Swinburne University of Technology

About: Swinburne University of Technology is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Galaxy & Population. The organization has 7223 authors who have published 25530 publications receiving 667955 citations. The organization is also known as: Swinburne Technical College & Swinburne College of Technology.

Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions.

Abstract: Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is nowadays considered as a core technology of today’s Fourth Industrial Revolution (4IR or Industry 4.0). Due to its learning capabilities from data, DL technology originated from artificial neural network (ANN), has become a hot topic in the context of computing, and is widely applied in various application areas like healthcare, visual recognition, text analytics, cybersecurity, and many more. However, building an appropriate DL model is a challenging task, due to the dynamic nature and variations in real-world problems and data. Moreover, the lack of core understanding turns DL methods into black-box machines that hamper development at the standard level. This article presents a structured and comprehensive view on DL techniques including a taxonomy considering various types of real-world tasks like supervised or unsupervised. In our taxonomy, we take into account deep networks for supervised or discriminative learning, unsupervised or generative learning as well as hybrid learning and relevant others. We also summarize real-world application areas where deep learning techniques can be used. Finally, we point out ten potential aspects for future generation DL modeling with research directions. Overall, this article aims to draw a big picture on DL modeling that can be used as a reference guide for both academia and industry professionals.

Highly Ordered Mesoporous Silica Films with Perpendicular Mesochannels by a Simple Stöber‐Solution Growth Approach

Abstract: This work was supported by the NSF of China (20890123), the State Key Basic Research Program of the PRC (2009AA033701 and 2009CB930400), the Science and Technology Commission of Shanghai Municipality (08DZ2270500), and the Shanghai Leading Academic Discipline Project (B108). Z.T. thanks the National Science Foundation for Post-doctoral Scientists of China (20100480030) and the Shanghai Postdoctoral Sustentation Fund (11R21411500) for financial support. We thank the Instrument Center of Central University in Taiwan for measuring the GISAX data.

Small business use of the Internet: Findings from Australian case studies

Abstract: Internet use among small businesses has recently become a popular topic for researchers in the fields of marketing, information systems and entrepreneurship. In view of the media hype this topic has received over recent months, it is important for small businesses to learn from the experiences of early adopters of the Internet. Presents the results of a case study research involving 23 Australian small businesses which were early adopters of the Internet ‐ and which are still users. Finds that they are predominantly using the Internet as a communications medium and, to a lesser extent, as a document transfer and advertising channel. Management enthusiasm and perceived benefits seem to be the driving force for ongoing Internet use, although little or no integration was discovered between internal applications and Internet inter‐organizational functions. Findings also point to the importance of entrepreneurship for successful Internet use.

Detecting and Preventing Cyber Insider Threats: A Survey

Abstract: Information communications technology systems are facing an increasing number of cyber security threats, the majority of which are originated by insiders. As insiders reside behind the enterprise-level security defence mechanisms and often have privileged access to the network, detecting and preventing insider threats is a complex and challenging problem. In fact, many schemes and systems have been proposed to address insider threats from different perspectives, such as intent, type of threat, or available audit data source. This survey attempts to line up these works together with only three most common types of insider namely traitor, masquerader, and unintentional perpetrator, while reviewing the countermeasures from a data analytics perspective. Uniquely, this survey takes into account the early stage threats which may lead to a malicious insider rising up. When direct and indirect threats are put on the same page, all the relevant works can be categorised as host, network, or contextual data-based according to audit data source and each work is reviewed for its capability against insider threats, how the information is extracted from the engaged data sources, and what the decision-making algorithm is. The works are also compared and contrasted. Finally, some issues are raised based on the observations from the reviewed works and new research gaps and challenges identified.

Multipartite Einstein-Podolsky-Rosen steering and genuine tripartite entanglement with optical networks

Abstract: This research was conducted by the Australian Research Council Centre of Excellence for Quantum Computation and Communication Technology (project number CE110001029) and has been supported by the Australian Research Council DECRA and Discovery Project Grants schemes. S.A. is grateful for funding from the Australia–Asia Prime Minister‘s Award. R.Y.T. thanks Swinburne University for a Research SUPRA Award, and Q.H. thanks National Natural Science Foundation of China under Grant No. 11121091 and 11274025. This work was supported in part by National Science Foundation Grant No. PHYS-1066293 and the hospitality of the Aspen Center for Physics.