Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
614
result(s) for
"Anthropology Data processing."
Sort by:
Anthropology, Space, and Geographic Information Systems
Major advances in the use of geographic information systems have been made in both anthropology and archaeology.Yet there are few published discussions of these new applications and their use in solving complex problems.
eBook
Media anthropology
A state-of-the-art overview of anthropological approaches to the study of media this new text brings together an international team of contributors who identify the major concepts, methods and bibliography involved and provide examples of current research.
eBook
Issues with data and analyses
Some aspects of science, taken at the broadest level, are universal in empirical research. These include collecting, analyzing, and reporting data. In each of these aspects, errors can and do occur. In this work, we first discuss the importance of focusing on statistical and data errors to continually improve the practice of science. We then describe underlying themes of the types of errors and postulate contributing factors. To do so, we describe a case series of relatively severe data and statistical errors coupled with surveys of some types of errors to better characterize the magnitude, frequency, and trends. Having examined these errors, we then discuss the consequences of specific errors or classes of errors. Finally, given the extracted themes, we discuss methodological, cultural, and systemlevel approaches to reducing the frequency of commonly observed errors. These approaches will plausibly contribute to the self-critical, self-correcting, ever-evolving practice of science, and ultimately to furthering knowledge.
Journal Article
Pitfalls of assessment of autonomic function by heart rate variability
Although analysis of heart rate variability is widely used for the assessment of autonomic function, its fundamental framework linking low-frequency and high-frequency components of heart rate variability with sympathetic and parasympathetic autonomic divisions has developed in the 1980s. This simplified framework is no longer able to deal with much evidence about heart rate variability accumulated over the past half-century. This review addresses the pitfalls caused by the old framework and discusses the points that need attention in autonomic assessment by heart rate variability.
Journal Article
Knee osteoarthritis has doubled in prevalence since the mid-20th century
Knee osteoarthritis (OA) is believed to be highly prevalent today because of recent increases in life expectancy and body mass index (BMI), but this assumption has not been tested using long-term historical or evolutionary data. We analyzed long-term trends in knee OA prevalence in the United States using cadaver-derived skeletons of people aged ≥50 y whose BMI at death was documented and who lived during the early industrial era (1800s to early 1900s; n = 1,581) and the modern postindustrial era (late 1900s to early 2000s; n = 819). Knee OA among individuals estimated to be ≥50 y old was also assessed in archeologically derived skeletons of prehistoric hunter-gatherers and early farmers (6000–300 B.P.; n = 176). OA was diagnosed based on the presence of eburnation (polish from bone-on-bone contact). Overall, knee OA prevalence was found to be 16% among the postindustrial sample but only 6% and 8% among the early industrial and prehistoric samples, respectively. After controlling for age, BMI, and other variables, knee OA prevalence was 2.1-fold higher (95% confidence interval, 1.5–3.1) in the postindustrial sample than in the early industrial sample. Our results indicate that increases in longevity and BMI are insufficient to explain the approximate doubling of knee OA prevalence that has occurred in the United States since the mid-20th century. Knee OA is thus more preventable than is commonly assumed, but prevention will require research on additional independent risk factors that either arose or have become amplified in the postindustrial era.
Journal Article
Data mining for sex estimation based on cranial measurements
•Machine learning algorithms are useful sex classifiers.•Classification rules and decision trees provide high accuracy rates.•The best sex classification accuracy is 91.9 %.•Nonstandard cranial measurements can be used for sex estimation.
The aim of the present study is to develop effective and understandable classification models for sex estimation and to identify the most dimorphic linear measurements in adult crania by means of data mining techniques. Furthermore, machine learning models and models developed through logistic regression analysis are compared in terms of performance. Computed tomography scans of 393 adult individuals were used in the study. A landmark-based approach was applied to collect the metric data. The three-dimensional coordinates of 47 landmarks were acquired and used for calculation of linear measurements. Two datasets of cranial measurements were assembled, including 37standard measurements and 1081 interlandmark distances, respectively. Three data mining algorithms were applied: the rule induction algorithms JRIP and Ridor, and the decision tree algorithm J48. Two advanced attribute selection methods (Weka BestFirst and Weka GeneticSearch) were also used. The best accuracy result (91.9 %) was achieved by a set of rules learnt by the JRIP algorithm from the dataset constructed by application of the GeneticSearch selection algorithm to the dataset of standard cranial measurements. The set consisted of five rules including seven cranial measurements. Its accuracy was even better than the classification rates achieved by the logistic regression models. Concerning the second dataset of nonstandard measurements, the best accuracy (88.3 %) was obtained by using classification models learnt by two algorithms – JRIP with a dataset preprocessed by the BestFirst selection algorithm and Ridor with preprocessing by the GeneticSearch selection algorithm. Our experiments show that for the two datasets mentioned above the rule-based models contain smaller sets of rules with shorter lists of measurements and achieve better classification accuracy results in comparison with decision tree-based models.
