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检索条件"任意字段=Knowledge-Based Software Engineering Conference"

共 17482 条记录，以下是911-920 订阅

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Residential Electricity Power Forecasting using GRU-based CNN and SAE Ensembler

Residential Electricity Power Forecasting using GRU-based CN...

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2023 IEEE International conference on Emerging Trends in engineering, Sciences and Technology, ICES and T 2023

作者： Raza, Ali Ali, Usman Ali, Zain Saeed, Muhammad Hamza Khan, Raja Jalees Ul Hussen Ayub, Nasir COMSATS University Islamabad Department of Computer Science WahCantt Campus Pakistan Riphah International University Computing Department Faisalabad Pakistan HITEC University Department of Electrical Engineering Taxila Pakistan National Textile University Department of Computer Science Faisalabad Pakistan Superior University Gold Campus Department of Software Engineering Lahore Pakistan Capital University of Science and Technology Department of Software Engineering Islamabad Pakistan

ISBN: (纸本)9781665455602

Smart grids play an important role to resolves issues related to electricity. Electrical load forecasting can be performed through smart grids to acquire knowledge about the electrical load that will be needed in the future. A combination of Stacked Autoencoding (SAE) and Gated Recurrent Unit (GRU) and a combination of Convolutional Neural Network (CNN), Grey Wolf Optimization (GWO), and GRU are proposed in this paper. Firstly, the historical load data is preprocessed and then preprocessed data is given to the feature selection and extraction methods to measure the importance of each feature. Features that have highest values are selected and input to the proposed classifiers. According to the results the proposed CNN-GRU-GWO gave the highest accuracy rate of 96.31%. This application of this article will help the utility purchase the exact amount of electricity from the grid, which will lead to grid stability. © 2023 IEEE.

关键词： Smart power grids

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Chinese Relation Extraction with Bi-directional Context-based Lattice LSTM 16th

Chinese Relation Extraction with Bi-directional Context-Base...

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16th International conference on knowledge Science, engineering and Management (KSEM)

作者： Ding, Chengyi Wu, Lianwei Liu, Pusheng Wang, Linyong Northwestern Polytech Univ Sch Software Xian Peoples R China Northwestern Polytech Univ Sch Comp Sci Xian Peoples R China Nanjing Univ Posts & Telecommun Sch Comp Sci Nanjing Peoples R China

ISBN: (纸本)9783031402883;9783031402890

Chinese entity relation extraction (Chinese RE) is a crucial task for various NLP applications. It aims to automatically extract relationships between entities in Chinese texts, thereby enhancing the accuracy of natural language understanding. Although existing hybrid methods can overcome some of the shortcomings of character-based and word-based methods, they still suffer from polysemy ambiguity, which results in inaccuracy when representing the relationships between entities in text. To address the issue, we propose a Bi-directional Contextbased Lattice (BC-Lattice) model for Chinese RE task. In detail, our BC-Lattice consists of: (1) A context-based polysemy weighting (CPW) module allocates weights to multiple senses of polysemous words from external knowledge base by modeling context-level information, thus obtaining more accurate representations of polysemous words;(2) A cross-attention semantic interaction-enhanced (CSI) classifier promotes exchange of semantic information between hidden states from forward and backward perspectives for more comprehensive representations of relation types. In experiments conducted on two public datasets from distinct domains, our method yields improved F1 score by up to 3.17%.

关键词： Information extraction Relation extraction NLP Polysemy disambiguation Lattice architecture External knowledge

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AI-Driven Appbox to Facilitate Self-Assessment in an Intelligent Educational Environment 21

AI-Driven Appbox to Facilitate Self-Assessment in an Intelli...

引用

21st International conference on Information Technology based Higher Education and Training, ITHET 2024

作者： Ivanova, Malinka Grosseck, Gabriela Holotescu, Carmen Technical University of Sofia Faculty of Applied Mathematics and Informatics Department of Informatics Sofia Bulgaria West University of Timisoara Faculty of Sociology and Psychology Department of Psychology Timisoara Romania 'Ioan Slavici' University of Timisoara Faculty of Engineering Department of Information Technology Timisoara Romania

ISBN: (纸本)9798331516635

Intelligent learning environments integrate various functions for processing and analyzing learning data by leveraging learning analytics theory. based on this data, numerous machine learning (ML) and artificial intelligence (AI) models are created to predict learning behavior and learning performance with main purpose to improve learning, assessment and teaching. The important role of self-assessment conducted by students in support of their learning progress and final results continues to be explored and discussed. Despite the availability of various educational software products, there is a need to develop intelligent applications to enhance students' self-assessment. The purpose of the paper is to present a conceptual framework and its subsequent implementation by developing a set with web applications based on ML and AI techniques. The applications are related to self-assessment of affective state, predicting and planning learning tasks, self-assessment of graphic objects, knowledge gaining from conversational assistant and self-assessment of learning performance. © 2024 IEEE.

关键词： Adversarial machine learning

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What to Teach First, Hardware or software? Improving Success in Introductory Programming Courses

What to Teach First, Hardware or Software? Improving Success...

