Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Development of a cost-effectiveness model for guardrail selection. Executive summary. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Development of a cost-effectiveness model for guardrail selection. Volume I: technical documentation. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Development of a cost-effectiveness model for guardrail selection. Volume II: user's manual. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

From Darwinism to kaiserism, being a review of the origin, effects and collapse of Germany's attempt at world-dominion by methods of barbarism;

Mode of access: Internet.

Simulating the effects of dominance and epistasis on selection response in the CIMMYT wheat breeding program using QuCim

Plant breeders use many different breeding methods to develop superior cultivars. However, it is difficult, cumbersome, and expensive to evaluate the performance of a breeding method or to compare the efficiencies of different breeding methods within an ongoing breeding program. To facilitate comparisons, we developed a QU-GENE module called QuCim that can simulate a large number of breeding strategies for self-pollinated species. The wheat breeding strategy Selected Bulk used by CIMMYT's wheat breeding program was defined in QuCim as an example of how this is done. This selection method was simulated in QuCim to investigate the effects of deviations from the additive genetic model, in the form of dominance and epistasis, on selection outcomes. The simulation results indicate that the partial dominance model does not greatly influence genetic advance compared with the pure additive model. Genetic advance in genetic systems with overdominance and epistasis are slower than when gene effects are purely additive or partially dominant. The additive gene effect is an appropriate indicator of the change in gene frequency following selection when epistasis is absent. In the absence of epistasis, the additive variance decreases rapidly with selection. However, after several cycles of selection it remains relatively fixed when epistasis is present. The variance from partial dominance is relatively small and therefore hard to detect by the covariance among half sibs and the covariance among full sibs. The dominance variance from the overdominance model can be identified successfully, but it does not change significantly, which confirms that overdominance cannot be utilized by an inbred breeding program. QuCim is an effective tool to compare selection strategies and to validate some theories in quantitative genetics.

Isolation and characterization of integron-containing bacteria without antibiotic selection

The emergence of antibiotic resistance among pathogenic and commensal bacteria has become a serious problem worldwide. The use and overuse of antibiotics in a number of settings are contributing to the development of antibiotic-resistant microorganisms. The class 1 and 2 integrase genes (intI1 and intI2, respectively) were identified in mixed bacterial cultures enriched from bovine feces by growth in buffered peptone water (BPW) followed by integrase-specific PCR. Integrase-positive bacterial colonies from the enrichment cultures were then isolated by using hydrophobic grid membrane filters and integrase-specific gene probes. Bacterial clones isolated by this technique were then confirmed to carry integrons by further testing by PCR and DNA sequencing. Integron-associated antibiotic resistance genes were detected in bacteria such as Escherichia coli, Aeromonas spp., Proteus spp., Morganella morganii, Shewanella spp., and urea-positive Providencia stuartii isolates from bovine fecal samples without the use of selective enrichment media containing antibiotics. Streptomycin and trimethoprim resistance were commonly associated with integrons. The advantages conferred by this methodology are that a wide variety of integron-containing bacteria may be simultaneously cultured in BPW enrichments and culture biases due to antibiotic selection can be avoided. Rapid and efficient identification, isolation, and characterization of antibiotic resistance-associated integrons are possible by this protocol. These methods will facilitate greater understanding of the factors that contribute to the presence and transfer of integron-associated antibiotic resistance genes in bacterial isolates from red meat production animals.

Factors in the selection of patients for conditional release from their first psychiatric hospitalization

Objective: This study examined a sample of patients in Victoria, Australia, to identify factors in selection for conditional release from an initial hospitalization that occurred within 30 days of entry into the mental health system. Methods: Data were from the Victorian Psychiatric Case Register. All patients first hospitalized and conditionally released between 1990 and 2000 were identified (N = 8,879), and three comparison groups were created. Two groups were hospitalized within 30 days of entering the system: those who were given conditional release and those who were not. A third group was conditionally released from a hospitalization that occurred after or extended beyond 30 days after system entry. Logistic regression identified characteristics that distinguished the first group. Ordinary least-squares regression was used to evaluate the contribution of conditional release early in treatment to reducing inpatient episodes, inpatient days, days per episode, and inpatient days per 30 days in the system. Results: Conditional release early in treatment was used for 11 percent of the sample, or more than a third of those who were eligible for this intervention. Factors significantly associated with selection for early conditional release were those related to a better prognosis ( initial hospitalization at a later age and having greater than an 11th grade education), a lower likelihood of a diagnosis of dementia or schizophrenia, involuntary status at first inpatient admission, and greater community involvement ( being employed and being married). When the analyses controlled for these factors, use of conditional release early in treatment was significantly associated with a reduction in use of subsequent inpatient care.

The dynamics of a genetic algorithm under stabilizing selection

A formalism recently introduced by Prugel-Bennett and Shapiro uses the methods of statistical mechanics to model the dynamics of genetic algorithms. To be of more general interest than the test cases they consider. In this paper, the technique is applied to the subset sum problem, which is a combinatorial optimization problem with a strongly non-linear energy (fitness) function and many local minima under single spin flip dynamics. It is a problem which exhibits an interesting dynamics, reminiscent of stabilizing selection in population biology. The dynamics are solved under certain simplifying assumptions and are reduced to a set of difference equations for a small number of relevant quantities. The quantities used are the population's cumulants, which describe its shape, and the mean correlation within the population, which measures the microscopic similarity of population members. Including the mean correlation allows a better description of the population than the cumulants alone would provide and represents a new and important extension of the technique. The formalism includes finite population effects and describes problems of realistic size. The theory is shown to agree closely to simulations of a real genetic algorithm and the mean best energy is accurately predicted.

