Graphene-driven revolutions in ICT and beyond

This session described the FET Flagship Pilot on graphene and related two-dimensional materials. The flagship targets a revolution in information and communication technology, with impacts reaching into other areas of the society. The session featured four talks on the scientific and technological potential and open research challenges within the scope of the proposed flagship, industrial view on possibilities and challenges posed by graphene and related materials, and presentation on the implementation and structure of the flagship pilot. © Selection and peer-review under responsibility of FET11 conference organizers and published by Elsevier B.V.

Accelerator-induced transients in Accelerator Driven Subcritical Reactors

Achieving higher particles energies and beam powers have long been the main focus of research in accelerator technology. Since Accelerator Driven Subcritical Reactors (ADSRs) have become the subject of increasing interest, accelerator reliability and modes of operation have become important matters that require further research and development in order to accommodate the engineering and economic needs of ADSRs. This paper focuses on neutronic and thermo-mechanical analyses of accelerator-induced transients in an ADSR. Such transients fall into three main categories: beam interruptions (trips), pulsed-beam operation, and beam overpower. The concept of a multiple-target ADSR is shown to increase system reliability and to mitigate the negative effects of beam interruptions, such as thermal cyclic fatigue in the fuel cladding and the huge financial cost of total power loss. This work also demonstrates the effectiveness of the temperature-to-reactivity feedback mechanisms in ADSRs. A comparison of shutdown mechanisms using control rods and beam cut-off highlights the intrinsic safety features of ADSRs. It is evident that the presence of control rods is crucial in an industrial-scale ADSR. This paper also proposes a method to monitor core reactivity online using the repetitive pattern of beam current fluctuations in a pulsed-beam operation mode. Results were produced using PTS-ADS, a computer code developed specifically to study the dynamic neutronic and thermal responses to beam transients in subcritical reactor systems. © 2012 Elsevier B.V.

an intuitive formal proof for deadline driven scheduler

United Nations University, Int. Inst. for Softw. Technol., China; Vietnam National University, Hanoi, Vietnam; Vietnam Academy of Science and Technology, Vietnam

Design and Evaluation of the Hamal Parallel Computer

Parallel shared-memory machines with hundreds or thousands of processor-memory nodes have been built; in the future we will see machines with millions or even billions of nodes. Associated with such large systems is a new set of design challenges. Many problems must be addressed by an architecture in order for it to be successful; of these, we focus on three in particular. First, a scalable memory system is required. Second, the network messaging protocol must be fault-tolerant. Third, the overheads of thread creation, thread management and synchronization must be extremely low. This thesis presents the complete system design for Hamal, a shared-memory architecture which addresses these concerns and is directly scalable to one million nodes. Virtual memory and distributed objects are implemented in a manner that requires neither inter-node synchronization nor the storage of globally coherent translations at each node. We develop a lightweight fault-tolerant messaging protocol that guarantees message delivery and idempotence across a discarding network. A number of hardware mechanisms provide efficient support for massive multithreading and fine-grained synchronization. Experiments are conducted in simulation, using a trace-driven network simulator to investigate the messaging protocol and a cycle-accurate simulator to evaluate the Hamal architecture. We determine implementation parameters for the messaging protocol which optimize performance. A discarding network is easier to design and can be clocked at a higher rate, and we find that with this protocol its performance can approach that of a non-discarding network. Our simulations of Hamal demonstrate the effectiveness of its thread management and synchronization primitives. In particular, we find register-based synchronization to be an extremely efficient mechanism which can be used to implement a software barrier with a latency of only 523 cycles on a 512 node machine.

Flexibility and Efficiency in a Computer Program for Designing Circuits

This report is concerned with the problem of achieving flexibility (additivity, modularity) and efficiency (performance, expertise) simultaneously in one AI program. It deals with the domain of elementary electronic circuit design. The proposed solution is to provide a deduction-driven problem solver with built-in-control-structure concepts. This problem solver and its knowledge base in the applicaitn areas of design and electronics are descrbed. The prgram embodying it is being used to explore the solutionof some modest problems in circuit design. It is concluded that shallow reasoning about problem-solver plans is necessary for flexibility, and can be implemented with reasonable efficiency.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in Clouds: four kinds of schema.

The proposed research will focus on developing a novel approach to solve Software Service Evolution problems in Computing Clouds. The approach will support dynamic evolution of the software service in clouds via a set of discovered evolution patterns. An initial survey informed us that such an approach does not exist yet and is in urgent need. Evolution Requirement can be classified into evolution features; researchers can describe the whole requirement by using evolution feature typology, the typology will define the relation and dependency between each features. After the evolution feature typology has been constructed, evolution model will be created to make the evolution more specific. Aspect oriented approach can be used for enhance evolution feature-model modularity. Aspect template code generation technique will be used for model transformation in the end. Product Line Engineering contains all the essential components for driving the whole evolution process.

