A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

Predicting the performance of passenger ships using computer simulation

When designing a new passenger ship or naval vessel or modifying an existing design, how do we ensure that the proposed design is safe from an evacuation point of view? In the wake of major maritime disasters such as the Herald of Free Enterprise and the Estonia and in light of the growth in the numbers of high density, high-speed ferries and large capacity cruise ships, issues concerned with the evacuation of passengers and crew at sea are receiving renewed interest. In the maritime industry, ship evacuation models are now recognised by IMO through the publication of the Interim Guidelines for Evacuation Analysis of New and Existing Passenger Ships including Ro-Ro. This approach offers the promise to quickly and efficiently bring evacuation considerations into the design phase, while the ship is "on the drawing board" as well as reviewing and optimising the evacuation provision of the existing fleet. Other applications of this technology include the optimisation of operating procedures for civil and naval vessels such as determining the optimal location of a feature such as a casino, organising major passenger movement events such as boarding/disembarkation or restaurant/theatre changes, determining lean manning requirements, location and number of damage control parties, etc. This paper describes the development of the maritimeEXODUS evacuation model which is fully compliant with IMO requirements and briefly presents an example application to a large passenger ferry.

Position paper on passive sampling techniques for the monitoring of contaminants in the aquatic environment - Achievements to date and perspectives

This paper, based on the outcome of discussions at a NORMAN Network-supported workshop in Lyon (France) in November 2014 aims to provide a common position of passive sampling community experts regarding concrete actions required to foster the use of passive sampling techniques in support of contaminant risk assessment and management and for routine monitoring of contaminants in aquatic systems. The brief roadmap presented here focusses on the identification of robust passive sampling methodology, technology that requires further development or that has yet to be developed, our current knowledge of the evaluation of uncertainties when calculating a freely dissolved concentration, the relationship between data from PS and that obtained through biomonitoring. A tiered approach to identifying areas of potential environmental quality standard (EQS) exceedances is also shown. Finally, we propose a list of recommended actions to improve the acceptance of passive sampling by policy-makers. These include the drafting of guidelines, quality assurance and control procedures, developing demonstration projects where biomonitoring and passive sampling are undertaken alongside, organising proficiency testing schemes and interlaboratory comparison and, finally, establishing passive sampler-based assessment criteria in relation to existing EQS.

A model of macadamia with application to pruning in orchards

A self-organising model of macadamia, expressed using L-Systems, was used to explore aspects of canopy management. A small set of parameters control the basic architecture of the model, with a high degree of self-organisation occurring to determine the fate and growth of buds. Light was sensed at the leaf level and used to represent vigour and accumulated basipetally. Buds also sensed light so as to provide demand in the subsequent redistribution of the vigour. Empirical relationships were derived from a set of 24 completely digitised trees after conversion to multiscale tree graphs (MTG) and analysis with the OpenAlea software library. The ability to write MTG files was embedded within the model so that various tree statistics could be exported for each run of the model. To explore the parameter space a series of runs was completed using a high-throughput computing platform. When combined with MTG generation and analysis with OpenAlea it provided a convenient way in which thousands of simulations could be explored. We allowed the model trees to develop using self-organisation and simulated cultural practices such as hedging, topping, removal of the leader and limb removal within a small representation of an orchard. The model provides insight into the impact of these practices on potential for growth and the light distribution within the canopy and to the orchard floor by coupling the model with a path-tracing program to simulate the light environment. The lessons learnt from this will be applied to other evergreen, tropical fruit and nut trees.

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

A Recommender System based on the Immune Network

Abstract-The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

An Artificial Immune System Based Recommender

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques. Notes: Uwe Aickelin, University of the West of England, Coldharbour Lane, Bristol, BS16 1QY, UK

A cyber exercise post assessment framework: In Malaysia perspectives

Critical infrastructures are based on complex systems that provide vital services to the nation. The complexities of the interconnected networks, each managed by individual organisations, if not properly secured, could offer vulnerabilities that threaten other organisations’ systems that depend on their services. This thesis argues that the awareness of interdependencies among critical sectors needs to be increased. Managing and securing critical infrastructure is not isolated responsibility of a government or an individual organisation. There is a need for a strong collaboration among critical service providers of public and private organisations in protecting critical information infrastructure. Cyber exercises have been incorporated in national cyber security strategies as part of critical information infrastructure protection. However, organising a cyber exercise involved multi sectors is challenging due to the diversity of participants’ background, working environments and incidents response policies. How well the lessons learned from the cyber exercise and how it can be transferred to the participating organisations is still a looming question. In order to understand the implications of cyber exercises on what participants have learnt and how it benefits participants’ organisation, a Cyber Exercise Post Assessment (CEPA) framework was proposed in this research. The CEPA framework consists of two parts. The first part aims to investigate the lessons learnt by participants from a cyber exercise using the four levels of the Kirkpatrick Training Model to identify their perceptions on reaction, learning, behaviour and results of the exercise. The second part investigates the Organisation Cyber Resilience (OCR) of participating sectors. The framework was used to study the impact of the cyber exercise called X Maya in Malaysia. Data collected through interviews with X Maya 5 participants were coded and categorised based on four levels according to the Kirkpatrick Training Model, while online surveys distributed to ten Critical National Information Infrastructure (CNII) sectors participated in the exercise. The survey used the C-Suite Executive Checklist developed by World Economic Forum in 2012. To ensure the suitability of the tool used to investigate the OCR, a reliability test conducted on the survey items showed high internal consistency results. Finally, individual OCR scores were used to develop the OCR Maturity Model to provide the organisation cyber resilience perspectives of the ten CNII sectors.

