Industry-driven innovative system development for the construction industry: The DIVERCITY project

Collaborative working has become possible using the innovative integrated systems in construction as many activities are performed globally with stakeholders situated in various locations. The Integrated VR based information systems can bind the fragmentation and provide communication and collaboration between the distributed stakeholders n various locations. The development of these technologies is vital for the uptake of these systems by the construction industry. This paper starts by emphasising the importance of construction IT research and reviews some future research directions in this area. In particular, the paper explores how virtual prototyping can improve the productivity and effectiveness of construction projects, and presents DIVERCITY, which is th as a case study of the research in virtual prototyping. Besides, the paper explores the requirements engineering of the DIVERCITY project. DIVERCITY has large and evolving requirements, which considered the perspectives of multiple stakeholders, such as clients, architects and contractors. However, practitioners are often unsure of the detail of how virtual environments would support the construction process, and how to overcome some barriers to the introduction of new technologies. This complicates the requirements engineering process

Study to determine potential flight applications and human factors design guidelines for voice recognition and synthesis systems

A study was conducted to determine potential commercial aircraft flight deck applications and implementation guidelines for voice recognition and synthesis. At first, a survey of voice recognition and synthesis technology was undertaken to develop a working knowledge base. Then, numerous potential aircraft and simulator flight deck voice applications were identified and each proposed application was rated on a number of criteria in order to achieve an overall payoff rating. The potential voice recognition applications fell into five general categories: programming, interrogation, data entry, switch and mode selection, and continuous/time-critical action control. The ratings of the first three categories showed the most promise of being beneficial to flight deck operations. Possible applications of voice synthesis systems were categorized as automatic or pilot selectable and many were rated as being potentially beneficial. In addition, voice system implementation guidelines and pertinent performance criteria are proposed. Finally, the findings of this study are compared with those made in a recent NASA study of a 1995 transport concept

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Reasoning about the Reliability of Diverse Two-Channel Systems in which One Channel is "Possibly Perfect"

This paper considers the problem of reasoning about the reliability of fault-tolerant systems with two "channels" (i.e., components) of which one, A, supports only a claim of reliability, while the other, B, by virtue of extreme simplicity and extensive analysis, supports a plausible claim of "perfection." We begin with the case where either channel can bring the system to a safe state. We show that, conditional upon knowing pA (the probability that A fails on a randomly selected demand) and pB (the probability that channel B is imperfect), a conservative bound on the probability that the system fails on a randomly selected demand is simply pA.pB. That is, there is conditional independence between the events "A fails" and "B is imperfect." The second step of the reasoning involves epistemic uncertainty about (pA, pB) and we show that under quite plausible assumptions, a conservative bound on system pfd can be constructed from point estimates for just three parameters. We discuss the feasibility of establishing credible estimates for these parameters. We extend our analysis from faults of omission to those of commission, and then combine these to yield an analysis for monitored architectures of a kind proposed for aircraft

Air Force Institute of Technology Research Report 2006

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

Software quality is an important research area and has gain considerable attention from software engineering community in identification of priority quality attributes in software development process. This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. The proposed algorithm is able to improve the weaknesses in PQF model in updating and learning the important attributes for software quality assessment. The existing assessment techniques lack of the capability to rank the quality attributes and data learning which can enhance the quality assessment process. The aim of the study is to identify and propose the application of Artificial Intelligence (AI) technique for improving quality assessment technique in PQF model. Therefore, FRA using FRT was constructed and the performance of the FRA was evaluated. The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. The result shows that the performance of FRA correlates strongly to PQF model with 98% correlation compared to the Kolmogorov-Smirnov Correlation Based Filter (KSCBF) algorithm with 83% correlation. Statistical significance test was also performed with score of 0.052 compared to the KSCBF algorithm with score of 0.048. The result shows that the FRA was more significant than KSCBF algorithm. The main contribution of this research is on the implementation of FRT with proposed Most Priority of Features (MPF) calculation in FRA for attributes assessment. Overall, the findings and contributions can be regarded as a novel effort in software quality for attributes selection