Algebraic analysis of small Scale LEX-BES

This work examines the algebraic cryptanalysis of small scale variants of the LEX-BES. LEX-BES is a stream cipher based on the Advanced Encryption Standard (AES) block cipher. LEX is a generic method proposed for constructing a stream cipher from a block cipher, initially introduced by Biryukov at eSTREAM, the ECRYPT Stream Cipher project in 2005. The Big Encryption System (BES) is a block cipher introduced at CRYPTO 2002 which facilitates the algebraic analysis of the AES block cipher. In this article, experiments were conducted to find solutions of equation systems describing small scale LEX-BES using Gröbner Basis computations. This follows a similar approach to the work by Cid, Murphy and Robshaw at FSE 2005 that investigated algebraic cryptanalysis on small scale variants of the BES. The difference between LEX-BES and BES is that due to the way the keystream is extracted, the number of unknowns in LEX-BES equations is fewer than the number in BES. As far as the authors know, this attempt is the first at creating solvable equation systems for stream ciphers based on the LEX method using Gröbner Basis computations.

New media services : ratings and recommendations websites in the travel and tourism industry

The travel and hospitality industry is one which relies especially crucially on word of mouth, both at the level of overall destinations (Australia, Queensland, Brisbane) and at the level of travellers’ individual choices of hotels, restaurants, sights during their trips. The provision of such word-of-mouth information has been revolutionised over the past decade by the rise of community-based Websites which allow their users to share information about their past and future trips and advise one another on what to do or what to avoid during their travels. Indeed, the impact of such user-generated reviews, ratings, and recommendations sites has been such that established commercial travel advisory publishers such as Lonely Planet have experienced a pronounced downturn in sales ¬– unless they have managed to develop their own ways of incorporating user feedback and contributions into their publications. This report examines the overall significance of ratings and recommendation sites to the travel industry, and explores the community, structural, and business models of a selection of relevant ratings and recommendations sites. We identify a range of approaches which are appropriate to the respective target markets and business aims of these organisations, and conclude that there remain significant opportunities for further operators especially if they aim to cater for communities which are not yet appropriately served by specific existing sites. Additionally, we also point to the increasing importance of connecting stand-alone ratings and recommendations sites with general social media spaces like Facebook, Twitter, and LinkedIn, and of providing mobile interfaces which enable users to provide updates and ratings directly from the locations they happen to be visiting. In this report, we profile the following sites: * TripAdvisor, the international market leader for travel ratings and recommendations sites, with a membership of some 11 million users; * IgoUgo, the other leading site in this field, which aims to distinguish itself from the market leader by emphasising the quality of its content; * Zagat, a long-established publisher of restaurant guides which has translated its crowdsourcing model from the offline to the online world; * Lonely Planet’s Thorn Tree site, which attempts to respond to the rise of these travel communities by similarly harnessing user-generated content; * Stayz, which attempts to enhance its accommodation search and booking services by incorporating ratings and reviews functionality; and * BigVillage, an Australian-based site attempting to cater for a particularly discerning niche of travellers; * Dopplr, which connects travel and social networking in a bid to pursue the lucrative market of frequent and business travellers; * Foursquare, which builds on its mobile application to generate a steady stream of ‘check-ins’ and recommendations for hospitality and other services around the world; * Suite 101, which uses a revenue-sharing model to encourage freelance writers to contribute travel writing (amongst other genres of writing); * Yelp, the global leader in general user-generated product review and recommendation services. In combination, these profiles provide an overview of current developments in the travel ratings and recommendations space (and beyond), and offer an outlook for further possibilities. While no doubt affected by the global financial downturn and the reduction in travel that it has caused, travel ratings and recommendations remain important – perhaps even more so if a reduction in disposable income has resulted in consumers becoming more critical and discerning. The aggregated word of mouth from many tens of thousands of travellers which these sites provide certainly has a substantial influence on their users. Using these sites to research travel options has now become an activity which has spread well beyond the digirati. The same is true also for many other consumer industries, especially where there is a significant variety of different products available – and so, this report may also be read as a case study whose findings are able to be translated, mutatis mutandis, to purchasing decisions from household goods through consumer electronics to automobiles.

