The COVID-19 pandemic has severely affected the world’s manufacturing industry, particularly in terms of the continued increase in logistics costs that has led to an increase in business operating costs. This study proposes a two-stage model for evaluating the most appropriate outsourcing logistics companies for a manufacturing factory. In the first stage, a modified Delphi method was used to recruit experienced experts to determine criteria for evaluating outsourcing logistics vendors and establish a hierarchical structure. In the second stage, the analytic hierarchy process (AHP) was used to evaluate suitable logistics companies based on the hierarchical structure. Finally, a case study was conducted to demonstrate the suitability of the two-stage model for evaluating outsourcing logistics companies for reducing logistics costs while maintaining service quality. The proposed model can be used as a basis for evaluating outsourcing logistics companies.
Abstract:In the ubiquitous computing environment, context reasoning is an important issue of context-awareness. It is used to deduce desired or higher-level context and then to provide suitable services automatically. The previous context-reasoning approaches are mainly non-temporal. The reasoning is according to the real-time contexts without time information. However, temporal contexts are very important information for context-awareness. Therefore, a temporal context reasoning model (TempCRM) based on resource description framework (RDF) and Web ontology language (OWL) is proposed in this paper. TempCRM is used for inferring the dangerous level of a smart home. In a home environment, a potential dangerous situation is caused by a series of temporal events. A temporal event is represented as a RDF-based temporal context. A smart home ontology is defined for the terms and relationships used in the temporal context. Then, a set of reasoning rules can be defined for inferring and computing the dangerous level. In the simulation study, a script with dangerous situations is designed to evaluate the dangerous level generated by TempCRM. The result illustrates that TempCRM is useful to alarm the inhabitant and thus prevent the occurrence of an incident from the temporal contexts.
As with rapid growth of the computer technology, Elearning systems usually require many hardware and software resources, There are numerous educational institutions that cannot offer such investments, and cloud learning platform is the best solution for them. This paper proposes a model of using cloud computing and learning network upon cloud-learning solutions development. The cloud-learning platform combined with different types of games is gradually noticed by people because it can enhance user learning motivation. This research has developed a Chinese language cloud-learning system for the new immigrant based on games mode, and investigated the properties of game-based cloud-learning system, expecting to help more and more new immigrants in Taiwan. The basic concept for designing the system is developing the learning games network using digital materials, which is applied to the cloud learning platform to attract the immigrant residents and assist them to improve Chinese language skills.
We develop aftamework using ontology inference and semantic processing techniques to help biologists to extract knowledge directly from a large scale of biological literature in NCBI PubMed. The system integrated various sharable thesauri of WordNet, MeSH (Medical Subject Heading), and GO (Gene ontology) to support the automatic semantic annotation and analysis. The natural language processing and semantc processing are facilitated by the ontological inference, and the system could automatically extract the correct molecular interactions from the complex sentences in an abstract automatically. Itfacilitates the biologists not only to save time and efforts to construct and analyze biological pathways, but also to discover the novel molecular interactions by comparing the information extractedfrom the literature with that in such existing pathway database as KEGG. We evaluated the system performance based on the pathways in Apoptosis domain
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.