Combining Deep Learning with Knowledge Graph for Design Knowledge Acquisition in Conceptual Product Design

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph.Specifically,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design.Moreover,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module.Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model.The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.

Cognitive Views on the Representation and Acquisition of L2 Grammatical Knowledge

The role of implicit and explicit learning,depth of processing and elaboration as well as involvement load hypothesis in second language grammatical acquisition were examined in this paper.We conclude that psychologists have associated better learning with depth of processing,or degree of elaboration.The Involvement Load Hypothesis can be conceived as a first attempt to stimulate researchers as well as practitioners to operationalize traditional general labels into task-specific components.

Acquisition and Active Navigation of Knowledge Particles throughout Product Variation Design Process

The variation design of complex products has such features as multivariate association, weak theory coupling and implicit knowledge iteration. However, present CAD soft wares are still restricted to making decisions only according to current design status in dynamic navigation which leads to the huge drain of the knowledge hidden in design process. In this paper, a method of acquisition and active navigation of knowledge particles throughout product variation design process is put forward. The multi-objective decision information model of the variation design is established via the definition of condition attribute set and decision attribute set in finite universe. The addition and retrieval of the variation semantics is achieved through bidirectional association between the transplantable structures and variation design semantics. The mapping relationships between the topology lapping geometry elements set and constraint relations set family is built by means of geometry feature analysis. The acquisition of knowledge particles is implemented by attribute reduction based on rough set theory to make multi-objective decision of variation design. The topology lapping status of transplantable substructures is known from DOF reduction. The active navigation of knowledge particles is realized through embedded event-condition-action（ECA） rules. The independent prototype system taking Alan, Charles, Ian＇s system（ACIS） as kernel has been developed to verify the proposed method by applying variation design of complex mechanical products. The test results demonstrate that the navigation decision basis can be successfully extended from static isolated design status to dynamic continuous design process so that it more flexibly adapts to the different designers and various variation design steps. It is of profound significance for enhancing system intelligence as well as improving design quality and efficiency.

Semantic Knowledge Acquisition from Blogs with Tag-Topic Model

This paper focuses on semantic knowl- edge acquisition from blogs with the proposed tag- topic model. The model extends the Latent Dirichlet Allocation （LDA） model by adding a tag layer be- tween the document and the topic. Each document is represented by a mixture of tags; each tag is as- sociated with a multinomial distribution over topics and each topic is associated with a multinomial dis- trNution over words. After parameter estimation, the tags are used to descrNe the underlying topics. Thus the latent semantic knowledge within the top- ics could be represented explicitly. The tags are treated as concepts, and the top-N words from the top topics are selected as related words of the con- cepts. Then PMI-IR is employed to compute the re- latedness between each tag-word pair and noisy words with low correlation removed to improve the quality of the semantic knowledge. Experiment re- sults show that the proposed method can effectively capture semantic knowledge, especially the polyse- me and synonym.

Intelligent Multilevel Knowledge Acquisition System for Product Design and Its Implementation

The characteristics of design process, design object and domain knowledge of complex product are analyzed. A kind of knowledge representation schema based on integrated generalized rule is stated. An AND-OR tree based model of concept for domain knowledge is set up. The strategy of multilevel domain knowledge acquisition based on the model is presented. The intelligent multilevel knowledge acquisition system (IMKAS) for product design is developed, and it is applied in the intelligent decision support system of concept design of complex product.

Effects of Written Corrective Feedback on College EFL Students’Writing Accuracy and Linguistic Knowledge Acquisition

Set at the interface between second language acquisition and second language writing,this study examines how different types of written corrective feedback(WCF)influence the writing accuracy of Chinese college students learning English as a Foreign Language(EFL)and whether WCF facilitates the students’grasp of the focused linguistic knowledge.The participants(n=60)were divided into direct correction group(n=20),indirect error-coding group(n=20)and metalinguistic explanation group(n=20).The three groups wrote four essays in two months and received WCF for the first three essays on the five targeted error types,namely tense errors,confusion of different forms of a word,word(articles,prepositions,etc.)missing,errors in subjectverb agreement and inappropriate verb-noun collocations.The results show that all three types of WCF improved students’writing accuracy but none of them had any statistical advantage,and the metalinguistic WCF was more effective than the other two forms in facilitating the acquisition of the targeted linguistic features.These results shed some light on teaching and consolidation of language points through writing in EFL contexts.

