Estimation of probabilities of label imperfections and correction of mislabels

There are no author-identified significant results in this report

Probabilistic cluster labeling of imagery data

The problem of obtaining the probabilities of class labels for the clusters using spectral and spatial information from a given set of labeled patterns and their neighbors is considered. A relationship is developed between class and clusters conditional densities in terms of probabilities of class labels for the clusters. Expressions are presented for updating the a posteriori probabilities of the classes of a pixel using information from its local neighborhood. Fixed-point iteration schemes are developed for obtaining the optimal probabilities of class labels for the clusters. These schemes utilize spatial information and also the probabilities of label imperfections. Experimental results from the processing of remotely sensed multispectral scanner imagery data are presented

Earth Resources: A continuing bibliography, issue 28

This bibliography lists 436 reports, articles, and other documents introduced into the NASA scientific and technical information system between October 1, 1980 and December 31, 1980. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems instrumentation and sensors, and economic analysis

Generation of Explanations for Logic Reasoning

This thesis delves into a fortiori arguments in deductive reasoning, underscoring their relevance in various domains such as law, philosophy, and artificial intelligence. The research is centred on employing GPT-3.5-turbo to automate the analysis of these arguments, with a focus on understanding intricate reasoning processes, generating clear and coherent explanations, and creating novel arguments. The methodology encompasses a series of tasks including detailed reasoning, interpretation, and the augmentation of a fortiori arguments. It involves meticulously identifying these arguments in diverse contexts, differentiating comparative elements, and categorizing them based on their logical structure. Extensive experiments reveals the challenges encountered by GPT-3.5-turbo in accurately detecting and classifying a fortiori arguments. Nevertheless, the model demonstrates a performance that rivals specialized models, particularly in extracting key components and interpreting underlying properties. The integration of external information into the model's processing significantly elevates the quality of the generated explanations. Additionally, the model exhibits a noteworthy capability in augmenting arguments, thus contributing to the enrichment of the data set. Despite facing certain limitations, this thesis makes significant contributions to the fields of artificial intelligence and logical reasoning. It introduces novel methodologies, establishes a rigorous evaluation framework, and provides deep insights that set the stage for future advancements in automated logical reasoning. The findings and methodologies presented herein not only underscore the potential of AI in complex reasoning tasks but also highlight areas for future research and development.Comment: 78 Pages, 16 Figures, Thesis Presentation is available at https://drive.google.com/file/d/1wLIBsjfLvO11PjCS6qx4Y9UgRBUfq3wQ/view?usp=sharin

Understanding and improving high-throughput sequencing data production and analysis

Advances in DNA sequencing revolutionized the field of genomics over the last 5 years. New sequencing instruments make it possible to rapidly generate large amounts of sequence data at substantially lower cost. These high-throughput sequencing technologies (e.g. Roche 454 FLX, Life Technology SOLiD, Dover Polonator, Helicos HeliScope and Illumina Genome Analyzer) make whole genome sequencing and resequencing, transcript sequencing as well as quantification of gene expression, DNA-protein interactions and DNA methylation feasible at an unanticipated scale. In the field of evolutionary genomics, high-throughput sequencing permitted studies of whole genomes from ancient specimens of different hominin groups. Further, it allowed large-scale population genetics studies of present-day humans as well as different types of sequence-based comparative genomics studies in primates. Such comparisons of humans with closely related apes and hominins are important not only to better understand human origins and the biological background of what sets humans apart from other organisms, but also for understanding the molecular basis for diseases and disorders, particularly those that affect uniquely human traits, such as speech disorders, autism or schizophrenia. However, while the cost and time required to create comparative data sets have been greatly reduced, the error profiles and limitations of the new platforms differ significantly from those of previous approaches. This requires a specific experimental design in order to circumvent these issues, or to handle them during data analysis. During the course of my PhD, I analyzed and improved current protocols and algorithms for next generation sequencing data, taking into account the specific characteristics of these new sequencing technologies. The presented approaches and algorithms were applied in different projects and are widely used within the department of Evolutionary Genetics at the Max Planck Institute of Evolutionary Anthropology. In this thesis, I will present selected analyses from the whole genome shotgun sequencing of two ancient hominins and the quantification of gene expression from short-sequence tags in five tissues from three primates

JSC document index

The Johnson Space Center (JSC) document index is intended to provide a single source listing of all published JSC-numbered documents their authors, and the designated offices of prime responsibility (OPR's) by mail code at the time of publication. The index contains documents which have been received and processed by the JSC Technical Library as of January 13, 1988. Other JSC-numbered documents which are controlled but not available through the JSC Library are also listed