F. Gant¹, L. Champaney¹, Ph. Rouch¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.14, No.3, pp. 97-98, 2010, DOI:10.3970/icces.2010.014.097

Abstract Widely used in aeronautics, bolted and riveted joints are subject to high and various loads during flight. The design of such elements is quite a challenge because of their large number and uncertain nonlinear behavior. Indeed, the control of joint properties such as bolt pretension, bolt hole clearance, and friction during manufacturing processes is an issue.
Engineering design uses a factor of safety (FoS) to quantify uncertainties, which often leads to an oversized structure. Here, the aim is to model uncertainty effects on quantities of interest in order to redefine a more accurate FoS that could reduce manufacturing costs.
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Syed Falahuddin Quadri¹, Xiaoyu Li^1,*, Desheng Zheng², Muhammad Umar Aftab¹, Yiming Huang³

Journal on Big Data, Vol.1, No.1, pp. 1-7, 2019, DOI:10.32604/jbd.2019.05899

Abstract Given the glut of information on the web, it is crucially important to have a system, which will parse the information appropriately and recommend users with relevant information, this class of systems is known as Recommendation Systems (RS)-it is one of the most extensively used systems on the web today. Recently, Deep Learning (DL) models are being used to generate recommendations, as it has shown state-of-the-art (SoTA) results in the field of Speech Recognition and Computer Vision in the last decade. However, the RS is a much harder problem, as the central variable in the recommendation system’s environment is the… More >

Chuanrong Wu^1,*, Veronika Lee¹, Mark E. McMurtrey²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 365-378, 2019, DOI:10.32604/cmc.2019.06949

Abstract Product innovation is regarded as a primary means for enterprises to maintain their competitive advantage. Knowledge transfer is a major way that enterprises access knowledge from the external environment for new product innovation. Knowledge transfer may face the risk of infringement of the intellectual property rights of other enterprises and the termination of licensing agreements by the knowledge source. Enterprises must develop independent innovation knowledge at the same time they profit from knowledge transfers. Therefore, new product development by an enterprise usually consists of three types of new knowledge: big data knowledge transferred from big data knowledge providers, private knowledge… More >

Lanlan Rui¹, Yabin Qin^1,*, Biyao Li¹, Zhipeng Gao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 291-315, 2019, DOI:10.31614/cmes.2018.04240

Abstract Maintenance is an important aspect in the lifecycle of communication network devices. Prevalent problems in the maintenance of communication networks include inconvenient data carrying and sub-optimal scheduling of work orders, which significantly restrict the efficiency of maintenance work. Moreover, most maintenance systems are still based on cloud architectures that slow down data transfer. With a focus on the completion time, quality, and load balancing of maintenance work, we propose in this paper a learning-based virus evolutionary genetic algorithm with multiple quality-of-service (QoS) constraints to implement intelligent scheduling in an edge network. The algorithm maintains the diversity of the population and… More >

Ziya Aktas¹, Semih Cetin²

CMES-Computer Modeling in Engineering & Sciences, Vol.76, No.2, pp. 133-162, 2011, DOI:10.3970/cmes.2011.076.133

Abstract The knowledge society has been developed and shaped by amazing improvements during the last two decades. On that development and improvement, social sciences such as psychology or anthropology have also had significant impact as much as real sciences like medicine or engineering, in particular, Information Technology or Information and Communications Technology. The new trends and explosion of knowledge due to Internet and Web technologies have radically changed the way we structure business and its main building block, i.e. "knowledge". Though information/knowledge system development efforts have been regarded formerly as mere information technology activities, now we have been experiencing alternative ways… More >

Dun Li¹, Hong Wu¹, Jinzhu Gao², Zhuoyun Liu¹, Lun Li¹, Zhiyun Zheng^1,*

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 301-321, 2019, DOI:10.32604/cmc.2019.05953

Abstract With the rapid development of the semantic web and the ever-growing size of uncertain data, representing and reasoning uncertain information has become a great challenge for the semantic web application developers. In this paper, we present a novel reasoning framework based on the representation of fuzzy PR-OWL. Firstly, the paper gives an overview of the previous research work on uncertainty knowledge representation and reasoning, incorporates Ontology into the fuzzy Multi Entity Bayesian Networks theory, and introduces fuzzy PR-OWL, an Ontology language based on OWL2. Fuzzy PR-OWL describes fuzzy semantics and uncertain relations and gives grammatical definition and semantic interpretation. Secondly,… More >

Wenpeng Lu^1,*, Fanqing Meng², Shoujin Wang³, Guoqiang Zhang⁴, Xu Zhang¹, Antai Ouyang⁵, Xiaodong Zhang⁶

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 197-212, 2019, DOI:10.32604/cmc.2019.06068

Abstract Word sense disambiguation (WSD) is a fundamental but significant task in natural language processing, which directly affects the performance of upper applications. However, WSD is very challenging due to the problem of knowledge bottleneck, i.e., it is hard to acquire abundant disambiguation knowledge, especially in Chinese. To solve this problem, this paper proposes a graph-based Chinese WSD method with multi-knowledge integration. Particularly, a graph model combining various Chinese and English knowledge resources by word sense mapping is designed. Firstly, the content words in a Chinese ambiguous sentence are extracted and mapped to English words with BabelNet. Then, English word similarity… More >

Bohan Niu^1,*, Yongfeng Huang²

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 1-14, 2019, DOI:10.32604/cmc.2019.06032

Abstract The goal of research on the topics such as sentiment analysis and cognition is to analyze the opinions, emotions, evaluations and attitudes that people hold about the entities and their attributes from the text. The word level affective cognition becomes an important topic in sentiment analysis. Extracting the (attribute, opinion word) binary relationship by word segmentation and dependency parsing, and labeling those by existing emotional dictionary combined with webpage information and manual annotation, this paper constitutes a binary relationship knowledge base. By using knowledge embedding method, embedding each element in (attribute, opinion, opinion word) as a word vector into the… More >

Chuanrong Wu^{1, *}, Evgeniya Zapevalova¹, Yingwu Chen², Feng Li³

CMC-Computers, Materials & Continua, Vol.54, No.3, pp. 269-285, 2018, DOI:10.3970/cmc.2018.054.269

Abstract In the big data environment, enterprises must constantly assimilate big data knowledge and private knowledge by multiple knowledge transfers to maintain their competitive advantage. The optimal time of knowledge transfer is one of the most important aspects to improve knowledge transfer efficiency. Based on the analysis of the complex characteristics of knowledge transfer in the big data environment, multiple knowledge transfers can be divided into two categories. One is the simultaneous transfer of various types of knowledge, and the other one is multiple knowledge transfers at different time points. Taking into consideration the influential factors, such as the knowledge type,… More >

Surya R. Kalidindi^1,2,3, Stephen R. Niezgoda¹, Giacomo L,i^1,1, Tony Fast¹

CMC-Computers, Materials & Continua, Vol.17, No.2, pp. 103-126, 2010, DOI:10.3970/cmc.2010.017.103

Abstract This paper presents a novel mathematical framework for building a comprehensive materials knowledge system (MKS) to extract, store and recall hierarchical structure-property-processing linkages for a broad range of material systems. This new framework relies heavily on the use of computationally efficient FFT (Fast Fourier Transforms)-based algorithms for data-mining local structure-response-structure evolution linkages from large numerical datasets produced by established modelling strategies for microscale phenomena. Another salient feature of this new framework is that it facilitates flow of high fidelity information in both directions between the constituent length scales, and thereby offers a new strategy for concurrent multi-scale modelling of materials… More >