A scalable evolvable hardware processing array

Evolvable hardware (EH) is an interesting alternative to conventional digital circuit design, since autonomous generation of solutions for a given task permits self-adaptivity of the system to changing environments, and they present inherent fault tolerance when evolution is intrinsically performed. Systems based on FPGAs that use Dynamic and Partial Reconfiguration (DPR) for evolving the circuit are an example. Also, thanks to DPR, these systems can be provided with scalability, a feature that allows a system to change the number of allocated resources at run-time in order to vary some feature, such as performance. The combination of both aspects leads to scalable evolvable hardware (SEH), which changes in size as an extra degree of freedom when trying to achieve the optimal solution by means of evolution. The main contributions of this paper are an architecture of a scalable and evolvable hardware processing array system, some preliminary evolution strategies which take scalability into consideration, and to show in the experimental results the benefits of combined evolution and scalability. A digital image filtering application is used as use case.

Epigenetic variability in the genetically uniform forest tree species Pinus pinea L

There is an increasing interest in understanding the role of epigenetic variability in forest species and how it may contribute to their rapid adaptation to changing environments. In this study we have conducted a genome-wide analysis of cytosine methylation pattern in Pinus pinea, a species characterized by very low levels of genetic variation and a remarkable degree of phenotypic plasticity. DNA methylation profiles of different vegetatively propagated trees from representative natural Spanish populations of P. pinea were analyzed with the Methylation Sensitive Amplified Polymorphism (MSAP) technique. A high degree of cytosine methylation was detected (64.36% of all scored DNA fragments). Furthermore, high levels of epigenetic variation were observed among the studied individuals. This high epigenetic variation found in P. pinea contrasted with the lack of genetic variation based on Amplified Fragment Length Polymorphism (AFLP) data. In this manner, variable epigenetic markers clearly discriminate individuals and differentiates two well represented populations while the lack of genetic variation revealed with the AFLP markers fail to differentiate at both, individual or population levels. In addition, the use of different replicated trees allowed identifying common polymorphic methylation sensitive MSAP markers among replicates of a given propagated tree. This set of MSAPs allowed discrimination of the 70% of the analyzed trees.

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Forming classes by stimulus frequency: Behavior and theory

Visual classification is the way we relate to different images in our environment as if they were the same, while relating differently to other collections of stimuli (e.g., human vs. animal faces). It is still not clear, however, how the brain forms such classes, especially when introduced with new or changing environments. To isolate a perception-based mechanism underlying class representation, we studied unsupervised classification of an incoming stream of simple images. Classification patterns were clearly affected by stimulus frequency distribution, although subjects were unaware of this distribution. There was a common bias to locate class centers near the most frequent stimuli and their boundaries near the least frequent stimuli. Responses were also faster for more frequent stimuli. Using a minimal, biologically based neural-network model, we demonstrate that a simple, self-organizing representation mechanism based on overlapping tuning curves and slow Hebbian learning suffices to ensure classification. Combined behavioral and theoretical results predict large tuning overlap, implicating posterior infero-temporal cortex as a possible site of classification.

Reproductive systems and evolution in vascular plants

Differences in the frequency with which offspring are produced asexually, through self-fertilization and through sexual outcrossing, are a predominant influence on the genetic structure of plant populations. Selfers and asexuals have fewer genotypes within populations than outcrossers with similar allele frequencies, and more genetic diversity in selfers and asexuals is a result of differences among populations than in sexual outcrossers. As a result of reduced levels of diversity, selfers and asexuals may be less able to respond adaptively to changing environments, and because genotypes are not mixed across family lineages, their populations may accumulate deleterious mutations more rapidly. Such differences suggest that selfing and asexual lineages may be evolutionarily short-lived and could explain why they often seem to be of recent origin. Nonetheless, the origin and maintenance of different reproductive modes must be linked to individual-level properties of survival and reproduction. Sexual outcrossers suffer from a cost of outcrossing that arises because they do not contribute to selfed or asexual progeny, whereas selfers and asexuals may contribute to outcrossed progeny. Selfing and asexual reproduction also may allow reproduction when circumstances reduce opportunities for a union of gametes produced by different individuals, a phenomenon known as reproductive assurance. Both the cost of outcrossing and reproductive assurance lead to an over-representation of selfers and asexuals in newly formed progeny, and unless sexual outcrossers are more likely to survive and reproduce, they eventually will be displaced from populations in which a selfing or asexual variant arises.