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

Newly qualified teachers’ needs of support for professional competences in four European countries: Finland, the United Kingdom, Portugal, and Belgium

The first few years in the teaching profession are usually demanding. Although initial teacher education forms an essential foundation for teachers’ work, it cannot fully prepare new teachers for the complexities of working life. This study focuses on investigating the need for professional development support among newly qualified teachers to determine what their professional learning needs are and how these needs differ among teachers from four different countries: Finland, the United Kingdom (England), Portugal and Belgium (Flanders). The research data was collected via a questionnaire from 314 teachers, each with less than five years of teaching experience, and both closed and open-ended questions were included. The quantitative data was analysed using descriptive statistics and factor analysis to identify the latent variables associated with their needs. Answers to the open-ended questions were used to gain deeper insight into the newly qualified teachers’ situation. The results indicate that new teachers need support, especially regarding conflict situations and in differentiating their teaching. In addition, when analysing the profiles of eight support-need latent variables, all of the teachers in the different countries viewed supporting students’ holistic development as the most important area. Although the results of this study cannot be generalised, they provide an important overview of new teachers’ learning needs that should be taken into account when planning and organising support for them. (DIPF/Orig.)

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

Utilisation de cartes conceptuelles par des formatrices en nutrition à la petite enfance

Introduction : Extenso, le centre de référence en nutrition de l’Université de Montréal, a développé les formations Croqu’Plaisir destinées aux intervenants en services de garde à la petite enfance et des nutritionnistes furent sélectionnées afin de les déployer au Québec. Étant donné le volume imposant de nouvelles connaissances à intégrer pour les diététistes-nutritionnistes, l’utilisation d’un outil pédagogique visant à structurer la pensée semblait pertinente. Cette étude avait pour objectif de décrire l’utilisation de cartes conceptuelles par des nutritionnistes formatrices à la petite enfance au Québec. Méthode : Les nutritionnistes formatrices ont assisté à une formation sur les cartes conceptuelles qui leur a permis de développer une carte conceptuelle à l’aide du logiciel CmapTools sur un sujet de leur choix. Puis, leurs perceptions furent recensées lors d'entrevues dirigées et individuelles. Résultats : 8 diététistes-nutritionnistes possédant de 2 à 15 ans d’expérience et ayant animé de 0 à 32 formations Croqu’Plaisir ont participé à l’étude. Les participantes de l’étude ont affirmé être assez autonomes pour utiliser les fonctions de base du logiciel, mais ont vécu des difficultés lors de la conception de leur carte. Conclusion : Plusieurs commentaires des participantes révèlent des barrières à leur utilisation, soit le temps, la résistance au changement et les barrières organisationnelles. Pour que la place des cartes conceptuelles en nutrition se développe et que leur utilisation soit valorisée, un contexte propice à leur utilisation doit être crée, tant d’un point de vue personnel qu’organisationnel, tant en milieu académique que professionnel.

The local dimension of employment-related welfare policy in Germany, England and Sweden

The link between work and welfare is a key pathway of modern welfare state development in Western Europe. National governments face a constant balancing act between the welfare expectations of the labour forces and the labour market liberalisation demands of the business communities. Facilitating the transit from welfare into employment has therefore become an important tool for the British, German and Swedish governments, providing labour as and when needed while keeping welfare expenditure in check. However, the approaches to organising active labour market policies are quite different, notably with regard to the territorial dimension. Although labour markets are quite diverse in all three cases, the role of local authorities, local agencies and local labour market actors from the private and voluntary sector are generally under-developed and apparently under-appreciated, but in different ways and for different reasons. The article compares current employment-related welfare provisions and approaches to develop active labour market policies in the three countries, and concludes that while certain structural and procedural similarities exist, the basic political priorities and actual support and services provided remain very far apart.

Utilisation de cartes conceptuelles par des formatrices en nutrition à la petite enfance

Introduction : Extenso, le centre de référence en nutrition de l’Université de Montréal, a développé les formations Croqu’Plaisir destinées aux intervenants en services de garde à la petite enfance et des nutritionnistes furent sélectionnées afin de les déployer au Québec. Étant donné le volume imposant de nouvelles connaissances à intégrer pour les diététistes-nutritionnistes, l’utilisation d’un outil pédagogique visant à structurer la pensée semblait pertinente. Cette étude avait pour objectif de décrire l’utilisation de cartes conceptuelles par des nutritionnistes formatrices à la petite enfance au Québec. Méthode : Les nutritionnistes formatrices ont assisté à une formation sur les cartes conceptuelles qui leur a permis de développer une carte conceptuelle à l’aide du logiciel CmapTools sur un sujet de leur choix. Puis, leurs perceptions furent recensées lors d'entrevues dirigées et individuelles. Résultats : 8 diététistes-nutritionnistes possédant de 2 à 15 ans d’expérience et ayant animé de 0 à 32 formations Croqu’Plaisir ont participé à l’étude. Les participantes de l’étude ont affirmé être assez autonomes pour utiliser les fonctions de base du logiciel, mais ont vécu des difficultés lors de la conception de leur carte. Conclusion : Plusieurs commentaires des participantes révèlent des barrières à leur utilisation, soit le temps, la résistance au changement et les barrières organisationnelles. Pour que la place des cartes conceptuelles en nutrition se développe et que leur utilisation soit valorisée, un contexte propice à leur utilisation doit être crée, tant d’un point de vue personnel qu’organisationnel, tant en milieu académique que professionnel.

Impact of single parameter changes on Ceph cloud storage performance

In a general purpose cloud system efficiencies are yet to be had from supporting diverse applications and their requirements within a storage system used for a private cloud. Supporting such diverse requirements poses a significant challenge in a storage system that supports fine grained configuration on a variety of parameters. This paper uses the Ceph distributed file system, and in particular its global parameters, to show how a single changed parameter can effect the performance for a range of access patterns when tested with an OpenStack cloud system.