Trends,codes and virus attacks - 2003 year in review

A shortlist of the most memorable events of 2003 will undoubtedly include the demise of Saddam Hussein's regime but what will surely be omitted from most top 10s is the continuing threat posed by malware — viruses and other malicious code – and the nuisance of spam messaging. These omissions are made despite worrying developments in mass mail worms, blended threats and increasing spam complexity.     

The effects of socioeconomic status, race, and parenting on language development in early childhood.

The authors examined the associations between socioeconomic status (SES), race, maternal sensitivity, and maternal negative-intrusive behaviors and language development in a sample selected to reduce the typical confound between race and SES (n = 146). Mother–child interactions were observed at 12 and 24 months (coded by randomly assigned African American and European American coders); language abilities were assessed at 18, 24, 30, and 36 months. For receptive language, race was associated with ability level, and maternal sensitivity and negative-intrusive parenting were related to rate of growth. For expressive communication, race, SES, and maternal sensitivity were associated with rate of growth; race moderated the association between negative-intrusive parenting and rate of growth such that the relation was weaker for African American than for European American children. The results highlight the importance of sensitive parenting and suggest that the association between negative-intrusive parenting and language development may depend upon family context. Future work is needed concerning the race differences found, including examining associations with other demographic factors and variations in language input experienced by children, using culturally and racially validated indices of language development. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Probabilistic learning on manifolds (PLoM) with partition

The probabilistic learning on manifolds (PLoM) introduced in 2016 has solved difficult supervised problems for the “small data” limit where the number N of points in the training set is small. Many extensions have since been proposed, making it possible to deal with increasingly complex cases. However, the performance limit has been observed and explained for applications for which N is very small and for which the dimension of the diffusion-map basis is close to N. For these cases, we propose a novel extension based on the introduction of a partition in independent random vectors. We take advantage of this development to present improvements of the PLoM such as a simplified algorithm for constructing the diffusion-map basis and a new mathematical result for quantifying the concentration of the probability measure in terms of a probability upper bound. The analysis of the efficiency of this extension is presented through two applications.     

Some Grubbs-Type Statistics for the Detection of Several Outliers

Several widely used tests for outlying observations are reviewed. Problems of repeated application and “masking” are described. Suggested as appropriate to over-come these problems are two new statistics: L_k which is based on the k largest (observed) values and E_k which is based on the k largest (in absolute value) residuals. Tables of approximate critical values for these statistics are given for 0.01, .025,0.05, and 0.10 levels of significance and for sample size n = 3 (1) 20 (5) 50.     

Inductive transfer for learning Bayesian networks

In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with different conditions; or in industrial diagnosis, where there is equipment with similar specifications. In these cases it is common to have plenty of data for some scenarios but very little for others. In order to learn accurate models for rare cases, it is desirable to use data and knowledge from similar cases; a technique known as transfer learning. In this paper we propose an inductive transfer learning method for Bayesian networks, that considers both structure and parameter learning. For structure learning we use conditional independence tests, by combining measures from the target task with those obtained from one or more auxiliary tasks, using a novel weighted sum of the conditional independence measures. For parameter learning, we propose two variants of the linear pool for probability aggregation, combining the probability estimates from the target task with those from the auxiliary tasks. To validate our approach, we used three Bayesian networks models that are commonly used for evaluating learning techniques, and generated variants of each model by changing the structure as well as the parameters. We then learned one of the variants with a small dataset and combined it with information from the other variants. The experimental results show a significant improvement in terms of structure and parameters when we transfer knowledge from similar tasks. We also evaluated the method with real-world data from a manufacturing process considering several products, obtaining an improvement in terms of log-likelihood between the data and the model when we do transfer learning from related products.     

Performance comparison of the CRAY X-MP/24 with SDD and the CRAY-2

The CRAY-2 is considered to be one of the most powerful supercomputers. Its state-of-the-art technology features a faster clock and more memory than any other supercomputer available today. In this report the single processor performance of the CRAY-2 is compared with the older, more mature CRAY X-MP. Benchmark results are included for both the slow and the fast memory DRAM MOS CRAY-2. Our comparison is based on a kernel benchmark set aimed at evaluating the performance of these two machines on some standard tasks in scientific computing. Particular emphasis is placed on evaluating the impact of the availability of large real memory on the CRAY-2 versus fast secondary memory on the CRAY X-MP with SSD. Our benchmark includes large linear equation solvers and FFT routines, which test the capabilities of the different approaches to providing large memory. We find that in spite of its higher processor speed the CRAY-2 does not perform as well as the CRAY X-MP on the Fortran kernel benchmark. We also find that for large-scale applications, which have regular and predictable memory access patterns, a high-speed secondary memory device such as the SSD can provide performance equal to the large real memory of the CRAY-2.The author is an employee of SCA Division of Boeing Computer Services.     

