Age model of sediment core V20-120 (Table 2)

Time series analyses of atmospheric and oceanic variables in a late Pleistocene record from the northwest Pacific show the complex relationship of the response of various segments of the climate system to changes in the earth's orbit. Most variance spectra of time series from this subarctic record contain frequency peaks with periods corresponding to at least one of the major orbital components of eccentricity, obliquity, or precession. Although the radiolarian faunal (water mass) assemblages have prominent spectral peaks with 41,000-year periods which are coherent with obliquity at this frequency, only the Transitional faunal assemblage contains variance focused at a frequency corresponding to the 100,000-year period of eccentricity. Three of these faunal time series also show variance concentrated at a frequency with a 20,000-year period. These three time series are not coherent at a 20,000-year frequency with either of the dominant spectral peaks of precession. They are coherent, however, with variations in the second harmonic of the obliquity cycle. Changes in obliquity apparently affect siliceous faunal abundances in the northwest Pacific region of this high-latitude site more than variations in eccentricity or precession. Maxima in the time series of quartz abundance occur during low values of eccentricity and high glacial ice volume. Because atmospheric winds serve as the major source of supply of quartz to the sediments at this site, these high quartz values reflect increased aridity at the source region. Except for short periods during interglacials, the characteristics of the surface waters in this region of the subarctic Pacific during much of the last 460,000 years were similar to those which exist today in the Sea of Okhotsk. The spectrum of winter sea surface temperature estimates, derived from siliceous microfaunal abundances, contains dominant frequency peaks at periods of 100,000, 41,000, and 23,000 years which are coherent with eccentricity, obliquity, and precession, respectively. Based upon the relationship of the Subarctic Front with the dominance of specific faunal asemblages, the front was positioned south of its present-day location throughout much of the late Pleistocene.

Model minimum performance specifications for lidar (laser) speed measurement devices.

Mode of access: Internet.

Model minimum performance specifications for police traffic radar devices.

Mode of access: Internet.

Direct and general support and depot maintenance repair parts and special tools lists : tractor, full tracked, low speed : diesel engine, medium drawbar pull, oscillating track, 74-in. minimum gage, power shift transmission, w/bulldozer, hydraulic-tilting, w/backrip scarifier, w/winch, reversible, rear, 1 drum (Allis-Chalmers model HD16M) ....

"April 1972."

DS, GS, and depot maintenance manual : tractor, full tracked, low speed, diesel engine, medium drawbar pull, oscillating tract, 74-in. minimum gage, power shift transmission w/bulldozer, hydraulic tilting w/back rip scarifier, w/winch reversible, rear, 1 drum (Allis-Chalmers model HD16M) FSN 2410-078-6483 w/ripper, hydraulic (Allis-Chalmers model HD16M) FSN 2410-078-6484.

Includes index.

Organizational maintenance manual : tractor, full tracked, low speed, diesel engine, medium drawbar pull, oscillating track, 74-inch minimum gage, power shift transmission, w/bulldozer, hydraulic tilting w/backrip, scarifier, w/winch reversible, rear, 1 drum (Allis-Chalmers model HD16M) FSN 2410-078-6483 ....

"September 1965."

Organizational and direct support, repair parts, and special tools list for drill, pneumatic, drifter, crawler mounted, self propelled, dry type, 220 lb class, minimum 4-1/2 inch bore, power feed, 1-1/2 inch lugged shank chuck w/ 12 each [sic] shank rock drill (Chicago Pneumatic Tool Company model G-900) (NSN 3820-00-930-1917).

"May 1976."

Operator and organizational maintenance manual : pumping assembly, flammable liquid, bulk transfer, lightweight, centrifugal, 100 gpm minimum, gasoline-engine-driven (Barnes model US6ACG), FSN 4320-150-6116.

Includes index.

Statnote 9: The one-way analysis of variance (random effects model)

There is an alternative model of the 1-way ANOVA called the 'random effects' model or ‘nested’ design in which the objective is not to test specific effects but to estimate the degree of variation of a particular measurement and to compare different sources of variation that influence the measurement in space and/or time. The most important statistics from a random effects model are the components of variance which estimate the variance associated with each of the sources of variation influencing a measurement. The nested design is particularly useful in preliminary experiments designed to estimate different sources of variation and in the planning of appropriate sampling strategies.

Statnote 30 : The one-way analysis of variance (ANOVA):fixed effects model

In Statnote 9, we described a one-way analysis of variance (ANOVA) ‘random effects’ model in which the objective was to estimate the degree of variation of a particular measurement and to compare different sources of variation in space and time. The illustrative scenario involved the role of computer keyboards in a University communal computer laboratory as a possible source of microbial contamination of the hands. The study estimated the aerobic colony count of ten selected keyboards with samples taken from two keys per keyboard determined at 9am and 5pm. This type of design is often referred to as a ‘nested’ or ‘hierarchical’ design and the ANOVA estimated the degree of variation: (1) between keyboards, (2) between keys within a keyboard, and (3) between sample times within a key. An alternative to this design is a 'fixed effects' model in which the objective is not to measure sources of variation per se but to estimate differences between specific groups or treatments, which are regarded as 'fixed' or discrete effects. This statnote describes two scenarios utilizing this type of analysis: (1) measuring the degree of bacterial contamination on 2p coins collected from three types of business property, viz., a butcher’s shop, a sandwich shop, and a newsagent and (2) the effectiveness of drugs in the treatment of a fungal eye infection.

Multi-model fitting based on minimum spanning tree

This paper presents a novel approach to the computation of primitive geometrical structures, where no prior knowledge about the visual scene is available and a high level of noise is expected. We based our work on the grouping principles of proximity and similarity, of points and preliminary models. The former was realized using Minimum Spanning Trees (MST), on which we apply a stable alignment and goodness of fit criteria. As for the latter, we used spectral clustering of preliminary models. The algorithm can be generalized to various model fitting settings, without tuning of run parameters. Experiments demonstrate the significant improvement in the localization accuracy of models in plane, homography and motion segmentation examples. The efficiency of the algorithm is not dependent on fine tuning of run parameters like most others in the field.

Age model and sedimentation rate of core M174/KL11 (Table 1)

Stable isotope and faunal records from the central Red Sea show high-amplitude oscillations for the past 380,000 years. Positive delta18O anomalies indicate periods of significant salt buildup during periods of lowered sea level when water mass exchange with the Arabian Sea was reduced due to a reduced geometry of the Bab el Mandeb Strait. Salinities as high as 53 per mil and 55 per mil are inferred from pteropod and benthic foraminifera delta18O, respectively, for the last glacial maximum. During this period all planktonic foraminifera vanished from this part of the Red Sea. Environmental conditions improved rapidly after 13 ka as salinities decreased due to rising sea level. The foraminiferal fauna started to reappear and was fully reestablished between 9 ka and 8 ka. Spectral analysis of the planktonic delta18O record documents highest variance in the orbital eccentricity, obliquity, and precession bands, indicating a dominant influence of climatically - driven sea level change on environmental conditions in the Red Sea. Variance in the precession band is enhanced compared to the global mean marine climate record (SPECMAP), suggesting an additional influence of the Indian monsoon system on Red Sea climates.

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application