Expert systems for vendor selection

The survival of organisations, especially SMEs, depends, to the greatest extent, on those who supply them with the required material input. This is because if the supplier fails to deliver the right materials at the right time and place, and at the right price, then the recipient organisation is bound to fail in its obligations to satisfy the needs of its customers, and to stay in business. Hence, the task of choosing a supplier(s) from a list of vendors, that an organisation will trust with its very existence, is not an easy one. This project investigated how purchasing personnel in organisations solve the problem of vendor selection. The investigation went further to ascertain whether an Expert Systems model could be developed and used as a plausible solution to the problem. An extensive literature review indicated that very scanty research has been conducted in the area of Expert Systems for Vendor Selection, whereas many research theories in expert systems and in purchasing and supply management chain, respectively, had been reported. A survey questionnaire was designed and circulated to people in the industries who actually perform the vendor selection tasks. Analysis of the collected data confirmed the various factors which are considered during the selection process, and established the order in which those factors are ranked. Five of the factors, namely, Production Methods Used, Vendors Financial Background, Manufacturing Capacity, Size of Vendor Organisations, and Suppliers Position in the Industry; appeared to have similar patterns in the way organisations ranked them. These patterns suggested that the bigger the organisation, the more importantly they regarded the above factors. Further investigations revealed that respondents agreed that the most important factors were: Product Quality, Product Price and Delivery Date. The most apparent pattern was observed for the Vendors Financial Background. This generated curiosity which led to the design and development of a prototype expert system for assessing the financial profile of a potential supplier(s). This prototype was called ESfNS. It determines whether a prospective supplier(s) has good financial background or not. ESNS was tested by the potential users who then confirmed that expert systems have great prospects and commercial viability in the domain for solving vendor selection problems.

Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.

Integrated project evaluation and selection using multiple-attribute decision-making technique

The evaluation and selection of industrial projects before investment decision is customarily done using marketing, technical and financial information. Subsequently, environmental impact assessment and social impact assessment are carried out mainly to satisfy the statutory agencies. Because of stricter environment regulations in developed and developing countries, quite often impact assessment suggests alternate sites, technologies, designs, and implementation methods as mitigating measures. This causes considerable delay to complete project feasibility analysis and selection as complete analysis requires to be taken up again and again till the statutory regulatory authority approves the project. Moreover, project analysis through above process often results sub-optimal project as financial analysis may eliminate better options, as more environment friendly alternative will always be cost intensive. In this circumstance, this study proposes a decision support system, which analyses projects with respect to market, technicalities, and social and environmental impact in an integrated framework using analytic hierarchy process, a multiple-attribute decision-making technique. This not only reduces duration of project evaluation and selection, but also helps select optimal project for the organization for sustainable development. The entire methodology has been applied to a cross-country oil pipeline project in India and its effectiveness has been demonstrated. © 2005 Elsevier B.V. All rights reserved.

Decision support system for project selection

The evaluation and selection of industrial projects before investment decision is customarily done using marketing, technical, and financial information. Subsequently, environmental impact assessment and social impact assessment are carried out mainly to satisfy the statutory agencies. Because of stricter environment regulations in developed and developing countries, quite often impact assessment suggests alternate sites, technologies, designs, and implementation methods as mitigating measures. This causes considerable delay to complete project feasibility analysis and selection as complete analysis requires to be taken up again and again until the statutory regulatory authority approves the project. Moreover, project analysis through the above process often results in suboptimal projects as financial analysis may eliminate better options as more environment friendly alternative will always be cost intensive. In this circumstance, this study proposes a decision support system which analyses projects with respect to market, technicalities, and social and environmental impact in an integrated framework using analytic hierarchy process, a multiple attribute decision-making technique. This not only reduces duration of project evaluation and selection, but also helps select an optimal project for the organization for sustainable development. The entire methodology has been applied to a cross-country oil pipeline project in India and its effectiveness has been demonstrated. © 2008, IGI Global.

Writing and characterisation methods for UV-photosensitivity based devices and their applications

The underlying work to this thesis focused on the exploitation and investigation of photosensitivity mechanisms in optical fibres and planar waveguides for the fabrication of advanced integrated optical devices for telecoms and sensing applications. One major scope is the improvement of grating fabrication specifications by introducing new writing techniques and the use of advanced characterisation methods for grating testing. For the first time the polarisation control method for advanced grating fabrication has successfully been converted to apodised planar waveguide fabrication and the development of a holographic method for the inscription of chirped gratings at arbitrary wavelength is presented. The latter resulted in the fabrication of gratings for pulse-width suppression and wavelength selection in diode lasers. In co-operation with research partners a number of samples were tested using optical frequency domain and optical low coherence reflectometry for a better insight into the limitations of grating writing techniques. Using a variety of different fabrication methods, custom apodised and chirped fibre Bragg gratings were written for the use as filter elements for multiplexer-demultiplexer devices, as well as for short pulse generation and wavelength selection in telecommunication transmission systems. Long period grating based devices in standard, speciality and tapered fibres are presented, showing great potential for multi-parameter sensing. One particular scope is the development of vectorial curvature and refractive index sensors with potential for medical, chemical and biological sensing. In addition the design of an optically tunable Mach-Zehnder based multiwavelength filter is introduced. The discovery of a Type IA grating type through overexposure of hydrogen loaded standard and Boron-Germanium co-doped fibres strengthened the assumption of UV-photosensitivity being a highly non-linear process. Gratings of this type show a significantly lower thermal sensitivity compared to standard gratings, which makes them useful for sensing applications. An Oxford Lasers copper-vapour laser operating at 255 nm in pulsed mode was used for their inscription, in contrast to previous work using CW-Argon-Ion lasers and contributing to differences in the processes of the photorefractive index change