Detecting conversing groups of chatters : a model, algorithms, and tests

Chatrooms, for example Internet Relay Chat, are generally multi-user, multi-channel and multiserver chat-systems which run over the Internet and provide a protocol for real-time text-based conferencing between users all over the world. While a well-trained human observer is able to understand who is chatting with whom, there are no efficient and accurate automated tools to determine the groups of users conversing with each other. A precursor to analysing evolving cyber-social phenomena is to first determine what the conversations are and which groups of chatters are involved in each conversation. We consider this problem in this paper. We propose an algorithm to discover all groups of users that are engaged in conversation. Our algorithms are based on a statistical model of a chatroom that is founded on our experience with real chatrooms. Our approach does not require any semantic analysis of the conversations, rather it is based purely on the statistical information contained in the sequence of posts. We improve the accuracy by applying some graph algorithms to clean the statistical information. We present some experimental results which indicate that one can automatically determine the conversing groups in a chatroom, purely on the basis of statistical analysis.

Predicting the localized surface plasmon resonances of spherical nanoparticles on substrate : electrostatic eigenmode method

We present experimental results that demonstrate that the wavelength of the fundamental localised surface plasmon resonance for spherical gold nanoparticles on glass can be predicted using a simple, one line analytical formula derived from the electrostatic eigenmode method. This allows the role of the substrate in lifting mode degeneracies to be determined, and the role of local environment refractive indices on the plasmon resonance to be investigated. The effect of adding silica to the casting solution in minimizing nanopaticle agglomeration is also discussed.

Adaptive dynamic path re-planning RRT algorithms with game theory for UAVs

The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.

Pseudo-marginal algorithms with multiple CPUs

The emergence of pseudo-marginal algorithms has led to improved computational efficiency for dealing with complex Bayesian models with latent variables. Here an unbiased estimator of the likelihood replaces the true likelihood in order to produce a Bayesian algorithm that remains on the marginal space of the model parameter (with latent variables integrated out), with a target distribution that is still the correct posterior distribution. Very efficient proposal distributions can be developed on the marginal space relative to the joint space of model parameter and latent variables. Thus psuedo-marginal algorithms tend to have substantially better mixing properties. However, for pseudo-marginal approaches to perform well, the likelihood has to be estimated rather precisely. This can be difficult to achieve in complex applications. In this paper we propose to take advantage of multiple central processing units (CPUs), that are readily available on most standard desktop computers. Here the likelihood is estimated independently on the multiple CPUs, with the ultimate estimate of the likelihood being the average of the estimates obtained from the multiple CPUs. The estimate remains unbiased, but the variability is reduced. We compare and contrast two different technologies that allow the implementation of this idea, both of which require a negligible amount of extra programming effort. The superior performance of this idea over the standard approach is demonstrated on simulated data from a stochastic volatility model.

Comparing genotyping algorithms for Illumina's Infinium whole-genome SNP BeadChips

Background Illumina's Infinium SNP BeadChips are extensively used in both small and large-scale genetic studies. A fundamental step in any analysis is the processing of raw allele A and allele B intensities from each SNP into genotype calls (AA, AB, BB). Various algorithms which make use of different statistical models are available for this task. We compare four methods (GenCall, Illuminus, GenoSNP and CRLMM) on data where the true genotypes are known in advance and data from a recently published genome-wide association study. Results In general, differences in accuracy are relatively small between the methods evaluated, although CRLMM and GenoSNP were found to consistently outperform GenCall. The performance of Illuminus is heavily dependent on sample size, with lower no call rates and improved accuracy as the number of samples available increases. For X chromosome SNPs, methods with sex-dependent models (Illuminus, CRLMM) perform better than methods which ignore gender information (GenCall, GenoSNP). We observe that CRLMM and GenoSNP are more accurate at calling SNPs with low minor allele frequency than GenCall or Illuminus. The sample quality metrics from each of the four methods were found to have a high level of agreement at flagging samples with unusual signal characteristics. Conclusions CRLMM, GenoSNP and GenCall can be applied with confidence in studies of any size, as their performance was shown to be invariant to the number of samples available. Illuminus on the other hand requires a larger number of samples to achieve comparable levels of accuracy and its use in smaller studies (50 or fewer individuals) is not recommended.

The formation of gold nanoparticles using hydroquinone as a reducing agent through a localized pH change upon addition of NaOH to a solution of HAuCl4

We demonstrate a rapid synthesis of gold nanoparticles using hydroquinone as a reducing agent under acidic conditions without the need for precursor seed particles. The nanoparticle formation process is facilitated by the addition of NaOH to a solution containing HAuCl4 and hydroquinone to locally change the pH; this enhances the reducing capability of hydroquinone to form gold nucleation centres, after which further growth of gold can take place through an autocatalytic mechanism. The stability of the nanoparticles is highly dependent on the initial solution pH, and both the concentration of added NaOH and hydroquinone present in solution. The gold nanoparticles were characterized by UV–visible spectroscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, atomic force microscopy, dynamic light scattering, and zeta potential measurements. It was found that under optimal conditions that stable aqueous suspensions of 20 nm diameter nanoparticles can be achieved where benzoquinone, the oxidized product of hydroquinone, acts as a capping agent preventing nanoparticles aggregation.

