基于本体论的食品安全数据融合框架研究

庞杂的食品安全抽检数据由于分类编码问题不统一而使得数据融合难以实现，并进一步阻碍了与其他监测系统的融合与数据分析。解决各种食品安全数据融合的问题将对国家的食品安全监管具有重要意义，文章归纳总结了食品安全大数据在分类编码方面的主要存在问题，引入本体论的思想，并结合计算机工程，提出了构建基于本体论的计算机工程与大数据分析相结合的总体框架，以实现数据融合，服务政府和企业的有效监管。     

Virtual engineering of cyber-physical automation systems: The case of control logic

Mastering the fusion of information and communication technologies with physical systems to cyber-physical automation systems is of main concern to engineers in the industrial automation domain. The engineering of these systems is challenging as their distributed nature and the heterogeneity of stakeholders and tools involved in their engineering contradict the need for the simultaneous engineering of their cyber and physical parts over their life cycle. This paper presents a novel approach based on the virtual engineering method, which provides support for the simultaneous engineering of the cyber and physical parts of automation systems. The approach extends and integrates the life cycle centered view mandated by current conceptual architectures and the digital twin paradigm with an integrated, iterative engineering method. The benefits of the approach are highlighted in a case study related to the engineering of the control logic of a cyber physical automation system originating from the process engineering domain. We describe for the first time a modular domain ontology, which formally describes the cyber and physical part of the system. We present cyber services built on top of the ontology layer, which allow to automatically verify different control logic types and simultaneously verify cyber and physical parts of the system in an incremental manner.     

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.     

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.     

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.     

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.     

历史的当下:遗产保护实践下近代史研究反思

历史的书写，从来都逃避不了时代的主观性；而所谓历史的真实，亦无法摆脱客体的相对性，因而呈现出错综交杂的表象，难以一窥全貌。本文重拾中国营造学社开启的，以实物和史料相互印证的研究方法；基于多个真实的遗产保护案例，通过建筑本体勘查、历史影像的三维数字化还原、特殊节点构造的拆解分析、实物湮灭后的类型化推测等工作，试图破解特殊的建筑结构体系及做法，揭示建筑物背后隐藏的历史和文化。一切历史都是当代史，遗产保护实践中的探索与反思，不仅可以更好地叙述一段贴近真实的历史，同时，也构筑起一个深具历 史感的当下。     

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。     

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.     

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.