HAZOP Ontology Semantic Similarity Algorithm Based on ACO-GRNN

Hazard and operability (HAZOP) is an important safety analysis method, which is widely used in the safety evaluation of petrochemical industry. The HAZOP analysis report contains a large amount of expert knowledge and experience. In order to realize the effective expression and reuse of knowledge, the knowledge ontology is constructed to store the risk propagation path and realize the standardization of knowledge expression. On this basis, a comprehensive algorithm of ontology semantic similarity based on the ant clony optimization generalized neural network (ACO-GRNN) model is proposed to improve the accuracy of semantic comparison. This method combines the concept name, semantic distance, and improved attribute coincidence calculation method, and ACO-GRNN is used to train the weights of each part, avoiding the influence of manual weighting. The results show that the Pearson coefficient of this method reaches 0.9819, which is 45.83% higher than the traditional method. It could solve the problems of semantic comparison and matching, and lays a good foundation for subsequent knowledge retrieval and reuse.

Blurred Engineering Identities in Megascience

The scientific community engaged in research practices of high-energy physics in megascience laboratories is constituted by various subcommunities. These subcommittees are involved in engineering activities and preoccupied by phenomenal analyses. In recent decades, interdisciplinary accelerator and detector researchers, whose work is rooted in engineering, have replaced the experimentalists and instrumentalists of the 1970s; however, the role of pure theorists has remained essentially unchanged. In this article, the author clarifies the roles and specializations of these groups and explicate community members' blurred professional identities; the emphasis lies on engineering specialists and experimentalists. This research also attempts to clarify the reasons for the substantial imbalance of prestige among groups and how it is associated with access to highly valued epistemic practices such as articulating statements regarding natural phenomena. This paper applies an ethical theory framework to reveal how the lack of access to phenomenal knowledge expression—despite mediated contribution to knowledge production—creates participatory epistemic injustice. Finally, the author suggests ways to address this problem.

Analisis Pola Penggunaan Tagar Viral sebagai Media Pendidikan Karakter Netizen (Studi Kritis pada Fenomena Global mengenai Tagar #dajjal di Twitter)

ABSTRACTHashtag plays a role as the key to global social change while education plays a role as a tool to optimize it. A topic discussed in this study is that a research on viral hashtag has not been found as a medium for character education for netizens. The research problems formulated in this study are viral Twitter hashtags and the concept of viral hashtags as a medium for character education for netizens. This study aims to determine the patterns of viral hashtags on Twitter and to find out the concept of viral hashtags as a medium for character building for netizens. This study has the benefit of complementing the concept of character education in the technology era and helping people become netizens with character. The research used a qualitative approach with discourse analysis. The objects of this study are viral hashtags, while the subjects are netizens. The samples of this study are the hashtag #dajjal found on Twitter. The instruments used are observation and document notes. The data dealing with character education were analyzed and triangulated. The results of this study show that: 1) viral hashtags are used to share knowledge, pray, opinions, discussions, social movements, peace mediators, entertainment, and personal interests; 2) the concept of character education for netizens, namely viral hashtags as a medium for conveying knowledge, expression, declaration, clarification, action, and control values.Keywords: hashtags, media, character education, netizens, Twitter ABSTRAKTagar sebagai kunci perubahan sosial global dan pendidikan sebagai alat untuk mengoptimalnya. Masalah penelitian pada kajian ini yaitu belum ditemukan penelitian tagar viral sebagai media pendidikan karakter bagi netizen. Rumusan masalahnya adalah pola penggunaan tagar Twitter yang viral dan konsep tagar viral sebagai media pendidikan karakter bagi netizen. Tujuan penelitian ini yaitu untuk mengetahui pola penggunaan tagar yang viral di media sosial Twitter dan juga untuk mengetahui konsep tagar viral sebagai media pembinaan karakter netizen. Penelitian ini memiliki manfaat untuk melengkapi konsep pendidikan karakter era teknologi dan membantu masyarakat menjadi netizen yang berkarakter. Penelitian menggunakan: pendekatan kualitatif; analisis wacana; objek penelitian berupa tagar viral; subjeknya adalah netizen; sampel berupa tagar #dajjal; observasi; catatan dokumen; analisis tinjauan pendidikan karakter; dan triangulasi teori. Hasil penelitian ini yaitu: 1) tagar viral digunakan untuk berbagi ilmu, berdoa, beropini, diskusi, gerakan sosial, mediator perdamaian, hiburan, dan kepentingan pribadi; 2) konsep pendidikan karakter bagi netizen yaitu tagar viral sebagai media penyampai pengetahuan nilai (values knowledge), ekspresi keyakinan nilai (values express), deklasari pilihan nilai (values declare), klarifikasi nilai (values clarification), aksi nilai (values action), dan pengontrol nilai (values control).Kata Kunci: Tagar, media, pendidikan karakter, netizen, Twitter

Influence of Blade Profile Change on Gas Path Performance and Their Ontology-Based Fault Knowledge Expression

During the operation of the gas turbine engine, the blades are prone to gas path faults such as fouling, corrosion, and erosion, or even fracture. Current research usually ignores the impact of different changes in blade profile on the gas path performance. Due to the lack of a unified description between the faulty blade and the gas path performance, it is difficult to implement the knowledge expression for the blade faults. This paper proposed the following framework to fill this gap. (1) Establish a corresponding relationship between blade profile change and gas path performance degradation based on numerical simulation. (2) Combined with ontology, case-based reasoning in knowledge expression of blade faults is investigated. The knowledge base for blade faults is constructed with ontology using the simulation results. The integration, traceability, and reuse of the simulation results are realized. (3) A case is used to verify the effectiveness of the ontology knowledge base for the faulty blade and realize the knowledge expression of blade faults. This will support the real-time diagnosis of blade faults and health management for the gas turbine engine.

