51,399 research outputs found
Understanding requirements engineering process: a challenge for practice and education
Reviews of the state of the professional practice in Requirements Engineering (RE) stress that the RE process is both complex and hard to describe, and suggest there is a significant difference between competent and "approved" practice. "Approved" practice is reflected by (in all likelihood, in fact, has its genesis in) RE education, so that the knowledge and skills taught to students do not match the knowledge and skills required and applied by competent practitioners.
A new understanding of the RE process has emerged from our recent study. RE is revealed as inherently creative, involving cycles of building and major reconstruction of the models developed, significantly different from the systematic and smoothly incremental process generally described in the literature. The process is better characterised as highly creative, opportunistic and insight driven. This mismatch between approved and actual practice provides a challenge to RE education - RE requires insight and creativity as well as technical knowledge. Traditional learning models applied to RE focus, however, on notation and prescribed processes acquired through repetition. We argue that traditional learning models fail to support the learning required for RE and propose both a new model based on cognitive flexibility and a framework for RE education to support this model
Critical evaluation of Jet-A spray combustion using propane chemical kinetics in gas turbine combustion simulated by KIVA-2
Jet-A spray combustion has been evaluated in gas turbine combustion with the use of propane chemical kinetics as the first approximation for the chemical reactions. Here, the numerical solutions are obtained by using the KIVA-2 computer code. The KIVA-2 code is the most developed of the available multidimensional combustion computer programs for application of the in-cylinder combustion dynamics of internal combustion engines. The released version of KIVA-2 assumes that 12 chemical species are present; the code uses an Arrhenius kinetic-controlled combustion model governed by a four-step global chemical reaction and six equilibrium reactions. Researchers efforts involve the addition of Jet-A thermophysical properties and the implementation of detailed reaction mechanisms for propane oxidation. Three different detailed reaction mechanism models are considered. The first model consists of 131 reactions and 45 species. This is considered as the full mechanism which is developed through the study of chemical kinetics of propane combustion in an enclosed chamber. The full mechanism is evaluated by comparing calculated ignition delay times with available shock tube data. However, these detailed reactions occupy too much computer memory and CPU time for the computation. Therefore, it only serves as a benchmark case by which to evaluate other simplified models. Two possible simplified models were tested in the existing computer code KIVA-2 for the same conditions as used with the full mechanism. One model is obtained through a sensitivity analysis using LSENS, the general kinetics and sensitivity analysis program code of D. A. Bittker and K. Radhakrishnan. This model consists of 45 chemical reactions and 27 species. The other model is based on the work published by C. K. Westbrook and F. L. Dryer
Profiling user activities with minimal traffic traces
Understanding user behavior is essential to personalize and enrich a user's
online experience. While there are significant benefits to be accrued from the
pursuit of personalized services based on a fine-grained behavioral analysis,
care must be taken to address user privacy concerns. In this paper, we consider
the use of web traces with truncated URLs - each URL is trimmed to only contain
the web domain - for this purpose. While such truncation removes the
fine-grained sensitive information, it also strips the data of many features
that are crucial to the profiling of user activity. We show how to overcome the
severe handicap of lack of crucial features for the purpose of filtering out
the URLs representing a user activity from the noisy network traffic trace
(including advertisement, spam, analytics, webscripts) with high accuracy. This
activity profiling with truncated URLs enables the network operators to provide
personalized services while mitigating privacy concerns by storing and sharing
only truncated traffic traces.
In order to offset the accuracy loss due to truncation, our statistical
methodology leverages specialized features extracted from a group of
consecutive URLs that represent a micro user action like web click, chat reply,
etc., which we call bursts. These bursts, in turn, are detected by a novel
algorithm which is based on our observed characteristics of the inter-arrival
time of HTTP records. We present an extensive experimental evaluation on a real
dataset of mobile web traces, consisting of more than 130 million records,
representing the browsing activities of 10,000 users over a period of 30 days.