Journal Article
The importance of processing procedures and threshold values in CT scan segmentation of skeletal elements: An example using the immature os coxa
•CT scan processing protocols should remain consistent for accurate results.•Slight variation (e.g., ∼50 HU) in thresholding does not substantially alter resultant surfaces.•Error generated by scan processing is less than allowable measurement error (1–2mm).
As the accessibility and utility of virtual databases of skeletal collections continues to grow, the impact that scan processing procedures has on the accuracy of data obtained from virtual databases remains relatively unknown. This study quantifies the intra- and inter-observer error generated from varying computed tomography (CT) scan processing protocols, including re-segmentation, incrementally varying thresholding value, and data collectors’ selection of the threshold value on a set of virtual subadult pelves. Four observers segmented the subadult ossa coxarum from postmortem CT scans of the fully-fleshed bodies of eleven individuals of varying ages. Segmentation protocol was set, with the exception of each observer selecting their own thresholding value for each scan. The resulting smoothed pelvic surfaces were then compared using deviation analyses. Root mean square error (RMSE), average distance deviation, and maximum deviation distances demonstrated that thresholding values of ∼50 HU (Hounsfield units) are easily tolerated, the surfaces generated are robust to error, and threshold value selection does not systematically vary with user experience. The importance of consistent methodology during segmentation protocol is highlighted here, especially with regards to consistency in both selected thresholding value as well as smoothing protocol, as these variables can affect subsequent measurements of the resultant surfaces.
Journal Article
Unmanned aerial vehicle (UAV) paired with LiDAR sensor to detect bodies on surface under vegetation cover: Preliminary test
The use of unmanned aerial vehicles (UAVs) has become increasingly accessible, enabling their deployment in a diverse range of operational contexts. UAVs have been tested as part of search and rescue missions. Following the successful use of UAVs in the wilderness medicine literature, we questioned their ability to be used in forensic context to search for missing persons or human remains, especially under canopy cover. Subsequently, various sensors were then repurposed from their original applications to address forensic concerns. This preliminary study aimed to evaluate the efficacy of airborne Light Detection and Ranging sensors (LiDAR) in detecting a concealed human body on a surface within a densely vegetated search area. To proceed, two LiDAR sensors were tested with several modalities. A dendrometric method was used to estimate the tree density of the search area, and the Normalized Difference Vegetation Index (NDVI) was used to bring precision in the appreciation of canopy cover density. The results showed that airborne LiDAR sensors can capture body signatures in areas with dense vegetation. The ground point density reached 0.26 % in a high-vegetated area. The study highlighted the importance of refining data processing techniques, including point cloud selection and the implementation of true positive/false positive analysis, to improve detection accuracy. Furthermore, the potential integration of complementary sensors such as thermographic and multispectral sensors was discussed, which may enhance the detection of thermal anomalies and chemical markers associated with decomposition.
•The airborne LiDAR allows to detect body signature on surface under canopy.•LiDAR supporting 5 echoes is more efficient than 3 echoes LiDAR in locating body signature.•The RGB mapping camera included in the LiDAR L2 Zenmuse allows to detect cloths colors under vegetation cover.•The L1 LiDAR sensor ground point percentage was 0.11 % and L2 LiDAR sensor ground point percentage was 0.26 % despite canopy.
Journal Article
Female exogamy and gene pool diversification at the transition from the Final Neolithic to the Early Bronze Age in central Europe
Human mobility has been vigorously debated as a key factor for the spread of bronze technology and profound changes in burial practices as well as material culture in central Europe at the transition from the Neolithic to the Bronze Age. However, the relevance of individual residential changes and their importance among specific age and sex groups are still poorly understood. Here, we present ancient DNA analysis, stable isotope data of oxygen, and radiogenic isotope ratios of strontium for 84 radiocarbon-dated skeletons from seven archaeological sites of the Late Neolithic Bell Beaker Complex and the Early Bronze Age from the Lech River valley in southern Bavaria, Germany. Complete mitochondrial genomes documented a diversification of maternal lineages over time. The isotope ratios disclosed the majority of the females to be nonlocal, while this is the case for only a few males and subadults. Most nonlocal females arrived in the study area as adults, but we do not detect their offspring among the sampled individuals. The striking patterns of patrilocality and female exogamy prevailed over at least 800 y between about 2500 and 1700 BC. The persisting residential rules and even a direct kinship relation across the transition from the Neolithic to the Bronze Age add to the archaeological evidence of continuing traditions from the Bell Beaker Complex to the Early Bronze Age. The results also attest to female mobility as a driving force for regional and supraregional communication and exchange at the dawn of the European metal ages.
Journal Article