The International Society for the Study of Vascular Anomalies (ISSVA) ontology

The International Society for the Study of Vascular Anomalies (ISSVA) provides a classification for vascular anomalies that enables specialists to unambiguously classify diagnoses. This classification is only available in PDF format and is not machine-readable, nor does it provide unique identifiers that allow for structured registration. In this paper, we describe the process of transforming the ISSVA classification into an ontology. We also describe the structure of this ontology, as well as two applications of the ontology using examples from the domain of rare disease research. We used the expertise of an ontology expert and clinician during the development process. We semi-automatically added mappings to relevant external ontologies using automated ontology matching systems and manual assessment by experts. The ISSVA ontology should contribute to making data for vascular anomaly research more Findable, Accessible, Interoperable, and Reusable (FAIR). The ontology is available at https://bioportal.bioontology.org/ontologies/ISSVA.     

A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines

In this article we illustrate a methodology for building cross-language search engine. A synergistic approach between thesaurus-based approach and corpus-based approach is proposed. First, a bilingual ontology thesaurus is designed with respect to two languages: English and Spanish, where a simple bilingual listing of terms, phrases, concepts, and subconcepts is built. Second, term vector translation is used – a statistical multilingual text retrieval techniques that maps statistical information about term use between languages (Ontology co-learning). These techniques map sets of t f id f term weights from one language to another. We also applied a query translation method to retrieve multilingual documents with an expansion technique for phrasal translation. Finally, we present our findings.     

Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

This research proposes ACARDS (Augmented-Context bAsed RecommenDation Service) framework that is able to utilize knowledge over the Linked Open Data (LOD) cloud to recommend context-based services to users. To improve the level of user satisfaction with the result of the recommendation, the ACARDS framework implements a novel recommendation algorithm that can utilize the knowledge over the LOD cloud. In addition, the noble algorithm is able to use new concepts like the enriched tags and the augmented tags that originate from the hashtags on the SNSs materials. These tags are utilized to recommend the most appropriate services in the user’s context, which can change dynamically. Last but not least, the ACARDS framework implements the context-based reshaping algorithm on the augmented tag cloud. In the reshaping process, the ACARDS framework can recommend the highly receptive services in the users’ context and their preferences. To evaluate the performance of the ACARDS framework, we conduct four kinds of experiments using the Instagram materials and the LOD cloud. As a result, we proved that the ACARDS framework contributes to increasing the query efficiency by reducing the search space and improving the user satisfaction on the recommended services.     

Supply chain planning and scheduling integration using Lagrangian decomposition in a knowledge management environment

The integration of planning and scheduling decisions in rigorous mathematical models usually results in large scale problems. In order to tackle the problem complexity, decomposition techniques based on duality and information flows between a master and a set of subproblems are widely applied. In this sense, ontologies improve information sharing and communication in enterprises and can even represent holistic mathematical models facilitating the use of analytic tools and providing higher flexibility for model building. In this work, we exploit this ontologies’ capability to address the optimal integration of planning and scheduling using a Lagrangian decomposition approach. Scheduling/planning sub-problems are created for each facility/supply chain entity and their dual solution information is shared by means of the ontological framework. Two case studies based on a STN representation of supply chain planning and scheduling models are presented to emphasize the advantages and limitations of the proposed approach.     

Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

双轴晶体主平面上倍频的相位匹配

从折射率椭球方程和折射率椭球面出发，讨论光束在双轴晶体中传播及偏振的特性、主平面倍频共线相位匹配（PM）问题，得到了双轴晶体主平面内激光所有可能PM倍频的8种偏振组合及其相应的PM角公式、有效非线性（NL）系数deff的一般表达式。结果表明：得到的公式简单，可大大简化PM参数计算及优化设计；折射率椭球面是单层曲面，比双层的折射率面简单；基于折射率椭球面寻找所有可能PM的类型、偏振组合的方法物理图像简明，易于理解，大大降低了双轴晶体PM问题分析的难度。     

小型直喷柴油机喷雾油线在燃烧室内分布的研究

利用AutoCAD和Pro/E软件，二次开发了一套分析直喷柴油机喷油油束在燃烧室匹配的三维可视化分析软件，依据充分利用燃烧室有有效空间，保证油气均匀混合的原则，给出了等空燃比喷雾油线在燃烧室内的分布方法，提出了匹配理论：直喷柴油机的喷雾油线应对称布置于燃烧室中心与油嘴中心的连线上，活塞位于上止点时油线形成的锥面应轴向等燃烧室的有效容积；相邻油线在活塞顶燃烧室的投影积值与各油孔和喷油嘴轴线形成的夹角不等造成的各喷孔油量差值相一致。     

断块油藏提高采收率对策及技术应用

针对孤岛油区断块油藏关系多、油水关系复杂、含水上升快、采收率低等问题，从储层平面、层间、层内分析剩余油分布规律和下一步增产挖潜方向，提出了该类油藏提高采收率的对策和技术保障。通过综合治理，累积增油617kt，增加可采储量50kt。     

Swoop: A Web Ontology Editing Browser

In this paper, we describe Swoop, a hypermedia inspired Ontology Browser and Editor based on OWL, the recently standardized Web-oriented ontology language. After discussing the design rationale and architecture of Swoop, we focus mainly on its features, using illustrative examples to highlight its use. We demonstrate that with its Web-metaphor, adherence to OWL recommendations and key unique features, such as Collaborative Annotation using Annotea, Swoop acts as a useful and efficient Web Ontology development tool. We conclude with a list of future plans for Swoop, that should further increase its overall appeal and accessibility.     

运动估计块匹配两级搜索算法

根据视频图像相邻块在空间上具有很大的相关性,吸收了矢量预测块匹配的核心思想,提出一种两级块匹配运动估计算法,在第一级中,首先根据矢量预测确定一个小区域,然后在此区域内进行快速搜索,如果在第一级中没有搜索到匹配块则进行第二级搜索,该算法可大大提高搜索速度.