Our results show that the proposed methodology achieves around 90% accuracy in
segregating URLs representing user activities from non-representative URLs
Results of recent NASA studies on automatic spin prevention for fighter aircraft
A broad based research program was developed to eliminate or minimize inadvertent spins for advanced military aircraft. Recent piloted simulator studies and airplane flight tests have demonstrated that the automatic control systems in use on current fighters can be tailored to provide a high degree of spin resistance for some configurations without restrictions to maneuverability. Such systems result in greatly increased tactical effectiveness, safety, and pilot confidence
Origin of conductivity cross over in entangled multi-walled carbon nanotube network filled by iron
A realistic transport model showing the interplay of the hopping transport
between the outer shells of iron filled entangled multi-walled carbon nanotubes
(MWNT) and the diffusive transport through the inner part of the tubes, as a
function of the filling percentage, is developed. This model is based on
low-temperature electrical resistivity and magneto-resistance (MR)
measurements. The conductivity at low temperatures showed a crossover from
Efros-Shklovski (E-S) variable range hopping (VRH) to Mott VRH in 3 dimensions
(3D) between the neighboring tubes as the iron weight percentage is increased
from 11% to 19% in the MWNTs. The MR in the hopping regime is strongly
dependent on temperature as well as magnetic field and shows both positive and
negative signs, which are discussed in terms of wave function shrinkage and
quantum interference effects, respectively. A further increase of the iron
percentage from 19% to 31% gives a conductivity crossover from Mott VRH to 3D
weak localization (WL). This change is ascribed to the formation of long iron
nanowires at the core of the nanotubes, which yields a long dephasing length
(e.g. 30 nm) at the lowest measured temperature. Although the overall transport
in this network is described by a 3D WL model, the weak temperature dependence
of inelastic scattering length expressed as L_phi ~T^-0.3 suggests the
possibility for the presence of one-dimensional channels in the network due to
the formation of long Fe nanowires inside the tubes, which might introduce an
alignment in the random structure.Comment: 29 pages,10 figures, 2 tables, submitted to Phys. Rev.
Mixing and Matching Learning Design and Learning Analytics
In the last five years, learning analytics has proved its potential in predicting academic performance based on trace data of learning activities. However, the role of pedagogical context in learning analytics has not been fully understood. To date, it has been difficult to quantify learning in a way that can be measured and compared. By coding the design of e-learning courses, this study demonstrates how learning design is being implemented on a large scale at the Open University UK, and how learning analytics could support as well as benefit from learning design. Building on our previous work, our analysis was conducted longitudinally on 23 undergraduate distance learning modules and their 40,083 students. The innovative aspect of this study is the availability of fine-grained learning design data at individual task level, which allows us to consider the connections between learning activities, and the media used to produce the activities. Using a combination of visualizations and social network analysis, our findings revealed a diversity in how learning activities were designed within and between disciplines as well as individual learning activities. By reflecting on the learning design in an explicit manner, educators are empowered to compare and contrast their design using their own institutional data
Luby Transform Coding Aided Iterative Detection for Downlink SDMA Systems
A Luby Transform (LT) coded downlink Spatial Division Multiple Access (SDMA) system using iterative detection is proposed, which invokes a low-complexity near-Maximum-Likelihood (ML) Sphere Decoder (SD). The Ethernet-based Internet section of the transmission chain inflicts random packet erasures, which is modelled by the Binary Erasure Channel (BEC), which the wireless downlink imposes both fading and noise. A novel log-Likelihood Ratio based packet reliability metric is used for identifying the channel-decoded packets, which are likely to be error-infested. Packets having residual errors must not be passed on to the KT decoder for the sake of avoiding LT-decoding –induced error propagation. The proposed scheme is capable of maintaining an infinitesimally low packet error ratio in the downlink of the wireless Internet for Eb/n0 values in excess of about 3dB
Applied analytical combustion/emissions research at the NASA Lewis Research Center
Emissions of pollutants from future commercial transports are a significant concern. As a result, the Lewis Research Center (LeRC) is investigating various low emission combustor technologies. As part of this effort, a combustor analysis code development program was pursued to guide the combustor design process, to identify concepts having the greatest promise, and to optimize them at the lowest cost in the minimum time
Continuing professional development for RMIT International University Vietnam library staff: Adding value through an international partnership: A case study
The aim of this study was to explore the effectiveness of blended learning - the fusion of face-to-face and online learning experiences - to implement an effective and culturally sensitive program of professional development in an Australian university working in a developing country. It sought insight into pertinent pedagogical approaches for staff development across multiple locations including across national boundaries. The project demonstrated how learners can develop new capabilities and approaches by building on existing skills and knowledge as they interact in communities of practice. The immediate purpose was to design and deliver a continuing professional education program to meet the needs of librarians working at RMIT International University Vietnam in the context of the demands of the academic community and in the light of the challenge library staff experienced in seeking to meet explicit and tacit expectations. The project ran from late January to mid December 2010. The research questions were: 'Is blended learning effective as an approach to continuing professional development when working across cultures in a multinational organization?' and 'What contribution do face-to-face and online components make to learning outcomes?' The methodology used was an action learning approach. A 2009 consultant's report into the RMIT Vietnam Library established professional developmental needs which were further detailed in February 2010 by the project leader from RMIT University, Melbourne using a skills audit. Workshops in Vietnam, visits to Melbourne by several Vietnam staff members, and an online forum were then delivered
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