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The policy-science nexus: An area for improved competence in leadership
No full textIt is a fantastic experience to understand basic principles for worthy goals
together-across disciplinary, professional, and ideological boundaries-and to
realize that we need each other in order to attain those goals. Conversely, it
is sobering that so few of our leaders know how to build full sustainability
into their decision making, and to shape their analyses, debates, action
programs, stakeholder alliances, economies, and summit meetings accordingly.
That deficiency is reflected in the questions put to scientists, who are often
caught in the middle of conflicting policy proposals. On such occasions,
empirical facts may be presented out of context and applied as arguments for
alternative solutions: for or against the rapid phase-out of fossil fuels, for
or against nuclear power, etc. This results in attempts to deal with one issue
at a time, often creating a new sustainability problem while "solving" another.
Strategic planning toward sustainability is not something that you simply pick
up as you go along, if only you are sufficiently engaged in public debate, have
a certain field of expertise, or remain faithful to a certain ideology. What is
needed today are decision makers who are open to learning the crucial
competence of strategic planning and the language that goes with it-a language
that makes multi-sectoral collaboration possible at the scale required for
success. Only then can leaders make their leadership relevant, cooperate
effectively across discipline and sector boundaries; and only then can they ask
the relevant questions of scientists and other experts. This is not
incompatible with a strong economy or with competitiveness. It is just the
opposite: We are now experiencing increasing costs and lost opportunities due
to lack of competence in strategic sustainable development. Such competence is
not incompatible with the freedom to embrace different values and ideologies,
or with the creative tensions that may arise from the confrontation of such
values and ideologies with each other. On the contrary, the potential value of
creative tensions increases when they are not rooted in lack of knowledge and
misunderstandings
Numerical Results on the Delay Performance of Cognitive Radio Networks for Point-to-point and Point-to-multipoint Communications
No full textIn our paper published in [1], the delay performance of cognitive radio
networks for point-to-point and point-to-multipoint communications have been
studied. In this report, additional numerical results are provided to give more
insights into the impact of system parameters on the delay performance of
the considered cognitive radio network scenarios
Socio-technical congruence sabotaged by a hidden onshore outsourcing relationship: Lessons learned from an empirical study
No full textDespite the popularity of outsourcing arrangements, distributed software
development is still regarded as a complex endeavor. Complexity primarily comes
from the challenges in communication and coordination among participating
organizations. In this paper we discuss lessons learned from participatory
research carried out in a highly distributed onshore outsourcing project.
Previous research established that socio-technical congruence principles
alleviate distributed work. In practice we have found that alignment between
the systems structure and organizational structure can be studied from
different abstraction levels and also during different phases of project
lifecycle. We have found that official organizational structure differed from
the applied one, which meant that the planned alignment in task allocation
strategies was broken. Our findings indicate that the lack of socio-technical
congruence caused several implications, including unclear responsibilities,
delays in problem turnaround, conflicting changes, and non-delivered parts
Fostering and sustaining innovation in a Fast Growing Agile Company
No full textSustaining innovation in a fast growing software development company is
difficult. As organisations grow, peoples' focus often changes from the big
picture of the product being developed to the specific role they fill. This
paper presents two complementary approaches that were successfully used to
support continued developer-driven innovation in a rapidly growing Australian
agile software development company. The method "FedEx TM Day" gives developers
one day to showcase a proof of concept they believe should be part of the
product, while the method "20% Time" allows more ambitious projects to be
undertaken. Given the right setting and management support, the two approaches
can support and improve bottom-up innovation in organizations
Veto-based Malware Detection
No full textMalicious software (malware) represents a threat to the security and privacy of
computer users. Traditional signature-based and heuristic-based methods are
unsuccessful in detecting some forms of malware. This paper presents a malware
detection approach based on supervised learning. The main contributions of the
paper are an ensemble learning algorithm, two pre-processing techniques, and an
empirical evaluation of the proposed algorithm. Sequences of operational codes
are extracted as features from malware and benign files. These sequences are
used to produce three different data sets
with different configurations. A set of learning algorithms is
evaluated on the data sets and the predictions are combined
by the ensemble algorithm. The predicted output is decided on
the basis of veto voting. The experimental results show that the
approach can accurately detect both novel and known malware
instances with higher recall in comparison to majority voting
A Delay-Based Double-Talk Detector
No full textWhen an adaptive filter is used for echo cancellation, it is essential to
prevent the filter from diverging in situations when the echo signal is
contaminated with near-end disturbance, i.e. during double-talk. This paper
presents an extension of a previously proposed double-talk detector for
improved performance. It is shown that the computational complexity of the
proposed detector is lower than that of the well-used normalized cross
correlation (NCC) double-talk detector, at the cost of performance. Further, it
is shown that there can be a significant performance difference, in terms of
detecting double-talk, between having a fixed echo cancellation filter, which