Robust multidisciplinary design optimisation using CFD and advanced evolutionary algorithms

Computation Fluid Dynamics (CFD) has become an important tool in optimization and has seen successful in many real world applications. Most important among these is in the optimisation of aerodynamic surfaces which has become Multi-Objective (MO) and Multidisciplinary (MDO) in nature. Most of these have been carried out for a given set of input parameters such as free stream Mach number and angle of attack. One cannot ignore the fact that in aerospace engineering one frequently deals with situations where the design input parameters and flight/flow conditions have some amount of uncertainty attached to them. When the optimisation is carried out for fixed values of design variables and parameters however, one arrives at an optimised solution that results in good performance at design condition but poor drag or lift to drag ratio at slightly off-design conditions. The challenge is still to develop a robust design that accounts for uncertainty in the design in aerospace applications. In this paper this issue is taken up and an attempt is made to prevent the fluctuation of objective performance by using robust design technique or Uncertainty.

Bitrate modeling of scalable videos using quantization parameter, frame rate and spatial resolution

The quality and bitrate modeling is essential to effectively adapt the bitrate and quality of videos when delivered to multiplatform devices over resource constraint heterogeneous networks. The recent model proposed by Wang et al. estimates the bitrate and quality of videos in terms of the frame rate and quantization parameter. However, to build an effective video adaptation framework, it is crucial to incorporate the spatial resolution in the analytical model for bitrate and perceptual quality adaptation. Hence, this paper proposes an analytical model to estimate the bitrate of videos in terms of quantization parameter, frame rate, and spatial resolution. The model can fit the measured data accurately which is evident from the high Pearson correlation. The proposed model is based on the observation that the relative reduction in bitrate due to decreasing spatial resolution is independent of the quantization parameter and frame rate. This modeling can be used for rate-constrained bit-stream adaptation scheme which selects the scalability parameters to optimize the perceptual quality for a given bandwidth constraint.

Recognising audio-visual speech in vehicles using the AVICAR database

Interacting with technology within a vehicle environment using a voice interface can greatly reduce the effects of driver distraction. Most current approaches to this problem only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to circumvent this is to use the visual modality in addition. However, capturing, storing and distributing audio-visual data in a vehicle environment is very costly and difficult. One current dataset available for such research is the AVICAR [1] database. Unfortunately this database is largely unusable due to timing mismatch between the two streams and in addition, no protocol is available. We have overcome this problem by re-synchronising the streams on the phone-number portion of the dataset and established a protocol for further research. This paper presents the first audio-visual results on this dataset for speaker-independent speech recognition. We hope this will serve as a catalyst for future research in this area.

An assessment system for evaluation of driving competencies

Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

Measuring the impact of information systems in Malaysia

Information Systems researchers have employed a diversity of sometimes inconsistent measures of IS success, seldom explicating the rationale, thereby complicating the choice for future researchers. In response to these and other issues, Gable, Sedera and Chan introduced the IS-Impact measurement model. This model represents “the stream of net benefits from the Information System (IS), to date and anticipated, as perceived by all key-user-groups”. Although the IS-Impact model was rigorously validated in previous research, there is a need to further generalise and validate it in different context. This paper reported the findings of the IS-Impact model revalidation study at four state governments in Malaysia with 232 users of a financial system that is currently being used at eleven state governments in Malaysia. Data was analysed following the guidelines for formative measurement validation using SmartPLS. Based on the PLS results, data supported the IS-Impact dimensions and measures thus confirming the validity of the IS-Impact model in Malaysia. This indicates that the IS-Impact model is robust and can be used across different context.

Note on similarity solutions for viscous flow over an impermeable and non-linearly (quadratic) stretching sheet

Similarity solutions for flow over an impermeable, non-linearly (quadratic) stretching sheet were studied recently by Raptis and Perdikis (Int. J. Non-linear Mech. 41 (2006) 527–529) using a stream function of the form ψ=αxf(η)+βx2g(η). A fundamental error in their problem formulation is pointed out. On correction, it is shown that similarity solutions do not exist for this choice of ψ

Overloading truck traffic study and strategy to minimise it

Overloaded truck traffic is a significant problem on highways around the world. Developing countries in particular, overloaded truck traffic causes large amounts of unexpected expenditure in terms of road maintenance because of premature pavement damage. Overloaded truck traffic is a common phenomenon in developing countries, because of inefficient road management and monitoring systems. According to the available literature, many developing countries are facing the same problem, which is economic loss caused by the existence of overloaded trucks in the traffic stream. This paper summarizes the available literature, news reports, journal articles and traffic research regarding overloaded traffic. It examines the issue of overloading and the strategies and legislation used in developed countries.

