.10.1056
Ontology is a formal and explicit specification technique that defines concepts and relationships of a system. It is utilized to establish a common knowledge base and to reduce mismatches or inconsistencies during communication. Since a System-of-Systems (SoS) is a large-scale complex system that achieves higher-level common goals by the collaboration of constituent systems, ontologies need to be established for overall SoS development and operations. In other words, refined development and communications among various stakeholders of an SoS can be achieved based on the conceptualization power of an ontology. However, in order to build an ontology effectively, SoS engineers require a systematic means to provide a guideline for domain analysis and ontology establishment. To fulfill these requirements, this study proposes a meta-model, called the Meta-model for System-of- Systems (M2SoS), which enables systematic specifications of ontologies for SoS development. M2SoS is developed based on existing studies on meta-modeling approaches in the multi-agent system domain, but M2SoS is improved to meet SoS-specific requirements by SoS case analysis.
Social Engineering based Security Requirements Recommendation Framework to Prevent an Advanced Persistent Threat
http://doi.org/10.5626/JOK.2018.45.10.1015
Advanced Persistent Threat (APT) is a major threat to Socio-Technical System, which constitutes our society. This threat is an attack process rather than a hacking technique, unlike traditional methods of cyberbullying, so it is difficult to detect or defend a wide range of targets for a long period of time using a wide range of exploits. In particular, traditional advanced threats involve technical approaches, such as firewalls, log checks, and packet analysis, in which the first stage of the intelligent, sustained threat analysis involves the ease with which human vulnerabilities are pursued during the early stages of the process. This paper proposes a framework that analyzes the vulnerable social perspective based on the various human factors to prevent advanced persistent threats by using three-layered approach and recommends a security requirement to complement them by using ontology-based approach.
Search
Journal of KIISE
- ISSN : 2383-630X(Print)
- ISSN : 2383-6296(Electronic)
- KCI Accredited Journal
Editorial Office
- Tel. +82-2-588-9240
- Fax. +82-2-521-1352
- E-mail. chwoo@kiise.or.kr