is a common strategy in objective evaluation techniques, and an adaptive
filter, which is more close to realistic conditions
Cognitive Radio Networks
No full textCognitive Radio Networks (CRNs) are emerging as a solution to increase the
spectrum utilization by using unused or less used spectrum in radio
environments. The basic idea is to allow unlicensed users access to licensed
spectrum, under the condition that the interference perceived by the licensed
users is minimal. New communication and networking technologies need to be
developed, to allow the use of the spectrum in a more efficient way and to
increase the spectrum utilization. This means that a number of technical
challenges must be solved for this technique to get acceptance. The most
important issues are regarding Dynamic Spectrum Access (DSA), architectural
issues (with focus on network reconfigurability), deployment of smaller cells
and security
User Impatience and Network Performance
No full textIn this work, we analyze from passive measurements the correlations between the
user-induced interruptions of TCP connections and different end-to-end
performance metrics. The aim of this study is to assess the possibility for a
network operator to take into account the customers' experience for network
monitoring. We first observe that the usual connection-level performance
metrics of the interrupted connections are not very different, and sometimes
better than those of normal connections. However, the request-level performance
metrics show stronger correlations between the interruption rates and the
network quality-of-service. Furthermore, we show that the user impatience could
also be used to characterize the relative sensitivity of data applications to
various network performance metrics
Decision Support for Estimation of the Utility of Software and E-mail
No full textBackground: Computer users often need to distinguish between good and bad
instances of software and e-mail messages without the aid of experts. This
decision process is further complicated as the perception of spam and spyware
varies between individuals. As a consequence, users can benefit from using a
decision support system to make informed decisions concerning whether an
instance is good or bad.
Objective: This thesis investigates approaches for estimating the utility of
e-mail and software. These approaches can be used in a personalized decision
support system. The research investigates the performance and accuracy of the
approaches.
Method: The scope of the research is limited to the legal grey- zone of
software and e-mail messages. Experimental data have been collected from
academia and industry. The research methods used in this thesis are simulation
and experimentation. The processing of user input, along with malicious user
input, in a reputation system for software were investigated using simulations.
The preprocessing optimization of end user license agreement classification was
investigated using experimentation. The impact of social interaction data in
regards to personalized e-mail classification was also investigated using
experimentation.
Results: Three approaches were investigated that could be adapted for a
decision support system. The results of the investigated reputation system
suggested that the system is capable, on average, of producing a
rating ±1 from an objects correct rating. The results of the preprocessing
optimization of end user license agreement classification suggested negligible
impact. The results of using social interaction information in e-mail
classification suggested that accurate spam detectors can be generated from the
low-dimensional social data model alone, however, spam detectors generated from
combinations of the traditional and social models were more accurate.
Conclusions: The results of the presented approaches suggestthat it is possible
to provide decision support for detecting software that might be of low utility
to users. The labeling of instances of software and e-mail messages that are in
a legal grey-zone can assist users in avoiding an instance of low utility, e.g.
spam and spyware. A limitation in the approaches is that isolated
implementations will yield unsatisfactory results in a real world setting. A
combination of the
approaches, e.g. to determine the utility of software, could yield improved
results
Non-Intrusive Network-Based Estimation of Web Quality of Experience Indicators
No full textQuality of Experience (QoE) deals with the acceptance of a service quality by
the users and has evolved significantly as an important concept over the past
10 years. Network operators and service providers have gained interest in
QoE-aware management of networks, in order to better fulfill end-user demands
and gain a competitive edge in the market. While this growth promises new
business opportunities, it also presents several challenges to the networking
researchers, which are mainly related to the assessment of user experience.
Several QoE assessment models have been proposed to estimate the user
satisfaction for a given service quality. Most of them are intrusive and
require knowledge of the content reference. In contrast, the network operators
require non-intrusive methods, which allow models to be implementable on the
network-level without having much knowledge about that reference. The methods
should be able to monitor QoE passively in real-time, based on the information
readily available on network level.
This thesis investigates indicators, which are intended to be used in the
development of non-intrusive network-based methods for the real-time QoE
assessment and monitoring. First, a bridge is made between the user and the
network perspectives by correlating the user traffic characteristics measured
on an operational network and user subjective experience tested on an
experimental platform. It is shown that the user session volume appears to be
an indicator of users’ interest in the service. Second, the TCP connection
interruptions are investigated as an indicator to infer the user experience. It
is found out that the request-level performance metrics show stronger
correlations between the interruption rates and the network Quality of Service
(QoS). Third, a wavelet-based criterion is devised to assist in the
identification of those traffic gaps, which may result in the degradation of
QoE. It can be implemented on the network-level in quasi-real-time to quickly
identify the user-perceived performance issues