Evolution Oriented Monitoring oriented to Security Properties for Cloud Applications

Internet is changing from an information space to a dynamic computing space. Data distribution and remotely accessible software services, dynamism, and autonomy are prime attributes. Cloud technology offers a powerful and fast growing approach to the provision of infrastructure (platform and software services) avoiding the high costs of owning, operating, and maintaining the computational infrastructures required for this purpose. Nevertheless, cloud technology still raises concerns regarding security, privacy, governance, and compliance of data and software services offered through it. Concerns are due to the difficulty to verify security properties of the different types of applications and services available through cloud technology, the uncertainty of their owners and users about the security of their services, and the applications based on them, once they are deployed and offered through a cloud. This work presents an innovative and novel evolution-oriented, cloud-specific monitoring model (including an architecture and a language) that aim at helping cloud application developers to design and monitor the behavior and functionality of their applications in a cloud environment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings

Models and metaphors: complexity theory and through-life management in the built environment

Complexity thinking may have both modelling and metaphorical applications in the through-life management of the built environment. These two distinct approaches are examined and compared. In the first instance, some of the sources of complexity in the design, construction and maintenance of the built environment are identified. The metaphorical use of complexity in management thinking and its application in the built environment are briefly examined. This is followed by an exploration of modelling techniques relevant to built environment concerns. Non-linear and complex mathematical techniques such as fuzzy logic, cellular automata and attractors, may be applicable to their analysis. Existing software tools are identified and examples of successful built environment applications of complexity modelling are given. Some issues that arise include the definition of phenomena in a mathematically usable way, the functionality of available software and the possibility of going beyond representational modelling. Further questions arising from the application of complexity thinking are discussed, including the possibilities for confusion that arise from the use of metaphor. The metaphor of a 'commentary machine' is suggested as a possible way forward and it is suggested that an appropriate linguistic analysis can in certain situations reduce perceived complexity

Take It To The Bank: How Land Banks Are Strengthening America's Neighborhoods

This report scans the land banking field nationally and reports on the scope and state of this movement. It also includes insights and recommendations for land bank practitioners, based on Community Progress staff members' many collective years of experience working with land banks across the country. There is no land bank model kit. There are, however, common attributes of effective and successful land banks that current and future land bank staff, practitioners, governments, and partner organizations can adopt. This report is intended to help shorten the learning curve

Evaluation of Neuro-Evolution Algorithms for Tactic Volatility Aware Processes

Our society is increasingly evolving to rely on computer mechanisms that perform a variety of tasks. From a self-driving car to a satellite in space relaying data from Mars rovers, we need these systems to perform optimally and without failure. One such point of failure these systems can encounter is tactic volatility of an adaptation tactic. Adaptation tactics are defined workflows that allow systems to navigate their environment. Tactic volatility is the variance in the behavior in the attribute of a tactic, such as cost and latency and/or the combination of the two. Current systems consider these tactic attributes to be static. Studies have shown that not accounting for tactic volatility can adversely affect a system\u27s ability to operate effectively and resiliently. To support self-adaptive systems and address their limitations, this paper proposes a Tactic Volatility Aware solution that utilizes eRNN (TVA-E) and addresses the limitations of current self-adaptive systems. For this research, we used real-world data that has been made available for use by researchers and academics. This data contains real-world volatility and helps us demonstrate the positive impact TVA-E when used in self-adaptive systems. We also employ the use of uncertainty reduction tactics and how they can assist in accounting for tactic volatility. This work will serve as an evaluation and a comparison of using different machine learning methods to predict and account for tactic volatility. We will study different predictive mechanisms in this paper: Auto-Regressive Moving Average(ARIMA), Evolving Recurrent Neural Network(eRNN), Multi-Layer Perceptron(MLP), and Support Vector Regression(SVR). These methods will be studied with our TVA-E process and we will analyze how they can enhance a self-adaptive system’s performance when it accounts for tactic volatility

An Examination of Manufactured Housing as a Community- and Asset-Building Strategy

An increasing share of lower-income families, the same population targeted by community-development organizations, are opting to live in housing that was built off-site in a factory to meet the performance standards of the national HUD manufactured-housing code. However, most community-development practitioners are just beginning to come to terms with the implications of manufactured housing for their work.This paper explores advantages and disadvantages of manufactured housing for those entities whose mission is community development and asset building. Several challenges are presented for practitioners: First, working to educate consumers while also creating financing processes that ensure manufactured home buyers obtain credit on the best terms for which they can qualify. Second, using the increased scrutiny under the Manufactured Housing Improvement Act of 2000 to advocate for states to enforce more rigorous installation standards and increased accountability. Third, working to overcome land-use controls which prevent manufactured homes from being placed in communities in need of affordable housing, as well as areas with more potential for appreciation. Fourth, working with designers and planners to develop innovative designs and housing developments, while maintaining manufactured housing's affordability advantages.Finally, equal effort must be devoted to address the difficult conditions of many lower-income people -- owners and renters alike -- living in older, and often deteriorating, mobile homes. While a few of these families and individuals could be relocated to new and better quality homes with the help of subsidies, resource limitations suggest the need to create cost-effective methods to eliminate health and safety problems by upgrading or rehabilitating this extremely affordable element of the nation's housing inventory.As a companion to this paper, an exhaustive literature review has been compiled

