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检索条件"任意字段=19th International Conference on Software Engineering and Knowledge Engineering"

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Integrating DGBL and Collaborative Learning in Enterprise Resource Planning Courses for Students with engineering Background 26th

Integrating DGBL and Collaborative Learning in Enterprise Re...

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26th international conference on Interactive Collaborative Learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP international conference on engineering Pedagogy

作者： May, Ming-Der Lunghwa Univ Sci & Technol Dept Ind Management Taoyuan Taiwan

ISBN: (纸本)9783031519789;9783031519796

Although the current ERP (Enterprise Resource Planning) course has the latest information system software as in the industry that can be operated in class, and with the refinement of PBL and teaching methods, students can learn from the perspective of system implementation, rather than the traditional system operation level. However, for most students, they are still more inclined to work data input, and cannot connect to process-oriented knowledge, or even processes analysis, causing students to fall into repetitive and monotonous system operations. therefore, this study intends to apply the digital online game competition in the ERP courses of the technical University students. To evaluate the "game-based teaching plan and course design strategy", a statistical comparative analysis is carried out on the impact of the ERP course plan. It is hoped that through such an instructional design integrating PBL and game-based learning, it can encourage students' spontaneous and interesting learning motivation and improve the effect of learning participation.

关键词： Digital game-based-learning Online business game Enterprise resource planning

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Mechanical Fault Prediction Based on Event knowledge Graph 15

Mechanical Fault Prediction Based on Event Knowledge Graph

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15th international conference on knowledge engineering and Ontology Development, KEOD 2023 as part of the 15th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2023

作者： He, Li Zhang, Liang Yan, Wei School of Information Science and Engineering Shandong Normal University Shandong Jinan250358 China Shandong University Shandong Qingdao266237 China

ISBN: (纸本)9789897586712

Currently, the majority of diagnoses in the field of mechanical faults are performed by experts or expert systems, which require domain experts to guide the completion while having subpar and limited portability. Consequently, we analyzed the current situation of rolling bearing fault, event knowledge graph and convolutional neural network, explored the intelligent fault diagnosis and prediction technology of rolling bearing, introduced event knowledge graph and convolutional neural network in rolling bearing fault diagnosis, provided support for fault diagnosis and prediction, enhanced the accuracy of fault diagnosis and prediction, and enabled the predictive of complex mechanical equations. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0).

关键词： Failure analysis

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ZK-CPABE: Blockchain-based CP-ABE Scheme Via Zero-knowledge Proof 7

ZK-CPABE: Blockchain-based CP-ABE Scheme Via Zero-Knowledge ...

引用

7th international conference on Advanced Electronic Materials, Computers, and software engineering, AEMCSE 2024

作者： Zhao, Jinyi Zhu, Jie Yin, Peng Yu, Yimin Xie, Long School of Logistics and Management Engineering Yunnan University of Finance and Economics Kunming China Division of Science & Technology Administration Yunnan University of Finance and Economics Kunming China Lianjia Primary School Wuhua District Kunming China School of Information Yunnan University of Finance and Economics Kunming China

ISBN: (纸本)9781510681866

the integration of blockchain technology with Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has addressed key challenges in distributed systems, such as mutual trust and collusion, while enhancing auditability of key management. However, existing blockchain-based CP-ABE models face a trilemma, unable to achieve decentralization, scalability, and security concurrently. therefore, we propose ZK-CPABE, which merges Zero-knowledge Proofs with blockchain-based CP-ABE, significantly improving verifiability and scalability. this system combines a secure private key distribution and zero-knowledge proofs to construct off-chain computation and scalable transactions for CP-ABE. Our Ethereum-based ZK-CPABE prototype demonstrates its effectiveness and potential for secure, scalable data sharing and access control. © 2024 SPIE.

关键词： Blockchain

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Conceptual modeling of the V gene annotation process in antibodies 11

Conceptual modeling of the V gene annotation process in anti...

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11th international conference in software engineering Research and Innovation (CONISOFT)

作者： Serret, Noemi Ortiz-Hernandez, Javier Miguel-Ruiz, Juan Barnetche, Jesus Martinez Hernandez, Yasmin Tecnol Nacl Mexico CENIDET Dept Ciencias Computac Cuernavaca Morelos Mexico Inst Nacl Salud Publ Ctr Invest Enfermedades Infecciosas Cuernavaca Morelos Mexico

ISBN: (纸本)9798350328837;9798350328844

the genes present in the V(D)J segments are components for the generation of antibodies. the function of antibodies is to detect foreign agents that are harmful to the organism. the location of the V, D and J genes is of great interest for the diagnosis of diseases and genomic disorders. the gene recognition or genome annotation process is of high complexity due to the integration of large volumes and diverse data sources. Genome annotation is the process of assigning information or labels to sections of the genome of a species. Advances have been made in the systematization of some steps of the annotation process, but activities that are performed manually by molecular biology specialists still prevail. Due to the diversity of rules that must be taken into account to determine the location of the V, D and J genes in the annotation process, a great amount of time and computational resources are consumed. In this work we propose the use of design science methodology for knowledge representation by means of conceptual modeling. the model represents the annotation process, the rules to determine its functionality and the parts that compose the V genes.