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2023 ASEE Annual conference and Exposition - The Harbor of engineering: Education for 130 Years, ASEE 2023

作者： Whalen, Richard Hertz, Joshua L. Northeastern University United States

This complete evidence-based practice paper presents an analysis and lessons learned in introductory engineering courses with content that includes problem-solving, algorithmic thinking, the use of microcontrollers, and C++ at a medium-sized private urban university. These courses specifically incorporate the integration of hands-on, project-based design projects with computer programming. The goal of the project work is to provide an authentic experience and give students the opportunity to develop process-driven problem-solving skills. A large focus of these classes is developing algorithmic thinking skills, and an introduction to computer programming has been used to facilitate meeting this objective. In addition, with the ubiquitous use of microcontrollers and platforms such as Arduino, faculty now can integrate hands-on experiences with hardware to motivate student learning. This paper presents the results of qualitative and quantitative analysis of two ways to introduce programming concepts and the use of microelectronics in a first-year engineering course. In one approach, students are first taught algorithmic thinking and programming in C++ in a traditional sense, without an introduction to hardware applications. Once they have gained facility in the programming language, they then apply this knowledge to hardware applications. In an alternative approach being piloted during this study, students are introduced to programming and algorithmic thinking via the hardware applications;the material is introduced concurrently instead of sequentially. Findings from pre and post-surveys indicate that students taught using both approaches had similar improvements in self-efficacy to code and build projects with basic circuitry. In addition, most students appreciated the approach used in their class;if taught with a hardware-first approach, they thought a hardware-first approach provides greater learning, and if taught with a software-first approach, they thought a hybr

关键词： Students

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Construction and application of BIM Structural Design course project library based on GSRevit software 3

Construction and application of BIM Structural Design course...

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3rd International conference on Education, knowledge and Information Management, ICEKIM 2022

作者： Chen, Li Song, Yafen Zhang, Yue Pei, Guihong Hubei Business College School of Urban Construction Wuhan China

ISBN: (纸本)9781665416665

With the development of building informatization and industrialization technology, the prefabricated concrete structures based on information technology has become a hot spot in the construction industry. 'BIM Structural Design' combines BIM Technology and Prefabricated building technology with the course content, and uses GSRevit software to carry out classroom teaching in order to cultivate students' structural design ability. The project teaching method is adopted in the course teaching method, and the project library composed of three different practical projects is reformed and created. In combination with students' learning ability and professional knowledge level, different engineering projects are selected for teaching for students at different levels, which can stimulate students' learning interest and initiative, effectively improve the teaching quality of the course, and enhance students' structural design ability and engineering practice ability. © 2022 IEEE.

关键词： Students

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The Needs Analysis of a Learning Framework to Enhance Problem-Solving Skills in IoT Course for Non-Engineer Learners 9

The Needs Analysis of a Learning Framework to Enhance Proble...

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9th International STEM Education conference (ISTEM-Ed)

作者： Reetanon, Khomsan Tungpantong, Chanin Songsriwittaya, Alisa King Mongkuts Univ Technol Thonburi Fac Ind Educ & Technol Bangkok Thailand

ISBN: (纸本)9798350365986;9798350365979

This research aims to study the needs and learning preferences of non-engineer learners (learners who do not study engineering majors) to increase problem-solving skills in Internet of Things (IoT) studies and provide a basis for designing new learning frameworks. This research used in-depth interviews with 5 non-engineering learners to gather insights into their needs, preferences, and challenges. The interviews were semi-structured and consisted of questions about background information. and open-ended questions about opinions. Thematic analysis was then used to identify repeating patterns from all interview transcripts. The results of the interviews revealed that non-engineering learners have an interest in IoT technology but encounter problems and need to develop problem-solving skills for IoT development, including a lack of knowledge and experience related to IoT, lack of motivation to learn about IoT, finding an IoT solution to solve a real-world problem. Dealing with these problems may be achieved by designing a learning framework that includes active learning techniques with problem-based learning (PBL), gamification, and hands-on learning. to gain experience with IoT hardware and software. However, this research is still in the early stages. More research may validate these findings whether this is related to a larger sample size, various student profiles, or long-term studies to evaluate long-term effects further.

关键词： Problem-Solving Skills IoT Non-engineering Learners

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software Requirement Ambiguity Avoidance Framework (SRAAF) for Selecting Suitable Requirement Elicitation Techniques for software Projects

Software Requirement Ambiguity Avoidance Framework (SRAAF) f...