Part 1 MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 1.) Theoretical aspects

Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

Accelerometer data reduction : a comparison of four reduction algorithms on select outcome variables

Purpose Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. Methods The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. Results The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. Conclusions These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies

Critical review of time-dependent shortest path algorithms: A multimodal trip planner perspective

A multimodal trip planner that produces optimal journeys involving both public transport and private vehicle legs has to solve a number of shortest path problems, both on the road network and the public transport network. The algorithms that are used to solve these shortest path problems have been researched since the late 1950s. However, in order to provide accurate journey plans that can be trusted by the user, the variability of travel times caused by traffic congestion must be taken into consideration. This requires the use of more sophisticated time-dependent shortest path algorithms, which have only been researched in depth over the last two decades, from the mid-1990s. This paper will review and compare nine algorithms that have been proposed in the literature, discussing the advantages and disadvantages of each algorithm on the basis of five important criteria that must be considered when choosing one or more of them to implement in a multimodal trip planner.

Design methodologies and architectures of hardware-based evolutionary algorithms for aerospace optimisation applications on FPGAS

This thesis is a study of new design methods for allowing evolutionary algorithms to be more effectively utilised in aerospace optimisation applications where computation needs are high and computation platform space may be restrictive. It examines the applicability of special hardware computational platforms known as field programmable gate arrays and shows that with the right implementation methods they can offer significant benefits. This research is a step forward towards the advancement of efficient and highly automated aircraft systems for meeting compact physical constraints in aerospace platforms and providing effective performance speedups over traditional methods.

Исследования и испытания алгоритмов автоматической пилотажно-навигационной системы малогабаритного беспилотного летательного аппарата = Research and testing of automatic navigation management system’s algorithms for small unmanned aerial vehicle

В статье представлено развитие принципа построения автоматической пилотажно-навигационной системы (АПНС) для беспилотного летательного аппарата (БЛА). Принцип заключается в синтезе комплексных систем управления БПЛА не только на основе использования алгоритмов БИНС, но и алгоритмов, объединяющих в себе решение задач формирования и отработки сформированной траектории резервированной системой управления и навигации. Приведены результаты аналитического исследования и данные летных экспериментов разработанных алгоритмов АПНС БЛА, обеспечивающих дополнительное резервирование алгоритмов навигации и наделяющих БЛА новым функциональной способностью по выходу в заданную точку пространства с заданной скоростью в заданный момент времени с учетом атмосферных ветровых возмущений. Предложена и испытана методика идентификации параметров воздушной атмосферы: направления и скорости W ветра. Данные летных испытаний полученного решения задачи терминальной навигации демонстрируют устойчивую работу синтезированных алгоритмов управления в различных метеоусловиях. The article presents a progress in principle of development of automatic navigation management system (ANMS) for small unmanned aerial vehicle (UAV). The principle defines a development of integrated control systems for UAV based on tight coupling of strap down inertial navigation system algorithms and algorithms of redundant flight management system to form and control flight trajectory. The results of the research and flight testing of the developed ANMS UAV algorithms are presented. The system demonstrates advanced functional redundancy of UAV guidance. The system enables new UAV capability to perform autonomous multidimensional navigation along waypoints with controlled speed and time of arrival taking into account wind. The paper describes the technique for real-time identification of atmosphere parameters such as wind direction and wind speed. The flight test results demonstrate robustness of the algorithms in diverse meteorological conditions.

Part 2. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 2.) Numerical aspects and implementation of model test cases

These lecture notes describe the use and implementation of a framework in which mathematical as well as engineering optimisation problems can be analysed. The foundations of the framework and algorithms described -Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) - lie upon traditional evolution strategies and incorporate the concepts of a multi-objective optimisation, hierarchical topology, asynchronous evaluation of candidate solutions , parallel computing and game strategies. In a step by step approach, the numerical implementation of EAs and HAPEAs for solving multi criteria optimisation problems is conducted providing the reader with the knowledge to reproduce these hand on training in his – her- academic or industrial environment.

Part 3. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 3.) Practical application to the design and optimisation of UAV systems

These lecture notes highlight some of the recent applications of multi-objective and multidisciplinary design optimisation in aeronautical design using the framework and methodology described in References 8, 23, 24 and in Part 1 and 2 of the notes. A summary of the methodology is described and the treatment of uncertainties in flight conditions parameters by the HAPEAs software and game strategies is introduced. Several test cases dealing with detailed design and computed with the software are presented and results discussed in section 4 of these notes.

An experimental based assessment of the deviation of the bearing characteristic frequencies

Slippage in the contact roller-races has always played a central role in the field of diagnostics of rolling element bearings. Due to this phenomenon, vibrations triggered by a localized damage are not strictly periodic and therefore not detectable by means of common spectral functions as power spectral density or discrete Fourier transform. Due to the strong second order cyclostationary component, characterizing these signals, techniques such as cyclic coherence, its integrated form and square envelope spectrum have proven to be effective in a wide range of applications. An expert user can easily identify a damage and its location within the bearing components by looking for particular patterns of peaks in the output of the selected cyclostationary tool. These peaks will be found in the neighborhood of specific frequencies, that can be calculated in advance as functions of the geometrical features of the bearing itself. Unfortunately the non-periodicity of the vibration signal is not the only consequence of the slippage: often it also involves a displacement of the damage characteristic peaks from the theoretically expected frequencies. This issue becomes particularly important in the attempt to develop highly automated algorithms for bearing damage recognition, and, in order to correctly set thresholds and tolerances, a quantitative description of the magnitude of the above mentioned deviations is needed. This paper is aimed at identifying the dependency of the deviations on the different operating conditions. This has been possible thanks to an extended experimental activity performed on a full scale bearing test rig, able to reproduce realistically the operating and environmental conditions typical of an industrial high power electric motor and gearbox. The importance of load will be investigated in detail for different bearing damages. Finally some guidelines on how to cope with such deviations will be given, accordingly to the expertise obtained in the experimental activity.