PepExplorer aids in the biological interpretation of de novo sequencing results;this is accomplished by assembling a list of homolog proteins obtained by aligning results from widely adopted de novo sequencing tools a...
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The rapid change of trading values from tangible assets to Intelectual Property has put both businesses and academia in a race to acquire and protect the rights to exploit such property. This is mainly accomplished in...
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The rapid change of trading values from tangible assets to Intelectual Property has put both businesses and academia in a race to acquire and protect the rights to exploit such property. This is mainly accomplished in the form of patent issuing by the governments, being time consuming and complicated due to the vast amount of documents that need to be analyzed in order to assert the novelty or validity of a patent application. Patent information retrieval research is thus growing quickly to support document analysis across multiple domains and information systems. One of the big challenges in patent analysis is the identification of the elements of innovation (concepts, processes, materials) and the relations between them, in the patent text. This paper presents a method for extracting semantic information from patent claims by using semantic annotations on phrasal structures, abstracting domain ontology information and outputting ontology-friendly structures to achieve generalization. An extraction system built upon the method is briefly evaluated on a document sample from INPI, the Brazilian patent office, a challenging information source.
Purpose: A calibrationless parallel imaging reconstruction method, termed simultaneous autocalibrating and k-space estimation (SAKE), is presented. It is a data-driven, coil-by-coil reconstruction method that does not...
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Heart rate variability (HRV) is known to be one of the representative ECG-derived features that are useful for diverse pervasive healthcare applications. The advancement in daily physiological monitoring technology is...
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ISBN:
(纸本)9781424479276
Heart rate variability (HRV) is known to be one of the representative ECG-derived features that are useful for diverse pervasive healthcare applications. The advancement in daily physiological monitoring technology is enabling monitoring of HRV in people's everyday lives. In this study, we evaluate the feasibility of measuring ECG-derived features such as HRV, only using the smartphone-integrated ECG sensors system named Sinabro. We conducted the evaluation with 13 subjects in five predetermined smartphone use cases. The result shows the potential that the smartphone-based sensing system can support daily monitoring of ECG-derived features;The average errors of HRV over all participants ranged from 1.65% to 5.83% (SD: 2.54~10.87) for five use cases. Also, all of individual HRV parameters showed less than 5% of average errors for the three reliable cases.
Background: Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. Objective: To develop a...
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Application code and processor parallelization, together with instruction set customization, are the most common and effective ways to enhance the performance and efficiency of application-specific processors (ASIPs)....
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To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 1...
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
Dynamic adaptation is the customization of a business process to make it applicable to a particular situation at any time of its life cycle. Adapting requires experience, and involves knowledge about various, internal...
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ISBN:
(纸本)9781467360845
Dynamic adaptation is the customization of a business process to make it applicable to a particular situation at any time of its life cycle. Adapting requires experience, and involves knowledge about various, internal and external, aspects of business. Thus, we argue for the application of adaptation rules, considering the context of a particular process instance. Furthermore, we state that a context-based adaptation environment should go beyond, and learn from decisions, as well as continuously identify new unforeseen situations (context definitions). The aim of this paper is to present a computational engine that infers the need to update situations and adaptation rules, suggesting changes to them. An application scenario is presented to discuss the usage of the proposal.
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