Modeling the factors that influence knowledge transfer in mergers and acquisitions

This paper constructs a model on the factors that influence knowledge transfer in mergers and acquisitions(M&A) and validates it via questionnaire surveys. Using 125valid collected questionnaires, multiple linear regression analysis and hierarchical regression analysis showed that five out of the ten factors had a positive effect on knowledge transfer effect. The ranking of factor importance, from high to low, was knowledge explicitness, relationship quality, learning intent, advanced transfer activities, and learning capability, which is fairly consistent with positive factors observed in other interorganizational knowledge transfer researches. Our results also showed that one of the control variables(size of acquired firm) had neither a direct or indirect effect on knowledge transfer in M&A. Additionally, our research found that knowledge distance and degree of M&A integration had a positive influence on knowledge transfer effect at the early stage after M&A, but had a negative influence at the late stage. Based on this research, several suggestions for knowledge transfer in M&A are proposed.

Research on Genetic Algorithm Based Knowledge Auto Acquisition for Fault Diagnosis

In this paper, a genetic algorithm based knowledge auto acquisition approach for fault diagnosis is proposed. Under the circumstances that diagnostic examples are available but no empirical knowledge can be obtained, knowledge for fault diagnosis can be

A New Algorithm for the Acquisition of Knowledge from Scientific Literature in Specific Fields Based on Natural Language Comprehension

The acquisition of knowledge and the representation of that acquisition have always been viewed as the bottleneck in the construction of knowledge-based systems. The traditional methods of acquiring knowledge are based on knowledge engineering and communication with field experts. However, these methods cannot produce systematic knowledge effectively, automatically construct knowledge-based systems, or benefit knowledge reasoning. It has been noted that, in specific professional fields, experts often use fixed patterns to describe their expertise in the scientific articles that they publish. Abstracts and conclusions, for example, are key components of the scientific article, containing abundant field knowledge. This paper suggests a method of acquiring production rules from the abstracts and conclusions of scientific articles in specific fields based on natural language comprehension. First, the causal statements in article abstracts and conclusions are extracted using existing techniques, such as text mining. Next, antecedence and consequence fragments are extracted using causal template matching algorithms. As the final step, part-of-speech-tagging production rules are automatically generated according to a syntax parsing tree from the speech pair sequence. Experiments show that this system not only improves the efficiency of knowledge acquisition but also simultaneously generates systematic knowledge and guarantees the accuracy of acquired knowledge.

Application of Multi-Frequency SAR Images for Knowledge Acquisition

The aim of this research is to apply TerraSAR X-band, Envisat C-band and Palsar L-band synthetic aperture radar (SAR) images for a knowledge acquisition process. For the study, backscattering properties of different natural and man-made objects of urban environment are analyzed on the basis of statistics of signatures of the selected classes. After the knowledge acquisition, for the acquired knowledge representation, a rule-based approach is proposed. Overall, the research demonstrated that the multi-frequency radar images can be effectively used for the knowledge acquisition as well as for the analysis of different land cover types.

Knowledge Acquisition in Small and Medium Businesses

This article applies to the process of organizational knowledge acquisition by managers and specialists with the possession of manager license. The theoretical part explains： concepts of knowledge, knowledge management, knowledge sources, and the step of creating and acquiring knowledge. The research part focuses on the presentation and analysis of obtained results of research performed by the author.

Knowledge acquisition method for case-knowledge-based product family design

Knowledge acquisition has always been the bottleneck of artificial intelligence. It is the critical point in product family design. Here a knowledge acquisition method was introduced based on scenario model and repository grid and attribute ordering table technology. This method acquired knowledge through providing product design cases to expert, and recording the means and knowledge used by the expert to describe and resolve problems. It used object to express design entity, used scenario to describe the design process, used Event-Condition-Action（ECA） nile to drive design process, and with the help of repository grid and attribute ordering table technology to acquire design knowledge. It＇ s a good way to capture explicit and implicit knowledge. And its validity is proved with respective examples.

Basic Elements Knowledge Acquisition Study in the Chinese Character Intelligent Formation System

In the Chinese character intelligent formation system without Chinese character library, it is possible that the same basic element in different Chinese characters is different in position, size and shape. The geometry transformation from basic elements to the components of Chinese characters can be realized by affine transformation, the transformation knowledge acquisition is the premise of Chinese character intelligent formation. A novel algorithm is proposed to ac-quire the affine transformation knowledge of basic elements automatically in this paper. The interested region of Chi-nese character image is determined by the structure of the Chinese character. Scale invariant and location invariant of basic element and Chinese character image are extracted with SIFT features, the matching points of the two images are determined according to the principle of Minimum Euclidean distance of eigenvectors. Using corner points as identifi-cation features, calculating the one-way Hausdorff distance between corner points as the similarity measurement from the affine image to the Chinese character sub-image, affine coefficients are determined by optimal similarity. 70244 Chinese characters in National Standards GB18030-2005 character set are taken as the experimental object, all the characters are performed and the experimental courses and results are presented in this paper.