A Review of Inference Methods Based on Knowledge Graph

With the development of Internet and big data technology, the scale of data is growing exponentially, and these data contain a lot of valuable information. As the most intuitive way of knowledge expression, knowledge map can effectively organize and express data. As an important means of knowledge map completion, knowledge inference aims to deduce new knowledge or identify wrong knowledge based on existing knowledge in the knowledge map. Different from traditional knowledge inference methods, knowledge inference methods based on knowledge graphs are also diversified according to their simple, intuitive, flexible and rich knowledge expression forms. According to the types of reasoning methods, knowledge reasoning methods based on knowledge graph can be divided into single-step reasoning and multi-step reasoning. According to the different methods adopted for each type, each type also includes reasoning based on distributed representation; reasoning based on neural network and mixed reasoning. These methods are summarized in detail, and the future research direction and prospect of knowledge inference based on knowledge map are discussed and prospected.

Voice in marketing interactions

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Voice is an intrinsic feature of marketing interactions that varies among individual agents, across encounters, and throughout interactions. Despite the prevalence of voice in marketing interactions and its importance as a communicative tool, it remains one of the least studied elements resulting in limited understanding of how voice contributes to interaction outcomes. This dissertation examines voice through systematic conceptualization of its verbal (linguistic) and vocal (acoustic) features and sheds light on how they shape business outcomes. In two essays, this dissertation investigates this pervasive, yet under-studied feature of marketing interactions and provides empirical evidence of the importance of its consideration in in marketing interactions. Essay 1: Organizational Agent Voice in Business-to-Business Customer Interactions. My first essay takes a crucial initial step in enhancing understanding of agent voice by providing a framework for studying voice through systematic conceptualization of its verbal (linguistic) and vocal (acoustic) cues and how they communicate meaning in B2B agent-customer interactions. Specifically, this paper addresses two research questions: (1) what dynamic customer voice measure can serve as a key diagnostic metric for understanding the impact of agent voice on interaction outcomes? And, (2) how do agent verbal and vocal cues interplay to impact key dynamic customer metrics during interactions? An exploratory empirical investigation that isolates verbal and vocal cues in a naturalistic B2B interaction examines these questions and finds that agents' verbal and vocal cues jointly influence customer receptivity, which in turn, acts as a strong mediator of agent voice on interaction outcomes. Implications for research and practice are discussed. Essay 2: The Role of Voice in Salesperson Lead Calling Effectiveness. In essay 2, I examine voice in a context of growing importance to practitioners: inside sales. Inside sales, or remote selling activities within a firm, are growing at an unprecedented pace due to their ability to substantially reduce selling costs while enhancing efficacy of traditional outside sales forces. Effective lead conversion is a, if not the, critical challenge facing the inside sales force. In this essay, I conceptualize verbal (ask specificity, communicating value, relating knowledge expression, customer-tailored inquiry) and vocal (confidence, affability) tactics relevant in inside sales lead calling and analyze their impact on lead conversion through acoustic and textual analysis of naturalistic inside sales phone conversations. This research draws on persuasion knowledge literature to conceptualize which verbal and vocal tactics are most effective in motivating lead conversion. Given poor conversion rate (20 [percent]) of lead calls, understanding ways to enhance sales efficacy would be welcomed by practitioners.

Quantifying the Effects of Programming Education on Students’ Knowledge Representation and Perception in Computational Thinking

Students should be able to express their knowledge in a manner that computers can understand. We aim to improve students' computational thinking (CT) and to express knowledge representation through programming education. We have developed a tool to measure students' CT. Tests were conducted using pattern analysis, conditional comparison, abstraction, automation, and algorithm design. Through Python programming education, we taught students’ the knowledge expression needed to solve various problems, and then conducted a post-test. We analysed the correlations between the academic performance of students and their computer-related knowledge and expression skills. Even though students were unfamiliar with computer programming terminology and concepts, programming and computing education was administered based on problems that could be solved using elementary mathematics. There was no significant difference between the results of the initial students’ assessments and the results after the lecture. However, the correlation between the students’ assessments and actual academic performance was high. These studies provide a pilot model of how tools can be used to express and measure students’ knowledge of CT. Based on these results, students can learn a variety of techniques to express their knowledge and continue to improve upon such.

Case-based Reasoning of Damaged Ancient Buildings based on Ontology

At present, China has a large number of ancient buildings, and correspondingly, it also faces many problems. Staff of different professions have inconsistent perceptions of ancient buildings, resulting in inability to interact with information. In addition, the ancient architecture case did not carry out efficient reuse of knowledge. Therefore, this article applies ontology to the field of ancient architecture, and proposes the knowledge expression of ancient architecture based on ontology. And SWRL is used to describe the ancient building rules. Secondly, through the application of case-reasoning technology, the reuse of case knowledge of ancient architecture is realized. Ontology-based case representation can provide a unified definition of ancient building knowledge for different participants and lay the foundation for information interaction. Case-based reasoning provides an implementation method for knowledge reuse of ancient building damage cases.