Content Characteristics of Knowledge Integration in the eHealth Field:An Analysis Based on Citation Contexts

Purpose:This study attempts to disclose the characteristics of knowledge integration in an interdisciplinary field by looking into the content aspect of knowledge.Design/methodology/approach:The eHealth field was chosen in the case study.Associated knowledge phrases(AKPs)that are shared between citing papers and their references were extracted from the citation contexts of the eHealth papers by applying a stem-matching method.A classification schema that considers the functions of knowledge in the domain was proposed to categorize the identified AKPs.The source disciplines of each knowledge type were analyzed.Quantitative indicators and a co-occurrence analysis were applied to disclose the integration patterns of different knowledge types.Findings:The annotated AKPs evidence the major disciplines supplying each type of knowledge.Different knowledge types have remarkably different integration patterns in terms of knowledge amount,the breadth of source disciplines,and the integration time lag.We also find several frequent co-occurrence patterns of different knowledge types.Research limitations:The collected articles of the field are limited to the two leading open access journals.The stem-matching method to extract AKPs could not identify those phrases with the same meaning but expressed in words with different stems.The type of Research Subject dominates the recognized AKPs,which calls on an improvement of the classification schema for better knowledge integration analysis on knowledge units.Practical implications:The methodology proposed in this paper sheds new light on knowledge integration characteristics of an interdisciplinary field from the content perspective.The findings have practical implications on the future development of research strategies in eHealth and the policies about interdisciplinary research.Originality/value:This study proposed a new methodology to explore the content characteristics of knowledge integration in an interdisciplinary field.

The Theory of Biomedical Knowledge Integration (Ⅶ)──The Non-Euclid Macro-Micro Transform Law

This article continued to do the scholastic pursuits on some profound mechanisms in the life systems, which are believed to be related to the further development of Medical Informatics. It discussed at first the structural nature of things, then probed a principle which is a basis for both of the fractal theory and the wavelet analysis, being called the shape-constancy law of the basic constructors at the different scale levels. And the paper also ventured the equivalency between the shape of wave and matrix, thus presented a new concept "shaped-number", being expected to work in the operations of some bio-medical functions or shapes.

Using the KISO's Framework to Integrate Knowledge Sources

In complicated application environment such as CIMS (Computer Integrated Manufacture System) enterprise, it will bring great benefits to integrate distributed knowledge sources. But the difficulties of knowledge sharing and reuse seriously encumbrance the implementation of knowledge integration. In this paper, we describe how a framework of knowledge-integrated system based on ontology (KISO) can be used to support integrating distributed knowledge sources.

Improving the Efficiency of Multi-Objective Grasshopper Optimization Algorithm to Enhance Ontology Alignment

Ontology alignment is an essential and complex task to integrate heterogeneous ontology.The meta-heuristic algorithm has proven to be an effective method for ontology alignment.However,it only applies the inherent advantages of metaheuristics algorithm and rarely considers the execution efficiency,especially the multi-objective ontology alignment model.The performance of such multi-objective optimization models mostly depends on the well-distributed and the fast-converged set of solutions in real-world applications.In this paper,two multi-objective grasshopper optimization algorithms(MOGOA)are proposed to enhance ontology alignment.One isε-dominance concept based GOA(EMO-GOA)and the other is fast Non-dominated Sorting based GOA(NS-MOGOA).The performance of the two methods to align the ontology is evaluated by using the benchmark dataset.The results demonstrate that the proposed EMO-GOA and NSMOGOA improve the quality of ontology alignment and reduce the running time compared with other well-known metaheuristic and the state-of-the-art ontology alignment methods.

SUSTAINABLE NITROGEN MANAGEMENT FOR VEGETABLE PRODUCTION IN CHINA

Inappropriate nitrogen fertilizer management for the intensive Chinese vegetable production has caused low N use efficiency(NUE),high reactive nitrogen(Nr)losses and serious environmental risks with limited yield increase.Innovative N management strategy is an urgent need to achieve sustainable vegetable production.This paper summarizes recent studies on Nr losses and identifies the limitations from Chinese vegetable production systems and proposes three steps for sustainable N management in Chinese vegetable production.The three N management steps include,but are not limited to,(1)knowledge-based optimization of N fertilizer rate strategy,which maintains soil N supply to meet the dynamic vegetable demand in time,space and quantity;(2)innovative products and technology,which regulates the soil N forms and promotes the vegetable root growth to reduce the Nr loss;(3)integrated knowledge and products strategy(IKPS).The knowledge-based optimization of N fertilizer rate strategy and innovative products and technology,can maintain or increase vegetable yield,significantly improve NUE,and mitigate the region-specific and crop-specific Nr losses.More importantly,IKPS,based on combination of in-season root-zone N management strategy,innovative products and technology,and best crop cultivation management,is needed to produce more vegetables with lower Nr losses.