CloudMPL:a domain specific language for describing management policies for an autonomic cloud infrastructure

To benefit from the advantages that Cloud Computing brings to the IT industry, management policies must be implemented as a part of the operation of the Cloud. Among others, for example, the specification of policies can be used for the management of energy to reduce the cost of running the IT system or also for security policies while handling privacy issues of users. As cloud platforms are large, manual enforcement of policies is not scalable. Hence, autonomic approaches for management policies have recently received a considerable attention. These approaches allow specification of rules that are executed via rule-engines. The process of rules creation starts by the interpretation of the policies drafted by high-rank managers. Then, technical IT staff translate such policies to operational activities to implement them. Such process can start from a textual declarative description and after numerous steps terminates in a set of rules to be executed on a rule engine. To simplify the steps and to bridge the considerable gap between the declarative policies and executable rules, we propose a domain-specific language called CloudMPL. We also design a method of automated transformation of the rules captured in CloudMPL to the popular rule-engine Drools. As the policies are changed over time, code generation will reduce the time required for the implementation of the policies. In addition, using a declarative language for writing the specifications is expected to make the authoring of rules easier. We demonstrate the use of the CloudMPL language into a running example extracted from a management energy consumption case study.

A psychological investigation into the relationship between hemispheric functioning and specific written language difficulties (dyslexia), using pharmaceutical intervention techniques

This thesis attempts a psychological investigation of hemispheric functioning in developmental dyslexia. Previous work using neuropsychological methods with developmental dyslexics is reviewed ,and original work is presented both of a conventional psychometric nature and also utilising a new means of intervention. At the inception of inquiry into dyslexia, comparisons were drawn between developmental dyslexia and acquired alexia, promoting a model of brain damage as the common cause. Subsequent investigators found developmental dyslexics to be neurologically intact, and so an alternative hypothesis was offered, namely that language is abnormally localized (not in the left hemisphere). Research in the last decade, using the advanced techniques of modern neuropsychology, has indicated that developmental dyslexics are probably left hemisphere dominant for language. The development of a new type of pharmaceutical prep~ration (that appears to have a left hemisphere effect) offers an oppertunity to test the experimental hypothesis. This hypothesis propounds that most dyslexics are left hemisphere language dominant, but some of these language related operations are dysfunctioning. The methods utilised are those of psychological assessment of cognitive function, both in a traditional psychometric situation, and with a new form of intervention (Piracetam). The information resulting from intervention will be judged on its therapeutic validity and contribution to the understanding of hemispheric functioning in dyslexics. The experimental studies using conventional psychometric evaluation revealed a dyslexic profile of poor sequencing and name coding ability, with adequate spatial and verbal reasoning skills. Neuropsychological information would tend to suggest that this profile was indicative of adequate right hemsiphere abilities and deficits in some left hemsiphere abilities. When an intervention agent (Piracetam) was used with young adult dyslexics there were improvements in both the rate of acquisition and conservation of verbal learning. An experimental study with dyslexic children revealed that Piracetam appeared to improve reading, writing and sequencing, but did not influence spatial abilities. This would seem to concord with other recent findings, that deve~mental dyslexics may have left hemisphere language localisation, although some of these language related abilities are dysfunctioning.

Where do bright ideas occur in our brain? Meta-analytic evidence from neuroimaging studies of domain-specific creativity

Many studies have assessed the neural underpinnings of creativity, failing to find a clear anatomical localization. We aimed to provide evidence for a multi-componential neural system for creativity. We applied a general activation likelihood estimation (ALE) meta-analysis to 45 fMRI studies. Three individual ALE analyses were performed to assess creativity in different cognitive domains (Musical, Verbal, and Visuo-spatial). The general ALE revealed that creativity relies on clusters of activations in the bilateral occipital, parietal, frontal, and temporal lobes. The individual ALE revealed different maximal activation in different domains. Musical creativity yields activations in the bilateral medial frontal gyrus, in the left cingulate gyrus, middle frontal gyrus, and inferior parietal lobule and in the right postcentral and fusiform gyri. Verbal creativity yields activations mainly located in the left hemisphere, in the prefrontal cortex, middle and superior temporal gyri, inferior parietal lobule, postcentral and supramarginal gyri, middle occipital gyrus, and insula. The right inferior frontal gyrus and the lingual gyrus were also activated. Visuo-spatial creativity activates the right middle and inferior frontal gyri, the bilateral thalamus and the left precentral gyrus. This evidence suggests that creativity relies on multi-componential neural networks and that different creativity domains depend on different brain regions.