Diversity of Symbiodinium dinoflagellate symbionts from the Indo-Pacific sea slug Pteraeolidia ianthina (Gastropoda : Mollusca)

The aeolid nudibranch Pteraeolidia ianthina hosts symbiotic dinoflagellates in the same way as many reef-building corals. This widespread Indo-Pacific sea slug ranges from tropical to temperate waters, and offers a unique opportunity to examine a symbiosis that occurs over a large latitudinal gradient. We used partial 28S and 18S nuclear ribosomal (nr) DNA to examine the genetic diversity of the Symbiodinium dinoflagellates contained within F ianthina. We detected Symbiodinium from genetic clades A, B, C and D. P. ianthina from tropical regions (Singapore, Sulawesi) host Symbiodinium clade C or D or both; those from the subtropical eastern Australian coast (Heron Island, Mon Repo, Moreton Bay, Tweed Heads) host Symbiodinium clade C, but those from the temperate southeastern Australian coastline (Port Stephens, Bare Island) host clade A or B or both. The Symbiodinium populations within 1 individual nudibranch could be homogeneous or heterogeneous at inter- or intra-clade levels (or both). Our results suggested that the Pteraeolidia-Symbiodinium symbiosis is flexible and favours symbiont phylotypes best adapted for that environment. This flexibility probably reflects the function of the symbiont clade in relation to the changing environments experienced along the latitudinal range, and facilitates the large geographic range of P. ianthina.

Capabilities for strategic flexibility:a cognitive content framework

Different forms of strategic flexibility allow for reactive adaptation to different changing environments and the proactive driving of change. It is therefore becoming increasingly important for decision makers to not only possess marketing capabilities, but also the capabilities for strategic flexibility in its various forms. However, our knowledge of the relationships between decision makers’ different ways of thinking and their capabilities for strategic flexibility is limited. This limitation is constraining research and understanding. In this article we develop a theoretical cognitive content framework that postulates relationships between different ways of thinking about strategy and different information-processing demands. We then outline how the contrasting beliefs of decision makers may influence their capabilities to generate different hybrid forms of strategic flexibility at the cognitive level. Theoretically, the framework is embedded in resource-based theory, personal construct theory and schema theory. The implications for research and theory are discussed.

The impact of performance measurement in strategic planning

Purpose – To investigate the impact of performance measurement in strategic planning process. Design/methodology/approach – A large scale survey was conducted online with Warwick Business School alumni. The questionnaire was based on the Strategic Development Process model by Dyson. The questionnaire was designed to map the current practice of strategic planning and to determine its most influential factors on the effectiveness of the process. All questions were close ended and a seven-point Likert scale used. The independent variables were grouped into four meaningful factors by factor analysis (Varimax, coefficient of rotation 0.4). The factors produced were used to build regression models (stepwise) for the five assessments of strategic planning process. Regression models were developed for the totality of the responses, comparing SMEs and large organizations and comparing organizations operating in slowly and rapidly changing environments. Findings – The results indicate that performance measurement stands as one of the four main factors characterising the current practice of strategic planning. This research has determined that complexity coming from organizational size and rate of change in the sector creates variation in the impact of performance measurement in strategic planning. Large organizations and organizations operating in rapidly changing environments make greater use of performance measurement. Research limitations/implications – This research is based on subjective data, therefore the conclusions do not concern the impact of strategic planning process' elements on the organizational performance achievements, but on the success/effectiveness of the strategic planning process itself. Practical implications – This research raises a series of questions about the use and potential impact of performance measurement, especially in the categories of organizations that are not significantly influenced by its utilisation. It contributes to the field of performance measurement impact. Originality/value – This research fills in the gap literature concerning the lack of large scale surveys on strategic development processes and performance measurement. It also contributes in the literature of this field by providing empirical evidences on the impact of performance measurement upon the strategic planning process.