Atmospheric correction over land for MERIS

A three-stage atmospheric correction is proposed for the Medium Resolution Imaging Spectrometer (MERIS) from a validated formulation of the signal. We correct first for the gaseous transmittance. Assuming the ozone correction is well defined, we illustrate the need to include a correction for water vapour continuum which covers most of the MERIS bands. The water vapour transmittance can be computed from the water vapour content obtained from a twoband ratio at 900nm and 890nm. We demonstrate that a direct association between the transmittance in a given band and the two band ratio is more accurate due to the removal of the coupling between absorption and scattering. Secondly, the Rayleigh correction depends on the barometric pressure determined here from a two band ratio method with the oxygen A band. Good accuracy is obtained for the pressure when accounting for the coupling between scattering and gas absorption, which mostly depends on the surface reflectance. The Rayleigh reflectance is computed from a Fourier series decomposition in which primary scattering is corrected for multiple scattering by a multiplicative factor which is derived from a polynomial regression versus the optical thickness. A similar formulation of the signal is proposed for the aerosol reflectances from 12 predefined aerosol models. The aerosol correction relies on a characterization of the aerosol over Dense Dark Vegetation for which an identification criteria is proposed along with standard reflectance values in the blue and in the red.     

Simulation-based conjoint ranking for optimal decision support process under aleatory uncertainty

Design chain management requires many decision makers throughout the product development process. It is critical to reduce complexity and uncertainty of the design process by correctly modeling subjective data associated with decision makers’ preferences. This paper aims at using decision support to find optimal designs by modeling respondent preferences and trade-offs with consideration of uncertainty. Specifically, a simulation-based ranking methodology is implemented and incorporated with traditional conjoint analysis. This process facilitates a schematic decision support process by alleviating user fatigue. In addition, incorporation of uncertainty in the ranking process provides the capability of producing robust and reliable products. The efficacy and applicability of simulation-based conjoint ranking is demonstrated with a case study of a power-generating shock absorber design.     

Researchers on the pier: Academics’ use of a local internet gateway

This paper describes the establishment of an Internet gateway local to the University of Sussex, firstly as a Gopher and more recently as a World Wide Web server. There follows an account of a project currently underway to assess the practical value of Internet resources to research and the consequential training and support requirements. This assessment is planned to determine the value of a local gateway to academic researchers at Sussex and the roles specific to a local gateway that such comprehensive resources as Yahoo and BUBL cannot fulfil. The project is using an interview‐based methodology to gain an understanding of researchers’ views of Internet resource provision, and these interviews are being analysed with the help of the NUD*IST qualitative data analysis software package. The account is of research in progress, and hence does not conclude with the set of pragmatic policy proposals that forms its key objective. Instead, some indication is given of the broad early findings of the project     

Visual analysis of social networks in space and time using smartphone logs

We designed and applied interactive visualisation techniques for investigating how social networks are embedded in time and space, using data collected from smartphone logs. Our interest in spatial aspects of social networks is that they may reveal associations between participants missed by simply making contact through smartphone devices. Four linked and co-ordinated views of spatial, temporal, individual and social network aspects of the data, along with demographic and attitudinal variables, helped add context to the behaviours we observed. Using these techniques, we were able to characterise spatial and temporal aspects of participants’ social networks and suggest explanations for some of them. This provides some validation of our techniques.Unexpected deficiencies in the data that became apparent prompted us to evaluate the dataset in more detail. Contrary to what we expected, we found significant gaps in participant records, particularly in terms of location, a poorly connected sample of participants and asymmetries in reciprocal call logs. Although the data captured are of high quality, deficiencies such as these remain and are likely to have a significant impact on interpretations relating to spatial aspects of the social network. We argue that appropriately-designed interactive visualisation techniques–afforded by our flexible prototyping approach–are effective in identifying and characterising data inconsistencies. Such deficiencies are likely to exist in other similar datasets, and although the visual approaches we discuss for identifying data problems may not be scalable, the categories of problems we identify may be used to inform attempts to systematically account for errors in larger smartphone datasets.