Ontologies, taxonomies, thesauri:learning from texts

The use of ontologies as representations of knowledge is widespread but their construction, until recently, has been entirely manual. We argue in this paper for the use of text corpora and automated natural language processing methods for the construction of ontologies. We delineate the challenges and present criteria for the selection of appropriate methods. We distinguish three ma jor steps in ontology building: associating terms, constructing hierarchies and labelling relations. A number of methods are presented for these purposes but we conclude that the issue of data-sparsity still is a ma jor challenge. We argue for the use of resources external tot he domain specific corpus.

Independent component analysis for domain independent watermarking

A new principled domain independent watermarking framework is presented. The new approach is based on embedding the message in statistically independent sources of the covertext to mimimise covertext distortion, maximise the information embedding rate and improve the method's robustness against various attacks. Experiments comparing the performance of the new approach, on several standard attacks show the current proposed approach to be competitive with other state of the art domain-specific methods.

Visual data mining: integrating machine learning with information visualization

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework.

Progressive supranuclear palsy (PSP): general pathology and visual signs and symptoms

Progressive supranuclear palsy (PSP) is a rare, degenerative disorder of the brain believed to affect between 1.39 and 6.6 individuals per 100,000 of the population. The disorder is likely to be more common than suggested by these data due to difficulties in diagnosis and especially in distinguishing PSP from other conditions with similar symptoms such as multiple system atrophy (MSA), corticobasal degeneration (CBD), and Parkinson’s disease (PD). PSP was first described in 1964 by Steele, Richardson and Olszewski and originally called Steele-Richardson-Olszewski syndrome. The disorder is the second commonest syndrome in which the patient exhibits ‘parkinsonism’, viz., a range of problems involving movement most typically manifest in PD itself but also seen in PSP, MSA and CBD. Although primarily a brain disorder, patients with PSP exhibit a range of visual clinical signs and symptoms that may be useful in differential diagnosis. Hence, the present article describes the general clinical and pathological features of PSP, its specific visual signs and symptoms, discusses the usefulness of these signs in differential diagnosis, and considers the various treatment options.

Oculo-visual dysfunction in Parkinson's disease

This review describes the oculo-visual problems likely to be encountered in Parkinson's disease (PD) with special reference to three questions: (1) are there visual symptoms characteristic of the prodromal phase of PD, (2) is PD dementia associated with specific visual changes, and (3) can visual symptoms help in the differential diagnosis of the parkinsonian syndromes, viz. PD, progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), multiple system atrophy (MSA), and corticobasal degeneration (CBD)? Oculo-visual dysfunction in PD can involve visual acuity, dynamic contrast sensitivity, colour discrimination, pupil reactivity, eye movement, motion perception, and visual processing speeds. In addition, disturbance of visuo-spatial orientation, facial recognition problems, and chronic visual hallucinations may be present. Prodromal features of PD may include autonomic system dysfunction potentially affecting pupil reactivity, abnormal colour vision, abnormal stereopsis associated with postural instability, defects in smooth pursuit eye movements, and deficits in visuo-motor adaptation, especially when accompanied by idiopathic rapid eye movement (REM) sleep behaviour disorder. PD dementia is associated with the exacerbation of many oculo-visual problems but those involving eye movements, visuo-spatial function, and visual hallucinations are most characteristic. Useful diagnostic features in differentiating the parkinsonian symptoms are the presence of visual hallucinations, visuo-spatial problems, and variation in saccadic eye movement dysfunction.

Visual data mining using principled projection algorithms and information visualization techniques

We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. It is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. Copyright 2006 ACM.

Self-explanation in adaptive systems based on runtime goal-based models

The behaviour of self adaptive systems can be emergent, which means that the system’s behaviour may be seen as unexpected by its customers and its developers. Therefore, a self-adaptive system needs to garner confidence in its customers and it also needs to resolve any surprise on the part of the developer during testing and maintenance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system’s behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, we propose the use of goal-based requirements models at runtime to offer self-explanation of how a system is meeting its requirements. We demonstrate the analysis of run-time requirements models to yield a self-explanation codified in a domain specific language, and discuss possible future work.