Strategy paradigms for the management of quality:dealing with complexity

Quality management is dominated by rational paradigms for the measurement and management of quality, but these paradigms start to “break down”, when faced with the inherent complexity of managing quality in intensely competitive changing environments. In this article, the various theoretical strategy paradigms employed to manage quality are reviewed and the advantages and limitations of these paradigms are highlighted. A major implication of this review is that when faced with complexity, an ideological stance to any single strategy paradigm for the management of quality is ineffective. A case study is used to demonstrate the need for an integrative multi-paradigm approach to the management of quality as complexity increases.

Goal-based modeling of dynamically adaptive system requirements

Self-adaptation is emerging as an increasingly important capability for many applications, particularly those deployed in dynamically changing environments, such as ecosystem monitoring and disaster management. One key challenge posed by Dynamically Adaptive Systems (DASs) is the need to handle changes to the requirements and corresponding behavior of a DAS in response to varying environmental conditions. Berry et al. previously identified four levels of RE that should be performed for a DAS. In this paper, we propose the Levels of RE for Modeling that reify the original levels to describe RE modeling work done by DAS developers. Specifically, we identify four types of developers: the system developer, the adaptation scenario developer, the adaptation infrastructure developer, and the DAS research community. Each level corresponds to the work of a different type of developer to construct goal model(s) specifying their requirements. We then leverage the Levels of RE for Modeling to propose two complementary processes for performing RE for a DAS. We describe our experiences with applying this approach to GridStix, an adaptive flood warning system, deployed to monitor the River Ribble in Yorkshire, England.

Semantic reasoning for autonomic IT systems

Autonomic systems are required to adapt continually to changing environments and user goals. This process involves the real-Time update of the system's knowledge base, which should therefore be stored in a machine-readable format and automatically checked for consistency. OWL ontologies meet both requirements, as they represent collections of knowl- edge expressed in FIrst order logic, and feature embedded reasoners. To take advantage of these OWL ontology char- acteristics, this PhD project will devise a framework com- prising a theoretical foundation, tools and methods for de- veloping knowledge-centric autonomic systems. Within this framework, the knowledge storage and maintenance roles will be fulfilled by a specialised class of OWL ontologies. ©2014 ACM.

Conservation implications of the reproductive biology of the endangered vine Ipomoea microdactyla Griseb. (Convolvulaceae)

A plant's reproductive biology exerts a significant influence on both population persistence within changing environments and successful establishment of new populations. However, the interaction between extrinsic (i.e. ecological) and intrinsic (i.e. genetic) factors also is an important driver of demographic performance for plant populations. It is light of this that I performed a multidisciplinary investigation of the breeding system, seed and seedling establishment dynamics, and population genetic structure of the endangered Caribbean vine Ipomoea microdactyla Griseb. (Convolvulaceae). The results from the breeding system study show individuals from Florida, USA and Andros Island, Bahamas to be self-incompatible. Plants from the two regions are cross-compatible but there is evidence for outbreeding depression in their progeny. Significant regional differences were found in floral traits and progeny traits that suggests incipient speciation for the Florida populations. The results from the seed and seedling establishment dynamics experiment demonstrate that the restoration of small populations in Florida via seed and seedling augmentation is a successful strategy. The demographic performance of the outplanted individuals was driven significantly by ecological factors (e.g. herbivory) rather than by genetic factors which emphasizes that the ecological context is very important for successful restoration attempts. The results from the population genetic study using an analysis of molecular variation (AMOVA) reveal significant differences in genetic variation among individuals from Florida, Andros, and Cuba. A Bayesian analysis of population genetic structuring coincided with the previous AMOVA results among the three regions. The Mantel test indicated significant 'isolation by distance' for these regional populations implying restricted gene flow over relatively short distances. Overall, the Florida populations had the lowest measures of genetic diversity which is most likely due to the effects of both colonization founder events and habitat fragmentation. The results of my study highlight the value of performing multidisciplinary studies in relation to species conservation as knowledge of both extrinsic and intrinsic factors can best guide decisions for species preservation.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Who Shook Big Mac?: Panera Bread Co.

The authors identify the firm-specific core competencies that Panera Bread has relied on to achieve a competitive advantage in its business domain. The study illustrates how the company scans the dynamically changing environments and tailors their products and services in accordance with these changes.