Adaptive generalized predictive control algorithm implemented over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies

Identifying the genetic changes driving adaptive variation in natural populations is key to understanding the origins of biodiversity. The mosaic of mimetic wing patterns in Heliconius butterflies makes an excellent system for exploring adaptive variation using next-generation sequencing. In this study, we use a combination of techniques to annotate the genomic interval modulating red color pattern variation, identify a narrow region responsible for adaptive divergence and convergence in Heliconius wing color patterns, and explore the evolutionary history of these adaptive alleles. We use whole genome resequencing from four hybrid zones between divergent color pattern races of Heliconius erato and two hybrid zones of the co-mimic Heliconius melpomene to examine genetic variation across 2.2 Mb of a partial reference sequence. In the intergenic region near optix, the gene previously shown to be responsible for the complex red pattern variation in Heliconius, population genetic analyses identify a shared 65-kb region of divergence that includes several sites perfectly associated with phenotype within each species. This region likely contains multiple cis-regulatory elements that control discrete expression domains of optix. The parallel signatures of genetic differentiation in H. erato and H. melpomene support a shared genetic architecture between the two distantly related co-mimics; however, phylogenetic analysis suggests mimetic patterns in each species evolved independently. Using a combination of next-generation sequencing analyses, we have refined our understanding of the genetic architecture of wing pattern variation in Heliconius and gained important insights into the evolution of novel adaptive phenotypes in natural populations.

Modeling requirement driven architecture of adaptive healthcare system based on semiotics

In order to improve the quality of healthcare services, the integrated large-scale medical information system is needed to adapt to the changing medical environment. In this paper, we propose a requirement driven architecture of healthcare information system with hierarchical architecture. The system operates through the mapping mechanism between these layers and thus can organize functions dynamically adapting to user’s requirement. Furthermore, we introduce the organizational semiotics methods to capture and analyze user’s requirement through ontology chart and norms. Based on these results, the structure of user’s requirement pattern (URP) is established as the driven factor of our system. Our research makes a contribution to design architecture of healthcare system which can adapt to the changing medical environment.

An adaptive information grid architecture for recommendation system

This paper presents an adaptive information grid architecture for recommendation systems, which consists of the features of the recommendation rule and a co-citation algorithm. The algorithm addresses some challenges that are essential for further searching and recommendation algorithms. It does not require users to provide a lot of interactive communication. Furthermore, it supports other queries, such as keyword, URL and document investigations. When the structure is compared to other algorithms, the scalability is noticeably better. The high online performance can be obtained as well as the repository computation, which can achieve a high group-forming accuracy using only a fraction of web pages from a cluster.

Towards a renewable adaptive recyclable and environmental architecture

Research in pursuit of an effective response to the demands for a sustainable architecture has lead towards the conception of a Renewable, Adaptive, Recyclable and Environmental (R.A.R.E.) building typology. The term R.A.R.E. expresses issues that have assumed central importance in the current architectural debate. This paper establishes the principles of the typology, drawing on the contents and pedagogical methods applied in a building technology academic course, at fourth year level. The R.A.R.E methodology is presented to and explored by students in the search for a definition of an innovative architecture, which is both progressive and sustainable. The unit is structured into eight subjects: Sustainable Site & Climate Analysis; Flexible & Adaptive Structural Systems; Renewable & Environmental Building Materials; Modular Building Systems; Innovative Building Envelope Systems; Renewable & Non-conventional Energy Systems; Innovative Heating, Ventilation & Air Conditioning Systems; Water Collection & Storage Systems. Through a holistic and integrated approach, the unit presents a comprehensive overview of these ‘Sustainable Building Categories’, so that the students can produce a guide towards the design requirements of a Renewable, Adaptive, Recyclable and Environmental (R.A.R.E.) Architecture.

