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.     

Modeling Smart Grid neighborhoods with the ENERsip ontology

The electricity consumption in the buildings sector has been steadily increasing during the last decade, up to the point that energy efficiency in this sector has become a major problem for governments, utilities, customers, and the environment. The foreseen high penetration of distributed micro-generation facilities based on renewables can help to reduce the environmental footprint of buildings and households, although the complexity of managing effectively the electric grid increases dramatically under these conditions. The IEEE 2030 standard for interoperability in the Smart Grid remarks upon the importance of well-defined data models in such complex scenarios and puts emphasis on the benefits of ontologies and OWL (Web Ontology Language) for this purpose. This paper presents an OWL-based ontology that formally defines the vocabulary and taxonomy and captures the engineering and business semantics of this domain of knowledge (i.e., energy efficiency in the so-called nZEN – nearly Zero-Energy Neighborhoods). This ontology has been defined under the scope of the EU (European Union) research project ENERsip. The paper also highlights the main benefits the ontology brought to all the phases of the project life cycle, as well as how future work can make the most out of it.     

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.     

Engineering knowledge formalization and proposition for informatics development towards a CAD-integrated DfX system for product design

Target design methodologies (DfX) were developed to cope with specific engineering design issues such as cost-effectiveness, manufacturability, assemblability, maintainability, among others. However, DfX methodologies are undergoing the lack of real integration with 3D CAD systems. Their principles are currently applied downstream of the 3D modelling by following the well-known rules available from the literature and engineers’ know-how (tacit internal knowledge).This paper provides a method to formalize complex DfX engineering knowledge into explicit knowledge that can be reused for Advanced Engineering Informatics to aid designers and engineers in developing mechanical products. This research work wants to define a general method (ontology) able to couple DfX design guidelines (engineering knowledge) with geometrical product features of a product 3D model (engineering parametric data). A common layer for all DfX methods (horizontal) and dedicated layers for each DfX method (vertical) allow creating the suitable ontology for the systematic collection of the DfX rules considering each target. Moreover, the proposed framework is the first step for developing (future work) a software tool to assist engineers and designers during product development (3D CAD modelling).A design for assembly (DfA) case study shows how to collect assembly rules in the given framework. It demonstrates the applicability of the CAD-integrated DfX system in the mechanical design of a jig-crane. Several benefits are recognized: (i) systematic collection of DfA rules for informatics development, (ii) identification of assembly issues in the product development process, and (iii) reduction of effort and time during the design review.     

An ontology-based metamodel for multiagent-based simulations

Multiagent-based simulations enable us to validate different use-case scenarios in a lot of application domains. The idea is to develop a realistic virtual environment to test particular domain-specific procedures. This paper presents our general framework for interactive multiagent-based simulations in virtual environments. The major contribution of this paper is the integration of the notion of ontology as a core element to the design process of a behavioral simulation. The proposed metamodel describes the concepts of a multiagent simulation using situated agents moving in a semantically enriched 3D environment. The agents perceive the geometric and semantic data in the surrounding environment. They are also able to act in this environment by using high-level actions, which are described by the ontology of the environment. The concepts relating to the environment, the agent, and the entire simulation models are presented. Additionally, guidelines are given to exploit the simulation results to characterize the agents. Finally, a simple application of the metamodel is presented, based upon the use of Industry Foundation Classes.     

新时代呼唤新的建筑美学──就当下建筑、空间环境问题访中国后现代研究所所长李正天

世界是一个立体的太极球，以美国为代表的西方文明是一种阳性文明，加州则是阳性文明的阴点；以中国为代表的东方文明是一种阴性文明，广东则是阴性文明的阳点，两大文明相互激活，相互补充，定能够造就一种全新的文明。     

从政治视角理解和研究城市规划

城市规划不仅仅是一种专业活动,更是一种社会活动,掌握政治知识对城市规划专业实践和社会活动都有着重要的意义.政治知识应成为城市规划学科建设不容忽视的一部分.对城市规划政治的研究,可从城市规划的价值基础、城市规划事件过程和城市规划参与者三个方面展开.     

物联网本体存储数据可撤销加密仿真研究

针对物联网密钥不可随机拆分与撤销,本体存储数据容易遭到外界入侵,导致用户隐私信息泄露,提出物联网本体存储数据可撤销加密方法。根据数据可撤销加密的理论确定双线性映射函数,通过加密撤销的困难假设构建了物联网本体存储数据可撤销模型。对存储数据进行可撤销运算,采用了周期更新思想,将用户密钥属性、用户身份以及时间进行划分,并根据访问树的节点数据对用户存储数据进行加密计算。通过主要密钥随机拆分撤销运算,根据结果对存储数据可撤销加密进行安全认证。仿真结果表明,采用可撤销加密方法能够实现物联网密钥的随机拆分,缩短用户密钥更新周期,数据安全性更高。