Microscopic modelling of freeway operations

Freeways are divided roadways designed to facilitate the uninterrupted movement of motor vehicles. However, many freeways now experience demand flows in excess of capacity, leading to recurrent congestion. The Highway Capacity Manual (TRB, 1994) uses empirical macroscopic relationships between speed, flow and density to quantify freeway operations and performance. Capacity may be predicted as the maximum uncongested flow achievable. Although they are effective tools for design and analysis, macroscopic models lack an understanding of the nature of processes taking place in the system. Szwed and Smith (1972, 1974) and Makigami and Matsuo (1990) have shown that microscopic modelling is also applicable to freeway operations. Such models facilitate an understanding of the processes whilst providing for the assessment of performance, through measures of capacity and delay. However, these models are limited to only a few circumstances. The aim of this study was to produce more comprehensive and practical microscopic models. These models were required to accurately portray the mechanisms of freeway operations at the specific locations under consideration. The models needed to be able to be calibrated using data acquired at these locations. The output of the models needed to be able to be validated with data acquired at these sites. Therefore, the outputs should be truly descriptive of the performance of the facility. A theoretical basis needed to underlie the form of these models, rather than empiricism, which is the case for the macroscopic models currently used. And the models needed to be adaptable to variable operating conditions, so that they may be applied, where possible, to other similar systems and facilities. It was not possible to produce a stand-alone model which is applicable to all facilities and locations, in this single study, however the scene has been set for the application of the models to a much broader range of operating conditions. Opportunities for further development of the models were identified, and procedures provided for the calibration and validation of the models to a wide range of conditions. The models developed, do however, have limitations in their applicability. Only uncongested operations were studied and represented. Driver behaviour in Brisbane was applied to the models. Different mechanisms are likely in other locations due to variability in road rules and driving cultures. Not all manoeuvres evident were modelled. Some unusual manoeuvres were considered unwarranted to model. However the models developed contain the principal processes of freeway operations, merging and lane changing. Gap acceptance theory was applied to these critical operations to assess freeway performance. Gap acceptance theory was found to be applicable to merging, however the major stream, the kerb lane traffic, exercises only a limited priority over the minor stream, the on-ramp traffic. Theory was established to account for this activity. Kerb lane drivers were also found to change to the median lane where possible, to assist coincident mergers. The net limited priority model accounts for this by predicting a reduced major stream flow rate, which excludes lane changers. Cowan's M3 model as calibrated for both streams. On-ramp and total upstream flow are required as input. Relationships between proportion of headways greater than 1 s and flow differed for on-ramps where traffic leaves signalised intersections and unsignalised intersections. Constant departure onramp metering was also modelled. Minimum follow-on times of 1 to 1.2 s were calibrated. Critical gaps were shown to lie between the minimum follow-on time, and the sum of the minimum follow-on time and the 1 s minimum headway. Limited priority capacity and other boundary relationships were established by Troutbeck (1995). The minimum average minor stream delay and corresponding proportion of drivers delayed were quantified theoretically in this study. A simulation model was constructed to predict intermediate minor and major stream delays across all minor and major stream flows. Pseudo-empirical relationships were established to predict average delays. Major stream average delays are limited to 0.5 s, insignificant compared with minor stream delay, which reach infinity at capacity. Minor stream delays were shown to be less when unsignalised intersections are located upstream of on-ramps than signalised intersections, and less still when ramp metering is installed. Smaller delays correspond to improved merge area performance. A more tangible performance measure, the distribution of distances required to merge, was established by including design speeds. This distribution can be measured to validate the model. Merging probabilities can be predicted for given taper lengths, a most useful performance measure. This model was also shown to be applicable to lane changing. Tolerable limits to merging probabilities require calibration. From these, practical capacities can be estimated. Further calibration is required of traffic inputs, critical gap and minimum follow-on time, for both merging and lane changing. A general relationship to predict proportion of drivers delayed requires development. These models can then be used to complement existing macroscopic models to assess performance, and provide further insight into the nature of operations.