关键词： component conceptual model annotation process V(D)J segments V gene design science knowledge engineering

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Enhancing Topic Interpretability for Neural Topic Modeling through Topic-Wise Contrastive Learning 40

Enhancing Topic Interpretability for Neural Topic Modeling T...

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40th IEEE international conference on Data engineering, ICDE 2024

作者： Gao, Xin Lin, Yang Li, Ruiqing Wang, Yasha Chu, Xu Ma, Xinyu Yu, Hailong Software Engineering Institution School of Computer Science Peking University Beijing China Key Lab of High Confidence Software Technologies Ministry of Education Beijing China Peking University National Engineering Research Center of Software Engineering Beijing China School of Computer Science Center on Frontiers of Computing Studies Peking University China

ISBN: (纸本)9798350317152

Data mining and knowledge discovery are essential aspects of extracting valuable insights from vast datasets. Neural topic models (NTMs) have emerged as a valuable unsupervised tool in this field. However, the predominant objective in NTMs, which aims to discover topics maximizing data likelihood, often lacks alignment with the central goals of data mining and knowledge discovery which is to reveal interpretable insights from large data repositories. Overemphasizing likelihood maximization without incorporating topic regularization can lead to an overly expansive latent space for topic modeling. In this paper, we present an innovative approach to NTMs that addresses this misalignment by introducing contrastive learning measures to assess topic interpretability. We propose a novel NTM framework, named ContraTopic, that integrates a differentiable regularizer capable of evaluating multiple facets of topic interpretability throughout the training process. Our regularizer adopts a unique topic-wise contrastive methodology, fostering both internal coherence within topics and clear external distinctions among them. Comprehensive experiments conducted on three diverse datasets demonstrate that our approach consistently produces topics with superior interpretability compared to state-of-the-art NTMs. © 2024 IEEE.

关键词： Data mining

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Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion 38

Maat: Performance Metric Anomaly Anticipation for Cloud Serv...

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38th IEEE/ACM international conference on Automated software engineering (ASE)

作者： Lee, Cheryl Yang, Tianyi Chen, Zhuangbin Su, Yuxin Lyu, Michael R. Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Peoples R China Sun Yat Sen Univ Sch Software Engn Zhuhai Peoples R China

ISBN: (纸本)9798350329964

Ensuring the reliability and user satisfaction of cloud services necessitates prompt anomaly detection followed by diagnosis. Existing techniques for anomaly detection focus solely on real-time detection, meaning that anomaly alerts are issued as soon as anomalies occur. However, anomalies can propagate and escalate into failures, making faster-than-real-time anomaly detection highly desirable for expediting downstream analysis and intervention. this paper proposes Maat, the first work to address anomaly anticipation of performance metrics in cloud services. Maat adopts a novel two-stage paradigm for anomaly anticipation, consisting of metric forecasting and anomaly detection on forecasts. the metric forecasting stage employs a conditional denoising diffusion model to enable multi-step forecasting in an auto-regressive manner. the detection stage extracts anomaly-indicating features based on domain knowledge and applies isolation forest with incremental learning to detect upcoming anomalies. thus, our method can uncover anomalies that better conform to human expertise. Evaluation on three publicly available datasets demonstrates that Maat can anticipate anomalies faster than real-time comparatively or more effectively compared with state-of-the-art real-time anomaly detectors. We also present cases highlighting Maat's success in forecasting abnormal metrics and discovering anomalies.

关键词： Could Computing Anomaly Anticipation Denosing Diffusion Model Performance Metric

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Inclusive Gamification: An Exploratory Study in software Development Enterprises 35

Inclusive Gamification: An Exploratory Study in Software Dev...

