(if the parameter is a class, read the attribute value of the class), and the variables in the url and header use placeholder { {}}, if the variable name is inconsistent with the parameter name, you can use the AliasAs annotation (which can be used on parameters or class attributes) ...
Commonly, a single record attribute, or a combination of attributes, the so-called blocking key, is used to split the database records into blocks. Next, under the assumption that any two records in different blocks are unlikely to be duplicates, only every two records in a same block are...
Meta decision trees (MDTs) are a novel method for combining multiple classifiers. The difference between meta and ordinary decision trees (ODTs) is that MDT leaves specify which base-level classifier should be used, instead of predicting the class value directly. The attributes used by MDTs are ...
A detailed understanding of herd types is needed for animal disease control and surveillance activities, to inform epidemiological study design and interpretation and to guide effective policy- and decision-making. A number of different methods have been used to classify herd types, including expert-...
we will describe the prior works about biomedical relation classification using PubMed to prove the originality of our methods (“Prior works on biomedical relation classification using PubMed” section). After that, we will explain our proposed approach for the development and evaluation of biomedical...
The XmlReader and XmlWriter classes can often be combined to provide simple streaming transformations rather than resorting to XSLT which requires a the document to be loaded into memory. This class combination is often faster and uses less memory, although it requires more c...
AU-based expression recognition methods demand action units whose data related to training has been previously labelled by experts [15]. This is a process which is quite time-consuming and labour-intensive. Deep neural networks are being widely used for a lot of pattern-recognition tasks, namely...
Here, \({{t}_{A}}\) and \({{t}_{B}}\) indicate LRIs predicted by two distinct methods, respectively. Performance comparison of THGB and other models THGB was compared with CellEnBoost21, CellGiQ29, CellComNet11, and PIPR. CellEnBoost used a variety of methods to extract its biolog...
medical field are still in the early stage [27]. Related research mainly adopted data enhancement strategies, which often brought uncertain noise and fell into unstable results [28]. Therefore, it is necessary to develop new few-shot learning methods for chronic disease risk prediction based on ...
class files, including information about any constants, fields, or methods defined within the one or more class files; and using the information contained within the one or more class files to create a native executable run time image comprised of a searchable library of pre-loaded and pre-...