A roadmap to Renewable Adaptive Recyclable Environmental (R.A.R.E.) architecture

R.A.R.E. stands for Renewable Adaptive Recyclable Environmental Architecture; the acronym expresses a demand that is becoming increasingly important today in the eyes of designers and clients. The paper draws on the contents and the pedagogical methods applied in a Building Technology Unit (SRT 450) – at forth year level – at the School of Architecture and Building, Deakin University, Australia. The unit is basically structured upon eight subjects derived as relevant to the research and development for a R.A.R.E. Architecture: Sustainable Site & Climate Analysis; Flexible & Adaptive Structural Systems; Renewable Adaptive & Environmental Building Materials; Modular Building Systems; Innovative Building Envelope Systems; Renewable or Non-conventional Energy Systems; Innovative Heating, Ventilation & Air Conditioning; Water Storage & Systems. The overall objective of the unit is to present a comprehensive overview of all these Sustainable Building Categories (SBCs) so that the students can produce a guide towards the design of a R.A.R.E. Architecture. The push towards a holistic and integrated approach will contribute to the definition of an innovative architecture, which is both progressive and sustainable.

Architecture of adaptive spam filtering based on machine learning algorithms

Spam is commonly defined as unsolicited email messages and the goal of spam filtering is to distinguish between spam and legitimate email messages. Much work has been done to filter spam from legitimate emails using machine learning algorithm and substantial performance has been achieved with some amount of false positive (FP) tradeoffs. In the case of spam detection FP problem is unacceptable sometimes. In this paper, an adaptive spam filtering model has been proposed based on Machine learning (ML) algorithms which will get better accuracy by reducing FP problems. This model consists of individual and combined filtering approach from existing well known ML algorithms. The proposed model considers both individual and collective output and analyzes them by an analyzer. A dynamic feature selection (DFS) technique also proposed in this paper for getting better accuracy.

A Reference Architecture based on Reflection for Self-adaptive Software

Self-adaptive Software (SaS) presents specific characteristics compared to traditional ones, as it makes possible adaptations to be incorporated at runtime. These adaptations, when manually performed, normally become an onerous, error-prone activity. In this scenario, automated approaches have been proposed to support such adaptations; however, the development of SaS is not a trivial task. In parallel, reference architectures are reusable artifacts that aggregate the knowledge of architectures of software systems in specific domains. They have facilitated the development, standardization, and evolution of systems of those domains. In spite of their relevance, in the SaS domain, reference architectures that could support a more systematic development of SaS are not found yet. Considering this context, the main contribution of this paper is to present a reference architecture based on reflection for SaS, named RA4SaS (Reference Architecture for SaS). Its main purpose is to support the development of SaS that presents adaptations at runtime. To show the viability of this reference architecture, a case study is presented. As result, it has been observed that RA4SaS has presented good perspective to efficiently contribute to the area of SaS.

A Fast Reconfigurable 2D HW Core Architecture on FPGAs for Evolvable Self- Adaptive Systems

Modern FPGAs with Dynamic and Partial Reconfiguration (DPR) feature allow the implementation of complex, yet flexible, hardware systems. Combining this flexibility with evolvable hardware techniques, real adaptive systems, able to reconfigure themselves according to environmental changes, can be envisaged. In this paper, a highly regular and modular architecture combined with a fast reconfiguration mechanism is proposed, allowing the introduction of dynamic and partial reconfiguration in the evolvable hardware loop. Results and use case show that, following this approach, evolvable processing IP Cores can be built, providing intensive data processing capabilities, improving data and delay overheads with respect to previous proposals. Results also show that, in the worst case (maximum mutation rate), average reconfiguration time is 5 times lower than evaluation time.

Using architecture models to support the generation and operation of component-based adaptive systems

Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

Architecture and Implementation of Reporting Means in Adaptive Dynamically Extended Information Systems

This article describes architecture and implementation of subsystem intended for working with queries and reports in adaptive dynamically extended information systems able to dynamically extending. The main features of developed approach are application universality, user orientation and opportunity to integrate with external information systems. Software implementation is based on multilevel metadata approach.

A Semantic-Oriented Architecture of a Functional Module for Personalized and Adaptive Access to the Knowledge in a Multimedia Digital Library

This article presents the principal results of the doctoral thesis “Semantic-oriented Architecture and Models for Personalized and Adaptive Access to the Knowledge in Multimedia Digital Library” by Desislava Ivanova Paneva-Marinova (Institute of Mathematics and Informatics), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 27 October, 2008.