Data-driven fuzzy rule generation and its application for student academic performance evaluation

K. Rasmani and Q. Shen. Data-driven fuzzy rule generation and its application for student academic performance evaluation. Applied Intelligence, 25(3):305-319, 2006.

A scenario-driven decision support system for serious crime investigation

Q. Shen, J. Keppens, C. Aitken, B. Schafer, and M. Lee. A scenario driven decision support system for serious crime investigation. Law, Probability and Risk, 5(2):87-117, 2006. Sponsorship: UK Engineering and Physical Sciences Research Council grant GR/S63267; partially supported by grant GR/S98603

Error-driven active learning in growing radial basis function networks for early robot learning

Q. Meng and M.H. Lee, 'Error-driven active learning in growing radial basis function networks for early robot learning', 2006 IEEE International Conference on Robotics and Automation (IEEE ICRA 2006), 2984-90, Orlando, Florida, USA.

A corpus-driven error analysis of the oral and written production of Leaving Certificate Spanish learners

The Leaving Certificate (LC) is the national, standardised state examination in Ireland necessary for entry to third level education – this presents a massive, raw corpus of data with the potential to yield invaluable insight into the phenomena of learner interlanguage. With samples of official LC Spanish examination data, this project has compiled a digitised corpus of learner Spanish comprised of the written and oral production of 100 candidates. This corpus was then analysed using a specific investigative corpus technique, Computer-aided Error Analysis (CEA, Dagneaux et al, 1998). CEA is a powerful apparatus in that it greatly facilitates the quantification and analysis of a large learner corpus in digital format. The corpus was both compiled and analysed with the use of UAM Corpus Tool (O’Donnell 2013). This Tool allows for the recording of candidate-specific variables such as grade, examination level, task type and gender, therefore allowing for critical analysis of the corpus as one unit, as separate written and oral sub corpora and also of performance per task, level and gender. This is an interdisciplinary work combining aspects of Applied Linguistics, Learner Corpus Research and Foreign Language (FL) Learning. Beginning with a review of the context of FL learning in Ireland and Europe, I go on to discuss the disciplinary context and theoretical framework for this work and outline the methodology applied. I then perform detailed quantitative and qualitative analyses before going on to combine all research findings outlining principal conclusions. This investigation does not make a priori assumptions about the data set, the LC Spanish examination, the context of FLs or of any aspect of learner competence. It undertakes to provide the linguistic research community and the domain of Spanish language learning and pedagogy in Ireland with an empirical, descriptive profile of real learner performance, characterising learner difficulty.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Examining the effect of exit separation on aircraft evacuation performance using evacuation modelling techniques: "Is the 60 foot rule relevant?"

This paper examines the influence of exit separation, exit availability and seating configuration on aircraft evacuation efficiency and evacuation time. The purpose of this analysis is to explore how these parameters influence the 60 foot exit separation requirement found in aircraft certification rules. The analysis makes use of the airEXODUS evacuation model and is based on a typical wide-body aircraft cabin section involving two pairs of Type-A exits located at either end of the section with a maximum permissible loading of 220 passengers located between the exits. The analysis reveals that there is a complex relationship between exit separation and evacuation efficiency. Indeed, other factors such as exit flow rate and exit availability are shown to exert a strong influence on critical exit separations. A main finding of this work is that for the cabin section examined under certification conditions, exit separations up to 170 feet will result in approximately constant total evacuation times and average personal evacuation times. This practical exit separation threshold is decreased to 114 feet if another combination of exits is selected. While other factors must also be considered when determining maximum allowable exit separations, these results suggest it is not possible to mandate a maximum exit separation without taking into consideration exit type, exit availability and aircraft configuration. This has implications when determining maximum allowable exit separations for wide and narrow body aircraft. It is also relevant when considering the maximum allowable separation between different exit types on a given aircraft configuration.

Policy-driven self-management for an automotive middleware

This paper describes work towards the deployment of self-managing capabilities into an advanced middleware for automotive systems. The middleware will support a range of futuristic use-cases requiring context-awareness and dynamic system configuration. Several use-cases are described and their specific context-awareness requirements identified. The discussion is accompanied by a justification for the selection of policy-based computing as the autonomics technique to drive the self-management. The specific policy technology to be deployed is described briefly, with a focus on its specific features that are of direct relevance to the middleware project. A selected use-case is explored in depth to illustrate the extent of dynamic behaviour achievable in the proposed middleware architecture, which is composed of several policy-configured services. An early demonstration application which facilitates concept evaluation is presented and a sequence of typical device-discovery events is worked through