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

Geometric versus finite element modeling current and future trends at Northrop

Engineering Automation at Northrop encompasses the various design and analytical phases of air vehicle development. Design systems addresses automation of engineering/tooling design and computer aided manufacturing processes. The analysis systems automate aeroelastic modeling and postprocessing analysis results. These systems interface with aircraft loft and geometric entities thru localized transfer techniques. However, total integration effort based on a geometric database nucleus with peripheral design, analytical and manufacturing systems is well underway. An outline of the present and future trends is presented to help channel the RPI effort in this direction

Metrics, Software Engineering, Small Systems – the Future of Systems Development

In this talk I will introduce the importance of metrics, or measures, and the role they play in the development of high quality computer systems. I will review some key mega trends in computer science over the last three decades and then explain why I believe the trend to small networked systems, along with metrics and software engineering will define the future of high technology computer based systems. I first learned about metrics at the Bell System where everything was measured. Metrics can be understood easily if you think of them as measures, for example of calories or salt in food. Key system metrics include lines of code, productivity, known bugs or defects in systems, and predictions of how many defects remain to be found. Now small embedded systems such as watches and glasses are beginning their rise to importance. I expect wearable networks of small devices to replace and expand much of what we do with computers today. However, to do so successfully these systems will need better attention to system quality and reliability. Good software engineering, with attention to process and metrics that can produce high quality, reliable systems is the way to achieve this goal

Artificial Intelligence in Civil Engineering

Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering

A performance model for a local VoD system

Theme: Trends in Information Systems Engineering and Wireless Multimedia CommunicationsA multimedia information system provides an effective means to convey information to users. This paper studies the problem of carrying out video on demand (VoD) application over a high speed LAN to support Computer Supported Collaborative Working (CSCW) for people working in a local collaborative environment. A multimedia information system using HP 100VG-AnyLAN is proposed and setup for this purpose. Based on this system, a performance model is developed, which can be used to determine the requirement of network bandwidth and evaluate the system performance.published_or_final_versio

The development and technology transfer of software engineering technology at NASA. Johnson Space Center

The United State's big space projects of the next decades, such as Space Station and the Human Exploration Initiative, will need the development of many millions of lines of mission critical software. NASA-Johnson (JSC) is identifying and developing some of the Computer Aided Software Engineering (CASE) technology that NASA will need to build these future software systems. The goal is to improve the quality and the productivity of large software development projects. New trends are outlined in CASE technology and how the Software Technology Branch (STB) at JSC is endeavoring to provide some of these CASE solutions for NASA is described. Key software technology components include knowledge-based systems, software reusability, user interface technology, reengineering environments, management systems for the software development process, software cost models, repository technology, and open, integrated CASE environment frameworks. The paper presents the status and long-term expectations for CASE products. The STB's Reengineering Application Project (REAP), Advanced Software Development Workstation (ASDW) project, and software development cost model (COSTMODL) project are then discussed. Some of the general difficulties of technology transfer are introduced, and a process developed by STB for CASE technology insertion is described

An overview of computer-based natural language processing

Computer based Natural Language Processing (NLP) is the key to enabling humans and their computer based creations to interact with machines in natural language (like English, Japanese, German, etc., in contrast to formal computer languages). The doors that such an achievement can open have made this a major research area in Artificial Intelligence and Computational Linguistics. Commercial natural language interfaces to computers have recently entered the market and future looks bright for other applications as well. This report reviews the basic approaches to such systems, the techniques utilized, applications, the state of the art of the technology, issues and research requirements, the major participants and finally, future trends and expectations. It is anticipated that this report will prove useful to engineering and research managers, potential users, and others who will be affected by this field as it unfolds

A linear decomposition method for large optimization problems. Blueprint for development

A method is proposed for decomposing large optimization problems encountered in the design of engineering systems such as an aircraft into a number of smaller subproblems. The decomposition is achieved by organizing the problem and the subordinated subproblems in a tree hierarchy and optimizing each subsystem separately. Coupling of the subproblems is accounted for by subsequent optimization of the entire system based on sensitivities of the suboptimization problem solutions at each level of the tree to variables of the next higher level. A formalization of the procedure suitable for computer implementation is developed and the state of readiness of the implementation building blocks is reviewed showing that the ingredients for the development are on the shelf. The decomposition method is also shown to be compatible with the natural human organization of the design process of engineering systems. The method is also examined with respect to the trends in computer hardware and software progress to point out that its efficiency can be amplified by network computing using parallel processors