In this paper, we first establish a Schwarz-Pick lemma for higher-order derivatives of planar harmonic mappings, and apply it to obtain univalency criteria. Then we discuss distortion theorems, Lipschitz continuity an...In this paper, we first establish a Schwarz-Pick lemma for higher-order derivatives of planar harmonic mappings, and apply it to obtain univalency criteria. Then we discuss distortion theorems, Lipschitz continuity and univalency of planar harmonic mappings defined in the unit disk with linearly connected images.展开更多
Metadata aggregators and service providers harvest entire collections or they restrict harvesting by date or sets.However most often user approach to collections is not by dates or set names but by domain based keywor...Metadata aggregators and service providers harvest entire collections or they restrict harvesting by date or sets.However most often user approach to collections is not by dates or set names but by domain based keywords.Harvesting by domains is an issue when service providers attempt to collect data from multiple sources.The main problem is that harvesters,at present,do not have the facility to distinguish themes such as domains.In the present work,an attempt has been through Tharvest,a thematic harvester model using the proposed methodology harvesting agricultural resources from generic repositories.Tharvest encompasses a process where technical terms of the domain of agriculture are taken from AGROVOC,a multilingual,structured controlled vocabulary designed to cover concepts and terminologies in the agriculture domain.AGROVOC is deployed to provide the basis for selective harvesting.The system components and workflows are presented and described.Metadata aggregators provide end-users a single platform discovery facility to resources collected from various data providers.It is observed that aggregators such as INDUS[www.drtc.isibang/ac.in/indus]dealing with agriculture and related domains facilitate aggregating metadata from not only repositories but also other sources such as journals and enable a centralized access to full text and objects.While harvesting can be fairly simple and straight forward,it is not without its challenges.This paper intends to highlight some of the issues in harvesting metadata in agricultural domain.The particular focus is to identify agriculture related metadata from generic sets.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.11401184 and 11571216)Hu’nan Province Natural Science Foundation of China(Grant No.2015JJ3025)+3 种基金the Excellent Doctoral Dissertation of Special Foundation of Hu’nan Province(higher education 2050205)the Construct Program of the Key Discipline in Hu’nan Province(Grant No.[2011]76)Academy of Finland(Grant No.278328)the Vaisala Foundation of the Finnish Academy of Science and Letters
文摘In this paper, we first establish a Schwarz-Pick lemma for higher-order derivatives of planar harmonic mappings, and apply it to obtain univalency criteria. Then we discuss distortion theorems, Lipschitz continuity and univalency of planar harmonic mappings defined in the unit disk with linearly connected images.
文摘Metadata aggregators and service providers harvest entire collections or they restrict harvesting by date or sets.However most often user approach to collections is not by dates or set names but by domain based keywords.Harvesting by domains is an issue when service providers attempt to collect data from multiple sources.The main problem is that harvesters,at present,do not have the facility to distinguish themes such as domains.In the present work,an attempt has been through Tharvest,a thematic harvester model using the proposed methodology harvesting agricultural resources from generic repositories.Tharvest encompasses a process where technical terms of the domain of agriculture are taken from AGROVOC,a multilingual,structured controlled vocabulary designed to cover concepts and terminologies in the agriculture domain.AGROVOC is deployed to provide the basis for selective harvesting.The system components and workflows are presented and described.Metadata aggregators provide end-users a single platform discovery facility to resources collected from various data providers.It is observed that aggregators such as INDUS[www.drtc.isibang/ac.in/indus]dealing with agriculture and related domains facilitate aggregating metadata from not only repositories but also other sources such as journals and enable a centralized access to full text and objects.While harvesting can be fairly simple and straight forward,it is not without its challenges.This paper intends to highlight some of the issues in harvesting metadata in agricultural domain.The particular focus is to identify agriculture related metadata from generic sets.