An IoT architecture for decision support system in precision livestock

Sustainable animal production is a primary goal of technological development in the livestock industry. However, it is crucial to master the livestock environment due to the susceptibility of animals to variables such as temperature and humidity, which can cause illness, production losses, and discomfort. Thus, livestock production systems require monitoring, reasoning, and mitigating unwanted conditions with automated actions. The principal contribution of this study is the introduction of a self-adaptive architecture named e-Livestock to handle animal production decisions. Two case studies were conducted involving a system derived from the e-Livestock architecture, encompassing a Compost Barn production system - an environment and technology where bovine milk production occurs. The outcomes demonstrate the effectiveness of e-Livestock in three key aspects: (i) abstraction of disruptive technologies based on the Internet of Things (IoT) and Artificial Intelligence and their incorporation into a single architecture specific to the livestock domain, (ii) support for the reuse and derivation of an adaptive self-architecture to support the engineering of a decision support system for the livestock subdomain, and (iii) support for empirical studies in a real smart farm to facilitate future technology transfer to the industry. Therefore, our research’s main contribution is developing an architecture combining machine learning techniques and ontology to support more complex decisions when considering a large volume of data generated on farms. The results revealed that the e-Livestock architecture could support monitoring, reasoning, forecasting, and automated actions in a milk production/Compost Barn environment.Na indústria pecuária, a produção animal sustentável é o principal objetivo do desenvolvimento tecnológico. Porém, é fundamental manter boas condições no ambiente devido à suscetibilidade dos animais a variáveis como temperatura e umidade, que podem causar doenças, perdas de produção e desconforto. Assim, os sistemas de produção pecuária requerem monitoramento, controle e mitigação das condições indesejadas através de ações automatizadas. A principal contribuição deste estudo é a introdução de uma arquitetura auto-adaptativa denominada e-Livestock para apoiar as decisões relacionadas à produção animal. Foram conduzidos dois estudos de caso, envolvendo a arquitetura e-Livestock, que foi utilizada no sistema de produção Compost Barn - ambiente e tecnologia onde ocorre a produção de gado leiteiro. Os resultados demonstraram a utilidade do e-Livestock para avaliar três aspectos principais: (i) abstração de tecnologias disruptivas baseadas em Internet das Coisas (IoT) e Inteligência Artificial, e sua incorporação em uma arquitetura única, específica para o domínio da pecuária, (ii) suporte para a reutilização e derivação de uma arquitetura auto-adaptativa para apoiar o desenvolvimento de uma aplicação de apoio à decisão para o subdomínio da pecuária e (iii) suporte para estudos empíricos em uma fazenda inteligente real para facilitar a transferência de tecnologia para a indústria. Portanto, a principal contribuição dessa pesquisa é o desenvolvimento de uma arquitetura combinando técnicas de machine learning e ontologia para apoiar decisões mais complexas ao considerar um grande volume de dados gerados nas fazendas. Os resultados revelaram que a arquitetura e-Livestock pode apoiar monitoramento, controle, previsão e ações automatizadas em um ambiente de produção de leite/Compost Barn.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

Waters of The Past & Present - The Revival of Water's Forgotten Stories, The Relationship of Water to Architectural Development For The Chiva Warin Center (River Life Center) By the Mae Ping River, Chiang Mai, Thailand

This Doctorate Project studies waterfront cities and proposes a new waterfront development in Chiang Mai, Thailand around an ancient river that is not used to its full potential. The Doctorate Project is divided into two components, one is the research component where precedent case cities are selected for their waterfront locations and the symbolism of water in Thai culture, and two the second component is the design project which is a New Chiang Mai Urban Waterfront Center master plan (The Chiva Warin Center By the Mae Ping River) to revive the urban linkage between a historical site which has been divided from lack of use and accessibility, growing disconnected from each other. The site location is on both sides of the Mae Ping River consisting of marketplace and institutional buildings on one side of the riverbank and an entertainment edge, heritage shop houses and residences on the other side. Objectives of Design Project: - Preserve culture and still show authenticity of heritage in context to time and site. Through analysis identify which areas of the site must be preserved and what is past regeneration so that it can be used as the design redevelopment areas. - Bring recognition to a river which has been part of the site's history. - Achieve this with a walkable and cultural corridor along the Mae Ping's edge. - Allow future floods through the new master plan with elevated boardwalks so that daily activities continues during the flood days