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2022 IEEE International conference on Current Development in engineering and Technology, CCET 2022

作者： Gupta, Ashok Kumar Siddiqui, Shams Tabrez Qidwai, Khalid Ali Haider, Agha Salman Khan, Haneef Ahmad, Md Oqail Universiti Malaysia Terengganu Faculty of Science and Technology Kuala Terengganu Malaysia Jazan University Department of Computer Science Jazan Saudi Arabia Jazan University Department of Computer and Network Engineering Jazan Saudi Arabia B.S Abdur Rahman Crescent Institute of Science and Technology Department of Computer Application Tamil Nadu India

ISBN: (纸本)9781665454155

Ambiguity is an intrinsic deficiency of natural language written requirement documents. Requirement Engineers face difficulties while communicating with stakeholders from different backgrounds and knowledge to extract requirements. The selection of a suitable requirement elicitation technique plays a critical role to improve the quality of elicited requirements. Differences among elicitation techniques are very large;it implies that some techniques may perform better than others for a particular situation. Generally, requirement engineers select elicitation techniques based on their interests, knowledge, and experience. The selection of the right technique is critical as all techniques can not fit into different situations. In addition, before starting the new project, there is no software available that can help in selecting suitable elicitation techniques based on the situation. This paper proposed a software-based selection of suitable elicitation techniques used in SRAAF (software Requirement Ambiguity Avoidance Framework). The tool focuses on the first phase of SRAAF, specifically the situational parameter based selection of effective elicitation techniques. These situational parameters are mapped onto the knowledge base for the selection process. The tool takes situational parameters as input related to three categories: project, requirement engineer, and stakeholders. The tool suggests a technique based on situational parameters under the current settings. If any new evidence related to situational parameters, elicitation technique or contextual value is originated, these values or information can be easily included in the tool. © 2022 IEEE.

关键词： Engineers

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Enhancing Brain Tumor Classification Using Data-Efficient Image Transformer

Enhancing Brain Tumor Classification Using Data-Efficient Im...

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2024 International Russian Smart Industry conference, SmartIndustryCon 2024

作者： Yang, Jiafeng Rusak, Alena Belozubov, Alexander ITMO University Software Engineering and Computer Technology Dept. Saint-Petersburg Russia

ISBN: (纸本)9798350395044

Medical image analysis is essential in the diagnosis and treatment of many diseases, including brain tumors. This work investigates the effectiveness of transformer models in the multiclass classification of brain tumor MRI images. We use a combination of three publicly available brain tumor datasets classified into four categories and appropriately modify existing transformer variants, including adjustments to patch size, number of categories, dropout, etc. The results indicate that, due to the condition of insufficient data volume, most transformer variants are still inferior to the benchmark model VGG-16. The DeiT model with knowledge distillation has significantly improved various indices on the test set, verifying its effectiveness in the classification of brain tumor MRI images under limited data. The article supports the application of transformer-based models to medical image analysis. Follow-up work will verify the generalization performance of the model on other datasets and explore methods to reduce the dependence of the transformer on the data, making it more applicable to tasks such as medical images classification. © 2024 IEEE.

关键词： Distillation

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Script2Graph: Auto-construct Screenplay Text World by Mining Contextual Information 3

Script2Graph: Auto-construct Screenplay Text World by Mining...

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3rd IEEE International conference on software engineering and Artificial Intelligence, SEAI 2023

作者： Wang, Depei Cheng, Lianglun Liu, Hongwei Li, Ruihao Wang, Huilin Liu, Hongrui Guangdong University of Technology School of Automation Guangzhou China Guangdong University of Technology School of Computer Science and Technology Guangzhou China Tianjin Foreign Studies University Tianjin China Guangdong University of Technology School of Physics and Optoelectronic Engineering Guangzhou China Hanshan Normal University Chaozhou China San Jose State University San Jose United States

ISBN: (纸本)9798350337952

With the rapid development of artificial intelligence and the continuous emergence of innovative technologies, its application in movie scenes has gained attention. Meanwhile, the application of natural language processing techniques in movie scripts has gradually attracted the attention of researchers, making text information extraction more intelligent and convenient. However, most of the previous works for unstructured script processing ignore the theoretical guidance of computational language and lack the framework of knowledge schema. Therefore, we propose Script2Graph method based on text world theory to solve unstructured text information extraction and knowledge organization, and realize the automatic construction of script text world. Our experiments demonstrate that the method is effective in extracting text world elements and using high-quality information in downstream applications. © 2023 IEEE.

关键词： Computational linguistics

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Performance analysis of extracting object structure from source code 27

Performance analysis of extracting object structure from sou...

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27th International conference on knowledge based and Intelligent Information and engineering Sytems, KES 2023

作者： Wojszczyk, Rafal Hapka, Aneta Królikowski, Tomasz Faculty of Electronics and Computer Science Koszalin University of Technology 2 Sniadeckich Koszalin75-453 Poland

Tools for programmers are constantly evolving, and with that evolution comes tools that support their work, such as those that enable testing and analysis of program code. It is expected that tools integrated with programming environments will analyze code on the fly, and the results of the analysis will be available as soon as the program is compiled. This paper attempts to compare solutions for extracting object-oriented structure that begin the process of static source code analysis. Choosing the right solutions already at the beginning of static analysis, will affect the speed of the whole process as well as accuracy. And this will then affect the cost of programmers' work and the quality of the software tests performed. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： decompilation managed code object-oriented programming paradigm reverse engineering Static software analysis

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