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Full-Text Articles in Science and Technology Studies

Identity-Based Remote Data Integrity Checking With Perfect Data Privacy Preserving For Cloud Storage, Yong Yu, Man Ho Au, Giuseppe Ateniese, Xinyi Huang, Willy Susilo, Yuanshun Dai, Geyong Min Jan 2017

Identity-Based Remote Data Integrity Checking With Perfect Data Privacy Preserving For Cloud Storage, Yong Yu, Man Ho Au, Giuseppe Ateniese, Xinyi Huang, Willy Susilo, Yuanshun Dai, Geyong Min

Faculty of Engineering and Information Sciences - Papers: Part A

Remote data integrity checking (RDIC) enables a data storage server, say a cloud server, to prove to a verifier that it is actually storing a data owner's data honestly. To date, a number of RDIC protocols have been proposed in the literature. However, most of the constructions suffer from the issue of requiring complex key management. That is, they rely on the expensive public key infrastructure (PKI), which might hinder the deployment of RDIC in practice. In this paper, we propose a new construction of identity-based (ID-based) RDIC protocol by making use of key-homomorphic cryptographic primitive to reduce the system …


Sharing Social Network Data: Differentially Private Estimation Of Exponential Family Random-Graph Models, Vishesh Karwa, Pavel N. Krivitsky, Aleksandra B. Slavkovic Jan 2017

Sharing Social Network Data: Differentially Private Estimation Of Exponential Family Random-Graph Models, Vishesh Karwa, Pavel N. Krivitsky, Aleksandra B. Slavkovic

Faculty of Engineering and Information Sciences - Papers: Part A

Motivated by a real life problem of sharing social network data that contain sensitive personal information, we propose a novel approach to release and analyse synthetic graphs to protect privacy of individual relationships captured by the social network while maintaining the validity of statistical results. A case-study using a version of the Enron e-mail corpus data set demonstrates the application and usefulness of the proposed techniques in solving the challenging problem of maintaining privacy and supporting open access to network data to ensure reproducibility of existing studies and discovering new scientific insights that can be obtained by analysing such data. …


Collaborative Data Analytics Towards Prediction On Pathogen-Host Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song Jan 2017

Collaborative Data Analytics Towards Prediction On Pathogen-Host Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song

Faculty of Engineering and Information Sciences - Papers: Part B

Nowadays more and more data are being sequenced and accumulated in system biology, which bring the data analytics researchers to a brand new era, namely 'big data', to extract the inner relationship and knowledge from the huge amount of data.


Towards Massive Data And Sparse Data In Adaptive Micro Open Educational Resource Recommendation: A Study On Semantic Knowledge Base Construction And Cold Start Problem, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Fang Dong, Dongming Xu, Jun Shen Jan 2017

Towards Massive Data And Sparse Data In Adaptive Micro Open Educational Resource Recommendation: A Study On Semantic Knowledge Base Construction And Cold Start Problem, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Fang Dong, Dongming Xu, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs.


Cost-Effective Big Data Mining In The Cloud: A Case Study With K-Means, Qiang He, Xiaodong Zhu, Dongwei Li, Shuliang Wang, Jun Shen, Yun Yang Jan 2017

Cost-Effective Big Data Mining In The Cloud: A Case Study With K-Means, Qiang He, Xiaodong Zhu, Dongwei Li, Shuliang Wang, Jun Shen, Yun Yang

Faculty of Engineering and Information Sciences - Papers: Part B

Mining big data often requires tremendous computationalresources. This has become a major obstacle to broad applicationsof big data analytics. Cloud computing allows data scientists to access computationalresources on-demand for building their big data analytics solutions in the cloud.


Metamorphic Testing For Adobe Data Analytics Software, Darryl C. Jarman, Zhiquan Zhou, Tsong Yueh Chen Jan 2017

Metamorphic Testing For Adobe Data Analytics Software, Darryl C. Jarman, Zhiquan Zhou, Tsong Yueh Chen

Faculty of Engineering and Information Sciences - Papers: Part B

It is challenging to test data analytics software because a test oracle might not be available. This study reports our experience of applying metamorphic testing to Adobe's data analytics software that is used for anomaly detection in a set of time series data. We make use of geometric transformations to build metamorphic relations and generate simple time series data as the source test cases. The results of this study show that metamorphic testing is highly effective for both verification and validation purposes. An investigation of the issues detected during metamorphic testing revealed three bugs in the software under test.


Towards Cost Reduction In Cloud-Based Workflow Management Through Data Replication, Fei Xie, Jun Yan, Jun Shen Jan 2017

Towards Cost Reduction In Cloud-Based Workflow Management Through Data Replication, Fei Xie, Jun Yan, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.


Text Data Mining Of Aged Care Accreditation Reports To Identify Risk Factors In Medication Management In Australian Residential Aged Care Homes, Tao Jiang, Siyu Qian, David M. Hailey, Jun Ma, Ping Yu Jan 2017

Text Data Mining Of Aged Care Accreditation Reports To Identify Risk Factors In Medication Management In Australian Residential Aged Care Homes, Tao Jiang, Siyu Qian, David M. Hailey, Jun Ma, Ping Yu

Faculty of Engineering and Information Sciences - Papers: Part B

This study aimed to identify risk factors in medication management in Australian residential aged care (RAC) homes. Only 18 out of 3,607 RAC homes failed aged care accreditation standard in medication management between 7th March 2011 and 25th March 2015. Text data mining methods were used to analyse the reasons for failure. This led to the identification of 21 risk indicators for an RAC home to fail in medication management. These indicators were further grouped into ten themes. They are overall medication management, medication assessment, ordering, dispensing, storage, stock and disposal, administration, incident report, monitoring, staff and resident satisfaction. The …