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35th international conference on software engineering and knowledge engineering, SEKE 2023

作者： Elsalmy, Fayrouz Sherief, Nada Hany Abdelmoez, Walid Information Systems College of Computing and Information Technology Arab Academy for Science and Technology Alexandria Egypt Software engineering College of Computing and Information Technology Arab Academy for Science and Technology Alexandria Egypt

Gamification is the incorporation of game elements into non-game settings. software designers increase user motivation by introducing adequately engaging elements, such as leaderboards and badges, into an existing system. In recent years, few studies have examined the risks associated with gamification inside the business systems sector, especially within software development organizations. Yet, this issue must be addressed more systematically to build gamified solutions that take individual gamification risks into account. this research introduces "Inclusive Gamification" as contextually aware gamification that highlights individual risks. the purpose of this paper is twofold: 1) to identify the gamification risk factors that could cause the emergence of risks in software development organizations;and 2) to develop a list of risks with consideration of various contextual factors, namely tasks, personality type, adopted game element, and organizational cultural aspects. 15 employees from three software development companies participated in an exploratory study in which their perspectives on the negative effects of gamification were collected. As a result, we were able to identify several risk factors and associated risks. Our findings assist software engineers throughout the design process in identifying potential threats. thus, create gamified solutions that better situate employees at their workplaces. © 2023 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Personnel

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Improving temporal question answering using temporal knowledge graph embedding 4

Improving temporal question answering using temporal knowled...

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4th international conference on Computer engineering and Application, ICCEA 2023

作者： Chen, Jiabao Fan, Yongquan School of Computer & Software Engineering Xihua University Chengdu610039 China

ISBN: (纸本)9798350347548

knowledge graph question answering is an important research direction for question answering tasks. In recent years, there has been an increasing amount of research on knowledge graph question answering, but temporal knowledge graph question answering is still a relatively unexplored area. In question answering tasks, many natural language questions have explicit or implicit temporal constraints, and most existing research methods lack the temporal awareness to deal with complex temporal questions. To address these challenges, this paper proposes a question answering model based on temporal knowledge graph embedding (TKGETQA). the model uses TKG embeddings to root a question in the entities, relations and time horizons it references, and perceives temporal information from the question to improve the accuracy of answer prediction. Experiments on the dataset CronQuestions in this paper show that the TKGETQA model exhibits better results compared to existing temporal knowledge graph question answering approaches. © 2023 IEEE.

关键词： knowledge graph

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Aluminium-Sulfur Batteries: A low-cost Alternative to Lithium-ion Batteries 19

Aluminium-Sulfur Batteries: A low-cost Alternative to Lithiu...

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19th international Scientific Technical conference Alternating Current Electric Drives, ACED 2023

作者： Upadhyay, Akshay Das, Gurumukh Chauhan, Rajeev Kumar Department of Mechanical Engineering Agra India Department of Electrical Engineering Agra India

ISBN: (纸本)9798350310887

Long-term energy storage technologies are essential as energy demand grows globally. Due to the limited availability of Lithium, it is now necessary to look for alternatives to Lithium-ion (Li-ion) batteries. the present article describes Aluminium-Sulfur (Al-S) batteries, a powerful contender beyond the Li-ion domain. Both Aluminum and Sulfur are cost-effective and highly abundant elements on Earth. Al-based batteries may have a higher energy density than Li-ion batteries, which are monovalent, due to the triplet of Aluminium. With the increasing demand for electric vehicles (EVs), these batteries can be used at charging stations with the ability to charge faster. © 2023 IEEE.

关键词： Aluminum

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SemParser: A Semantic Parser for Log Analytics 23

SemParser: A Semantic Parser for Log Analytics

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45th IEEE/ACM international conference on software engineering (ICSE)

作者： Huo, Yintong Su, Yuxin Lee, Cheryl Lyu, Michael R. Chinese Univ Hong Kong Comp Sci & Engn Dept Hong Kong Peoples R China Sun Yat Sen Univ Sch Software Engn Zhuhai Peoples R China

ISBN: (纸本)9781665457019

Logs, being run-time information automatically generated by software, record system events and activities with their timestamps. Before obtaining more insights into the run-time status of the software, a fundamental step of log analysis, called log parsing, is employed to extract structured templates and parameters from the semi-structured raw log messages. However, current log parsers are all syntax-based and regard each message as a character string, ignoring the semantic information included in parameters and templates. thus, we propose the first semantic-based parser SemParser to unlock the critical bottleneck of mining semantics from log messages. It contains two steps, an end-to-end semantics miner and a joint parser. Specifically, the first step aims to identify explicit semantics inside a single log, and the second step is responsible for jointly inferring implicit semantics and computing structural outputs according to the contextual knowledge base of the logs. To analyze the effectiveness of our semantic parser, we first demonstrate that it can derive rich semantics from log messages collected from six widely-applied systems with an average F1 score of 0.985. then, we conduct two representative downstream tasks, showing that current downstream models improve their performance with appropriately extracted semantics by 1.2%-11.7% and 8.65% on two anomaly detection datasets and a failure identification dataset, respectively. We believe these findings provide insights into semantically understanding log messages for the log analysis community.

关键词： log analytics log parsing semantic parser

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