On Constructing the Cognitive Model of Knowledge Acquisition in Globalization-Oriented Study

This paper which is directed to constructing the cognitive model of knowledge acquisition in view of the increasing need of globalization-oriented study, points out features of globalization-oriented study, and proposes the importance and necessity for constructing the CMKAGS （cognitive model of knowledge acquisition in globalization-oriented study） which includes attention, background knowledge, and chunking memory that involves semantic chunking, information encoding as well as choice of information encoding. The cognitive model of knowledge acquisition in question aims at helping e-learners to memorize their learned knowledge and improve their studies effectively and efficiently, whether they study in enhanced conditions or in natural conditions

Product Evaluation Knowledge Acquisition Based on Rough Sets

The method and steps of acquiring evaluation rules based on the knowledge reduction theory of rough sets is discussed, and the distilling process and approach for the evaluation rules of mechanical product structure design is described by using hydraulic torque converter as an example. Practice shows that this approach to a certain extent simplifies the knowledge base structure and reasoning process in comparison with the case-based reasoning method in the aspect of setting up evaluation rule base and carrying out reasoning to realize the mechanical product evaluation.

Knowledge Acquisition from Forestry Machinery Patent Based on the Algorithm for Closed Weighted Pattern Mining

The application of big data mining can create over a trillion dollars value. Patents contain a great deal of new technologies and new methods which have unique value in the product innovation. In order to improve the effectiveness of big data mining and aid the innovation of products of forestry machinery, the algorithm for closed weighted pattern mining is applied to acquire the function knowledge in the patents of forestry machinery. Compared with the other algorithms for mining patterns, the algorithm is more suitable for the characteristics of patent data. It not only takes into account the importance of different items to reduce the search space effectively, but also avoids achieving excessive uninteresting patterns below the premise that assures quality. The extensive performance study shows that the patterns which are mined by the closed weighted pattern algorithm are more representative and the acquired knowledge has more realistic application significance.

An Empirical Study of Depth of Vocabulary Knowledge and Vocabulary Learning Metacognitive Strategies of Non-English Majors

This paper concentrates on the depth of vocabulary knowledge and vocabulary learning metacognitive strategies used by Chinese non-English majors in an independent college.Results show the depth of vocabulary knowledge of the subjects only reaches the passing level.And metacognitive strategies are correlated significantly with the depth of vocabulary knowledge.

基于Knowledge-Analysis的军事知识联通研究

军事专业知识在军事决策系统、军事智能教学系统、军事知识查询系统等高技术产品中具有重要的作用。知识库是机器智能的重要来源,所以有必要建立一个完善、协调、具有良好联通性的大型军事知识库,而大量实践证明计算机真正具有智能不仅需要大型知识库,而且更需要知识间广泛的联通。本文主要讨论军事概念联通。所谓概念联通是指通过关系链或属性或属性值将两个概念联系起来的过程。概念联通的目的之一就是通过概念联通帮助发现不同知识源的知识之间的不一致性,尽可能保证所获取知识的完备性和精确性,建立一个大型的军事专业知识库。

Integration of Decision-Support and Knowledge-Based Techniques in a Problem-Solving Strategy for Selection Problems

The limitations of traditional approaches to selection problems are examined. A problemsolving strategy is presented in which decision-support and knowledge-based techniques play complementary roles. An approach to the representation of knowledge to support the problem-solving strategy is presented which avoids commitment to a specific programming language or implementation environment. The problem of choosing a home is used to illustrate the representation of knowledge in a specific problem domain. Techniques for implementation of the problem-solving strategy are described. Knowledge elicitation techniques and their implementation in a development shell for application of the problem-solving strategy to any selection problem are also described.

Leadership,Knowledge Management,and Human Capital Development

This research highlights the need to develop a framework for leadership,human capital development,and knowledge management by reviewing existing literature in the field of research.The main aim of this research is to propose a model which supports the relationship between leadership(servant leadership,transformational leadership)and human capital development.The study also proposes that knowledge management(knowledge sharing,knowledge acquisition)will moderate the relationship between leadership(servant leadership,transformational leadership)and human capital development.A set of propositions that represent an empirically-driven research agenda,and also describe the relationships between the focal variables are presented to enhance audience’s understanding within a business context.