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Intelligent Healthcare Service Provisioning Using Ontology with Low-Level Sensory Data
( Asad Masood Khattak ),( Zeeshan Pervez ),( Sungyoung Lee ),( Young-koo Lee ) 한국인터넷정보학회 2011 KSII Transactions on Internet and Information Syst Vol.5 No.11
Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.
아사드마소드가탁 ( Asad Masood Khattak ),( La The Vinh ),이승룡 ( Sungyoung Lee ),구교호 ( Young-koo Lee ) 한국정보처리학회 2009 한국정보처리학회 학술대회논문집 Vol.16 No.2
To accommodate constantly growing knowledge in scientific discourse that is revised over time by domain experts, we need to also evolve our ontology. The body of knowledge will get structured and refined as we develop a deeper understanding of issues. Keeping trail of new changes in semantically rich and formally sound mechanism has pragmatic advantages for providing the undo and redo facility and ontology recovery to a previous state. In this research, we have proposed a framework that support change logging and then using these logged changes for reverting ontology to a previous consistent state and visualization of change effects on ontology. The system is compared with ChangesTab of Protégé and the results depict better accuracy for our system.
( La The Vinh ),( Asad Masood Khattak ),( Trinh Van Loan ),이승룡 ( Sungyoung Lee ),구교호 ( Young-ko Lee ) 한국정보처리학회 2009 한국정보처리학회 학술대회논문집 Vol.16 No.2
So far, many researches have been conducted in the area of audio based context recognition. Nevertheless, most of them are based on existing feature extraction techniques derived from linear signal processing such as Fourier transform, wavelet transform, linear prediction... Meanwhile, environmental audio signal may potentially contains non-linear dynamic properties. Therefore, it is a big potential to utilize non-linear dynamic signal processing techniques in audio based context recognition.
Object-oriented and ontology-alignment patterns-based expressive Mediation Bridge Ontology (MBO)
Khan, Wajahat Ali,Amin, Muhammad Bilal,Khattak, Asad Masood,Hussain, Maqbool,Afzal, Muhammad,Lee, Sungyoung,Kim, Eun Soo SAGE Publications 2015 JOURNAL OF INFORMATION SCIENCE Vol.41 No.3
<P>The Semantic Web is dependent on extensive knowledge management by interlinking resources on the web using matching techniques. This role is played by the progressing domain of ontology matching, by introducing ontology-matching tools. The focus of these matching tools is limited to matching techniques and automation, rather than expressive formal representation of alignments. We propose Mediation Bridge Ontology (MBO), an expressive alignment representation ontology used to store correspondences between matching ontologies matched by our ontology-matching tool, System for Parallel Heterogeneity Resolution (SPHeRe). The MBO utilizes object-oriented design patterns and the proposed ontology-alignment design patterns to provide extendibility and reusability factors to SPHeRe system. We compared our proposed system with existing systems using Coupling Factor, Number of Polymorphic methods and Rate of Change metrics to support extendibility and reusability. These factors contribute to the overall objective of interoperability for knowledge management in the Semantic Web.</P>
와자하트알리칸 ( Wajahat Ali Khan ),마크불후세인 ( Maqbool Hussain ),아사드마수드카탁 ( Asad Masood Khattak ),이승룡 ( Sungyoung Lee ),구교호 ( Young Koo Lee ) 한국정보처리학회 2011 한국정보처리학회 학술대회논문집 Vol.18 No.1
Due to heterogeneity in Data and Processes, healthcare systems are facing the challenge of interoperability. This heterogeneity results in different healthcare workflows of each individual organization. The compatibility of these heterogeneous workflows is possible when standards are followed. HL7 is one of the standards that is used for communicating medical data between healthcare systems. Its newer version V3 is providing semantic interoperability which is lacking in V2. The interoperability in HL7 V3 is only limited to data level and process level interoperability needs to be catered. The process level interoperability is achieved only when heterogeneous workflows are aligned. These workflows are very complex in nature due to continuous change in medical data resulting in problems related to maintenance and degree of automation. Semantic technologies plays important role in resolving the above mentioned problems. This research work is based on the integration of semantic technology in HL7 V3 standard to achieve semantic process interoperability. Web Service Modeling Framework (WSMF) is used for incorporating semantics in HL7 V3 processes and achieves seamless communication. Interaction Ontology represents the process artifacts of HL7 V3 and helps in achieving automation.