Profiles
David Herbert
UTAS Home Mr David Herbert
David Herbert
PhD Candidate
Information & Communication Technology
Room 454 , Centenary Building
+61 3 6226 7278 (phone)
View more on Mr David Herbert in WARP
Fields of Research
- Knowledge representation and reasoning (460206)
- Computing education (460804)
- Distributed systems and algorithms (460605)
- Information security management (460904)
- Health informatics and information systems (420308)
- Machine learning (461199)
- Data management and data science (460599)
- Human information interaction and retrieval (461003)
- Intelligent robotics (460205)
Research Objectives
- Information systems, technologies and services (220499)
- Application software packages (220401)
- Assessment, development and evaluation of curriculum (160301)
- Artificial intelligence (220403)
Publications
Total publications
7
Journal Article
(4 outputs)| Year | Citation | Altmetrics |
|---|---|---|
| 2021 | Ryu R, Yeom S, Kim S-H, Herbert D, 'Continuous multimodal biometric authentication schemes: A systematic review', IEEE Access, 9 pp. 34541-34557. ISSN 2169-3536 (2021) [Refereed Article] DOI: 10.1109/ACCESS.2021.3061589 [eCite] [Details] Co-authors: Ryu R; Yeom S | |
| 2019 | Yang W, Aghasian E, Garg K, Herbert D, Disiuta L, et al., 'A survey on blockchain-based internet service architecture: requirements, challenges, trends and future', IEEE Access, 7 pp. 75845-75872. ISSN 2169-3536 (2019) [Refereed Article] DOI: 10.1109/ACCESS.2019.2917562 [eCite] [Details] Citations: Scopus - 21Web of Science - 15 Co-authors: Yang W; Aghasian E; Garg K; Kang B | |
| 2019 | Yang W, Herbert D, Kim S, Kang B, 'MCRDR knowledge-based 3D dialogue simulation in clinical training and assessment', Journal of Medical Systems, 43 Article 200. ISSN 0148-5598 (2019) [Refereed Article] DOI: 10.1007/s10916-019-1262-0 [eCite] [Details] Co-authors: Yang W; Kim S; Kang B | |
| 2018 | Herbert D, Kang BH, 'Intelligent conversation system using multiple classification ripple down rules and conversational context', Expert Systems With Applications, 112 pp. 342-352. ISSN 0957-4174 (2018) [Refereed Article] DOI: 10.1016/j.eswa.2018.06.049 [eCite] [Details] Citations: Scopus - 12Web of Science - 5 Co-authors: Kang BH |
Conference Publication
(3 outputs)| Year | Citation | Altmetrics |
|---|---|---|
| 2019 | Herbert D, Kang B, 'Comparative analysis of intelligent personal agent performance', Lecture Notes in Computer Science, 26-27 August 2019, Cuvu, Fiji, pp. 127-141. ISBN 9783030306380 (2019) [Refereed Conference Paper] DOI: 10.1007/978-3-030-30639-7_11 [eCite] [Details] Citations: Scopus - 1 Co-authors: Kang B | |
| 2018 | Herbert N, Herbert D, 'Is the ATAR a Useful Predictor of Success in ICT? An Empirical Study', Proceedings of the 20th Australasian Computing Education Conference, 30 January - 2 February 2018, Brisbane, Queensland, pp. 35-44. ISBN 978-1-4503-6340-2 (2018) [Refereed Conference Paper] DOI: 10.1145/3160489.3160495 [eCite] [Details] Citations: Scopus - 1 Co-authors: Herbert N | |
| 2018 | Yang W, Garg S, Raza A, Herbert D, Kang BH, 'Blockchain: trends and future', Proceedings of the 15th Pacific Rim Knowledge Acquisition Workshop (PKAW 2018): Knowledge Management and Acquisition for Intelligent Systems, 28-29 August 2018, Nanjing, China, pp. 201-210. ISSN 0302-9743 (2018) [Refereed Conference Paper] DOI: 10.1007/978-3-319-97289-3 [eCite] [Details] Co-authors: Yang W; Garg S; Raza A; Kang BH |
Grants & Funding
Funding Summary
Number of grants
1
Total funding
$99,978
Projects
Seamless Integration of Knowledge Acquisition for Autonomous Systems by Domain Users with Prudence Capability (2016 - 2017)$99,978
- Description
- Knowledge-based systems are typically constrained by their ability to acquire new knowledge without the intercession of a technical knowledge engineer. This introduces a fundamental disconnect between the system and the domain expert - even if a knowledge acquisition interface is provided, the domain expert is usually highly constrained in their expressiveness and ability to train the system due to technology-specific implementation.Knowledge-based systems are also currently limited in their applicability to autonomous systems. The domain expert/knowledge acquisition bottleneck in this paradigm also poses a great challenge to effectively train an autonomous system with new or modified behaviours without considerable effort and implementation change. In the autonomous system-operating environment, there is no consistent model of abstraction (of services/behaviour, information and data) that can be leveraged across different systems and domains. To address these shortcomings, we will develop an extensive, easily maintainable hierarchical Knowledge Base System (KBS) for Autonomous Systems (AS) technologies (such as drones and humanoid robots) that will be trained by Knowledge Domain Experts (KDE) using a Natural Language (NL) interface for communication. The system will implement an abstracted architecture, taking a layer-based approach to separate data and hardware, information, and services, each with an associated, contextual knowledge base. We will introduce and develop a module (termed a Curator) that will facilitate the choice (or procurement via knowledge acquisition) of behavioural and information abstractions at each layer. This will allow the AS to infer correct behaviour given high-layer service directives, in effect allowing the KDE to train a behaviour quickly and effectively when the associated contextual knowledge base lacks the knowledge to fulfil an inter-layer request.
- Funding
- Asian Office of Aerospace Research & Development ($99,978)
- Scheme
- Grant
- Administered By
- University of Tasmania
- Research Team
- Kang BH; Han S; Herbert DP
- Period
- 2016 - 2017