Knowledge transfer in website design:exploring the processes and benefits of design collaboration for non-creative Micros

This thesis explores the interaction between Micros (<10 employees) from non-creative sectors and website designers ("Creatives") that occurred when creating a website of a higher order than a basic template site. The research used Straussian Grounded Theory Method with a longitudinal design, in order to identify what knowledge transferred to the Micros during the collaboration, how it transferred, what factors affected the transfer and outcomes of the transfer including behavioural additionality. To identify whether the research could be extended beyond this, five other design areas were also examined, as well as five Small to Medium Enterprises (SMEs) engaged in website and branding projects. The findings were that, at the start of the design process, many Micros could not articulate their customer knowledge, and had poor marketing and visual language skills, knowledge core to web design, enabling targeted communication to customers through images. Despite these gaps, most Micros still tried to lead the process. To overcome this disjoint, the majority of the designers used a knowledge transfer strategy termed in this thesis as ‘Bi-Modal Knowledge Transfer’, where the Creative was aware of the transfer but the Micro was unaware, both for drawing out customer knowledge from the Micro and for transferring visual language skills to the Micro. Two models were developed to represent this process. Two models were also created to map changes in the knowledge landscapes of customer knowledge and visual language – the Knowledge Placement Model and the Visual Language Scale. The Knowledge Placement model was used to map the placement of customer knowledge within the consciousness, extending the known Automatic-Unconscious -Conscious model, adding two more locations – Peripheral Consciousness and Occasional Consciousness. Peripheral Consciousness is where potential knowledge is held, but not used. Occasional Consciousness is where potential knowledge is held but used only for specific tasks. The Visual Language Scale was created to measure visual language ability from visually responsive, where the participant only responds personally to visual symbols, to visually multi-lingual, where the participant can use visual symbols to communicate with multiple thought-worlds. With successful Bi-Modal Knowledge Transfer, the outcome included not only an effective website but also changes in the knowledge landscape for the Micros and ongoing behavioural changes, especially in marketing. These effects were not seen in the other design projects, and only in two of the SME projects. The key factors for this difference between SMEs and Micros appeared to be an expectation of knowledge by the Creatives and failure by the SMEs to transfer knowledge within the company.

Dynamic decision-making based on NFR for managing software variability and configuration selection

Due to dynamic variability, identifying the specific conditions under which non-functional requirements (NFRs) are satisfied may be only possible at runtime. Therefore, it is necessary to consider the dynamic treatment of relevant information during the requirements specifications. The associated data can be gathered by monitoring the execution of the application and its underlying environment to support reasoning about how the current application configuration is fulfilling the established requirements. This paper presents a dynamic decision-making infrastructure to support both NFRs representation and monitoring, and to reason about the degree of satisfaction of NFRs during runtime. The infrastructure is composed of: (i) an extended feature model aligned with a domain-specific language for representing NFRs to be monitored at runtime; (ii) a monitoring infrastructure to continuously assess NFRs at runtime; and (iii) a exible decision-making process to select the best available configuration based on the satisfaction degree of the NRFs. The evaluation of the approach has shown that it is able to choose application configurations that well fit user NFRs based on runtime information. The evaluation also revealed that the proposed infrastructure provided consistent indicators regarding the best application configurations that fit user NFRs. Finally, a benefit of our approach is that it allows us to quantify the level of satisfaction with respect to NFRs specification.

Two case studies on generating administrative process applications with AdminDSL

Some organizations end up reimplementing the same class of business process over and over: an "administrative process", which consists of managing a form through several states and involving various roles in the organization. This results in wasted time that could be dedicated to better understanding the process or dealing with the fine details that are specific to the process. Existing virtual office solutions require specific training and infrastructure andmay result in vendor lock-in. In this paper, we propose using a high-level domain-specific language (AdminDSL) to describe the administrative process and a separate code generator targeting a standard web framework. We have implemented the approach using Xtext, EGL and the Django web framework, and we illustrate it through two case studies: a synthetic examination process which illustrates the architecture of the generated code, and a real-world workplace survey process that identified several future avenues for improvement.

Background and foreground knowledge in dynamic ontology construction

Ontologies have become a key component in the Semantic Web and Knowledge management. One accepted goal is to construct ontologies from a domain specific set of texts. An ontology reflects the background knowledge used in writing and reading a text. However, a text is an act of knowledge maintenance, in that it re-enforces the background assumptions, alters links and associations in the ontology, and adds new concepts. This means that background knowledge is rarely expressed in a machine interpretable manner. When it is, it is usually in the conceptual boundaries of the domain, e.g. in textbooks or when ideas are borrowed into other domains. We argue that a partial solution to this lies in searching external resources such as specialized glossaries and the internet. We show that a random selection of concept pairs from the Gene Ontology do not occur in a relevant corpus of texts from the journal Nature. In contrast, a significant proportion can be found on the internet. Thus, we conclude that sources external to the domain corpus are necessary for the automatic construction of ontologies.

miniDVMS v1.8 : A user manual(The data visualization and modeling system)

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. miniDVMS v1.8 provides a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualisation domain. The advantage of this interface is that the user is directly involved in the data mining process. Principled projection methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), are integrated with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, and user interaction facilities, to provide this integrated visual data mining framework. The software also supports conventional visualisation techniques such as principal component analysis (PCA), Neuroscale, and PhiVis. This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install and use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software.