SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

Microcharcoal concentration and elongation, and age model of sediment core MD96-2098

Although grassland and savanna occupy only a quarter of the world's vegetation, burning in these ecosystems accounts for roughly half the global carbon emissions from fire. However, the processes that govern changes in grassland burning are poorly understood, particularly on time scales beyond satellite records. We analyzed microcharcoal, sediments, and geochemistry in a high-resolution marine sediment core off Namibia to identify the processes that have controlled biomass burning in southern African grassland ecosystems under large, multimillennial-scale climate changes. Six fire cycles occurred during the past 170,000 y in southern Africa that correspond both in timing and magnitude to the precessional forcing of north-south shifts in the Intertropical Convergence Zone. Contrary to the conventional expectation that fire increases with higher temperatures and increased drought, we found that wetter and cooler climates cause increased burning in the study region, owing to a shift in rainfall amount and seasonality (and thus vegetation flammability). We also show that charcoal morphology (i.e., the particle's length-to-width ratio) can be used to reconstruct changes in fire activity as well as biome shifts over time. Our results provide essential context for understanding current and future grassland-fire dynamics and their associated carbon emissions.

Stratigraphic correlation of ODP Site 199-1218 and 199-1219

During Ocean Drilling Program Leg 199 a high-resolution (~1-2 cm/k.y.) biogenic sediment record from the late Paleocene to the early Miocene was recovered, containing an uninterrupted set of geomagnetic chrons as well as a detailed record of calcareous and siliceous biostratigraphic datum events. Shipboard lithologic proxy measurements and shore-based determinations of CaCO3 revealed regular cycles that can be attributed to climatic forcing. Discovering drill sites with well defined magneto- and biostratigraphic records that also show clear lithologic cycles is rare and valuable and creates the opportunity to develop a detailed stratigraphic intersite correlation, providing the basis to study paleoceanographic processes and mass accumulation rates at high resolution. Here we present extensive postcruise work that extends the shipboard composite depth stratigraphy by providing a high-resolution revised meters composite depth (rmcd) scale to compensate for depth distortion within individual cores. The depth-aligned data were then used to generate stacked records of lithologic proxy measurements. Making use of the increased signal-to-noise ratio in the stacked records, we then proceeded to generate a detailed site-to-site correlation between Sites 1218 and 1219 in order to decrease the depth uncertainty for magneto- and biostratigraphic datums. Stacked lithologic proxy records in combination with discrete measurements of CaCO3 were then exploited to calculate high-resolution carbonate concentration curves by regression of the multisensor track data with discrete measurements. By matching correlative features between the cores and wireline logging data, we also rescaled our core rmcd back to in situ depths. Our study identifies lithology-dependent core expansion due to unloading as the mechanism of varying stratigraphic thicknesses between cores.

Tie points and log-adjusted depth scales for ODP Leg 207 Sites

Multiple copies of Cretaceous black shales extending from the early Cenomanian to the end of the Santonian were recovered at five sites on Demerara Rise during Leg 207 of the Ocean Drilling Program. These sediments are primarily composed of laminated organic-rich claystones interbedded with coarser, lightly laminated foraminferal-bearing packstones and wackestones. The black shales represent the local expression of widespread organic-rich sedimentation in the Atlantic during the mid-Cretaceous. However, incomplete recovery prevented construction of continuous composite sections, resulting in uncertainties concerning the correct stratigraphic placement of individual cores. By combining high-resolution measurements of bulk density collected shipboard on the multisensor track with continuous downhole measurements of formation resistivity using the Formation MicroScanner, an equivalent logging depth scale was constructed for black shales recovered from Sites 1258, 1260, and 1261. The integrated depths approach centimeter-scale resolution and are supported by comparisons of coarser resolution natural gamma ray emissions collected on cores and through downhole logging operations. The new depths highlight the extent of both intra- and intercore gaps and provide an opportunity to further constrain temporal and spatial paleoceanographic changes captured in proxy records from these sediments.

Time series analysis of a Web search engine transaction log

In this paper, we use time series analysis to evaluate predictive scenarios using search engine transactional logs. Our goal is to develop models for the analysis of searchers’ behaviors over time and investigate if time series analysis is a valid method for predicting relationships between searcher actions. Time series analysis is a method often used to understand the underlying characteristics of temporal data in order to make forecasts. In this study, we used a Web search engine transactional log and time series analysis to investigate users’ actions. We conducted our analysis in two phases. In the initial phase, we employed a basic analysis and found that 10% of searchers clicked on sponsored links. However, from 22:00 to 24:00, searchers almost exclusively clicked on the organic links, with almost no clicks on sponsored links. In the second and more extensive phase, we used a one-step prediction time series analysis method along with a transfer function method. The period rarely affects navigational and transactional queries, while rates for transactional queries vary during different periods. Our results show that the average length of a searcher session is approximately 2.9 interactions and that this average is consistent across time periods. Most importantly, our findings shows that searchers who submit the shortest queries (i.e., in number of terms) click on highest ranked results. We discuss implications, including predictive value, and future research.

Automatic solder joint defect classification using the Log-Gabor filter

This paper proposes the validity of a Gabor filter bank for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance measure based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.

Solder joint defects classification using the Log-Gabor Filter, the Discrete Wavelet Transform and the Discrete Cosine Transform

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure project quality and reliability. This paper proposes the use of the Log-Gabor filter bank, Discrete Wavelet Transform and Discrete Cosine Transform for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.