Outputs (26)

A tool for generating synthetic data (2018)
Presentation / Conference Contribution
Peng, T., & Telle, A. (2018, October). A tool for generating synthetic data. Presented at DATA '18 First International Conference on Data Science, E-learning and Information Systems, Madrid, Spain

It is popular to use real-world data to evaluate data mining techniques. However, there are some disadvantages to use real-world data for such purposes. Firstly, real-world data in most domains is difficult to obtain for several reasons, such as budg... Read More about A tool for generating synthetic data.

A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network (2018)
Journal Article
Liu, X., Liu, Q., & Sun, M. (2018). A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network. Computers, Materials & Continua, 57(2), 179-194. https://doi.org/10.32604/cmc.2018.04025

In a home energy management system (HEMS), appliances are becoming diversified and intelligent, so that certain simple maintenance work can be completed by appliances themselves. During the measurement, collection and transmission of electricity load... Read More about A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network.

An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment (2018)
Journal Article
Jin, D.-D., Liu, Q., Liu, X., & Linge, N. (2019). An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment. Journal of Computers, 30(3), 130-142. https://doi.org/10.3966/199115992019063003010

Hadoop is a famous parallel computing framework that is applied to process large-scale data, but there exists such a task in hadoop framework, which is called “Straggling task” and has a serious impact on Hadoop. Speculative execution (SE) is an effe... Read More about An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment.

SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data (2018)
Journal Article
Xiao, B., Wang, Z., Liu, Q., & Liu, X. (2018). SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data. Computers, Materials & Continua, 56(3), 365-379. https://doi.org/10.3970/cmc.2018.01830

In recent years, the rapid development of big data technology has also been favored by more and more scholars. Massive data storage and calculation problems have also been solved. At the same time, outlier detection problems in mass data have also co... Read More about SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data.

SICSA Demofest 2018 - Supporting user choice in optimisation. (2018)
Exhibition / Performance
Urquhart, N., Hutcheson, W., & Hoehl, S. SICSA Demofest 2018 - Supporting user choice in optimisation. Exhibited at Our Dynamic Earth, Edinburgh. 6 November 2018 - 6 November 2018

Many complex optimisation problems can have multiple solutions, techniques such as MAP –Elites will produce a large number of solutions from which the user should make the final choice. That final choice may be based on a number of soft criteria for... Read More about SICSA Demofest 2018 - Supporting user choice in optimisation..

An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules (2018)
Journal Article
Habibullah, S., Liu, X., & Tan, Z. (2018). An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules. International Journal of Computer Theory and Engineering, 10(5), 164-169. https://doi.org/10.7763/ijcte.2018.v10.1219

Evolving legacy enterprise systems into a lean system architecture has been on the agendas of many enterprises. Recent advance in legacy system evaluation is in favour of microservice technologies, which not only significantly reduce the complexity i... Read More about An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules.

Interference graphs to monitor and control schedules in low-power WPAN (2018)
Journal Article
van der Lee, T., Liotta, A., & Exarchakos, G. (2019). Interference graphs to monitor and control schedules in low-power WPAN. Future Generation Computer Systems, 93, 111-120. https://doi.org/10.1016/j.future.2018.10.014

Highlights
• This study presents the complete and slotted interference graph model.
• The service uses the complete interference graph to evaluate the network.
• Slotted interference graphs are used to reschedule problematic connections.
• Rea... Read More about Interference graphs to monitor and control schedules in low-power WPAN.

Appliance Recognition Based on Continuous Quadratic Programming (2018)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2018, June). Appliance Recognition Based on Continuous Quadratic Programming. Presented at 4th International Conference on Cloud Computing and Security (ICCCS 2018), Haikou, China

The detailed information of residents' electricity consumption is of great significance to the planning of the use of electrical appliances and the reduction of electrical energy consumption. On the basis of analyzing the characteristics of residents... Read More about Appliance Recognition Based on Continuous Quadratic Programming.

2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms (2018)
Presentation / Conference Contribution
Lapok, P., Lawson, A., & Paechter, B. (2018, September). 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms. Presented at EngOpt 2018 International Conference on Engineering Optimization, Lisboa, Portugal

In this paper, we investigate the ability of genetic representation methods to describe two-dimensional outline shapes, in order to use them in a generative design system. A specific area of mechanical design focuses on planar mechanisms. These are a... Read More about 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms.

A Self-organizing LSTM-Based Approach to PM2.5 Forecast (2018)
Presentation / Conference Contribution
Liu, X., Liu, Q., Zou, Y., & Wang, G. (2018, June). A Self-organizing LSTM-Based Approach to PM2.5 Forecast. Presented at 4th International Conference on Cloud Computing and Security (ICCCS 2018), Haikou, China

Nanjing has been listed as the one of the worst performers across China with respect to the high level of haze-fog, which impacts people's health greatly. For the severe condition of haze-fog, PM2.5 is the main cause element of haze-fog pollution in... Read More about A Self-organizing LSTM-Based Approach to PM2.5 Forecast.

CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN (2018)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2018, April). CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN. Presented at 2018 3rd International Conference on Computer and Communication Systems (ICCCS), Nagoya, Japan

Acoustic Communication is one of the most common and popular techniques used for Underwater Sensor Networks. The design of its communication protocol becomes a challenge due to its features of high delay and low bandwidth. Relevant research work has... Read More about CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN.

Home appliances classification based on multi-feature using ELM (2018)
Journal Article
Wu, Z., Liu, Q., Chen, F., Chen, F., Liu, X., & Linge, N. (2018). Home appliances classification based on multi-feature using ELM. International Journal of Sensor Networks, 28(1), 34. https://doi.org/10.1504/ijsnet.2018.094710

With the development of science and technology, the application in artificial intelligence has been more and more popular, as well as smart home has become a hot topic. And pattern recognition adapting to smart home attracts more attention, while the... Read More about Home appliances classification based on multi-feature using ELM.

A Transparent Thread and Fiber Framework in C++CSP (2018)
Presentation / Conference Contribution
Chalmers, K. (2018, August). A Transparent Thread and Fiber Framework in C++CSP. Presented at Communicating Process Architectures, Dresden, Germany

There are multiple low-level concurrency primitives supported today, but these often require the programmer to be explicit in their implementation decisions at design time. This work illustrates how a process-oriented model written in C++CSP can hide... Read More about A Transparent Thread and Fiber Framework in C++CSP.

Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces. (2018)
Presentation / Conference Contribution
Bamgboye, O., Liu, X., & Cruickshank, P. (2018, July). Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces. Presented at 12th IEEE Interna@onal Workshop on QUALITY ORIENTED REUSE OF SOFTWARE" (QUORS 2018)/ 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Tokyo, Japan

Smart Spaces currently benefits from Internet of Things (IoT) infrastructures in order to realise its objectives. In many cases, it demonstrates this through certain automated applications that relies on sensor streams that comes with some uncertaint... Read More about Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces..

Developing an Evaluation Framework for Knowledge Management Systems in SMEs (2018)
Presentation / Conference Contribution
Bratton, A., & Thomson, A. (2018, June). Developing an Evaluation Framework for Knowledge Management Systems in SMEs. Paper presented at International Institute for Applied KM 2018 : Knowledge Management: Research, Organization, and Applied Innovation, University of Pisa, Pisa, Italy

This paper develops an evaluation framework for knowledge management systems (KMS) in small and medium-sized enterprises (SMEs). An embedded research approach was used to develop an evaluation framework for KMS in a small, UK-based, information techn... Read More about Developing an Evaluation Framework for Knowledge Management Systems in SMEs.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science (2018)
Journal Article
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018). Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science. Nature Communications, 9(1), Article 2383. https://doi.org/10.1038/s41467-018-04316-3

Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-... Read More about Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 (2018)
Journal Article
Pace, P., Aloi, G., Gravina, R., Caliciuri, G., Fortino, G., & Liotta, A. (2019). An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0. IEEE Transactions on Industrial Informatics, 15(1), 481-489. https://doi.org/10.1109/tii.2018.2843169

Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data coming from Internet of Things (IoT) devices toward... Read More about An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0.

Composition of dynamic components based on behavioral descriptions (2018)
Thesis
Barati, M. Composition of dynamic components based on behavioral descriptions. (Thesis). Université de Sherbrooke. http://researchrepository.napier.ac.uk/Output/2767225

Abstract: This thesis proposes solutions to four new problems stemming from a general framework of horizontal behavior composition, in which transition systems are used to model behaviors. The framework allows the realization of a new behavior from a... Read More about Composition of dynamic components based on behavioral descriptions.

On-Line Building Energy Optimization Using Deep Reinforcement Learning (2018)
Journal Article
Mocanu, E., Mocanu, D. C., Nguyen, P. H., Liotta, A., Webber, M. E., Gibescu, M., & Slootweg, J. G. (2019). On-Line Building Energy Optimization Using Deep Reinforcement Learning. IEEE Transactions on Smart Grid, 10(4), 3698-3708. https://doi.org/10.1109/tsg.2018.2834219

Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the future power systems and to help customers transition from a passive to an... Read More about On-Line Building Energy Optimization Using Deep Reinforcement Learning.

A method for electric load data verification and repair in home environment (2018)
Journal Article
Liu, Q., Li, S., Liu, X., & Linge, N. (2018). A method for electric load data verification and repair in home environment. International Journal of Embedded Systems, 10(3), 248-256. https://doi.org/10.1504/ijes.2018.091788

Home energy management (HEM) and smart home have been popular among people; HEM collects and analyses the electric load data to make the power use safe, reliable, economical, efficient and environmentally friendly. Without the correct data, the corre... Read More about A method for electric load data verification and repair in home environment.