Abstract We present an abstract development of Gödel’s incompleteness theorems, performed with the help Isabelle/HOL proof assistant. analyze sufficient conditions for applicability our theorems to a partially specified logic. In addition usual benefits generality, perspective enables comparison between alternative approaches from literature. These include Rosser’s variation first theorem, Jero...

Despite the success of deep learning methods in medical image segmentation tasks, human-level performance relies on massive training data with high-quality annotations, which are expensive and time-consuming to collect. The fact is that there exist low-quality annotations label noise, leads suboptimal learned models. Two prominent directions for noisy labels include pixel-wise noise robust imag...

This paper offers a genealogy of the field mass media and communication theory research, with purpose distilling grand narrative studies science. Such ‘story stories’ is articulated recurring concerns over categories taxonomies process, rapid development penetration new information technologies, attempts by scholars around world to respond our increasingly complex convergent environment. In con...

This paper aims to build integrated forward and reverse logistics model, and to optimize it with closed loop supply chain (CLSC). After that, we evaluate the effectiveness of the proposed model with the numerical examples, and simulate it with a bottles distilling/sale company in Korea. This paper designs the method of calculation for a solution using optimization algorithms with the priority-b...

Single-task models (STMs) struggle to learn sophisticated representations from a finite set of annotated data. Multitask learning approaches overcome these constraints by simultaneously training various associated tasks, thereby generic among tasks sharing some layers the neural network architecture. Because this, multitask (MTMs) have better generalization properties than those single-task lea...

The last several decades have seen significant advances in fluid–mechanical, water-quality, and ecological observation systems, as well related scientific computing capabilities [...]

From its early stages, the community of Pattern Recognition and Computer Vision has considered importance leveraging structural information when understanding images. Usually, graphs have been proposed as a suitable model to represent this kind due their flexibility representational power able codify both, components, objects, or entities pairwise relationship. Even though successfully applied ...