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检索条件"任意字段=18th International Conference on Software Engineering and Knowledge Engineering"

共 35586 条记录，以下是421-430 订阅

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Automatic Emotion Detection using SVM-based Optimal Kernel Function 18

Automatic Emotion Detection using SVM-based Optimal Kernel F...

引用

18th INDIAcom;11th international conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Priya, M. Ranjani, B. Rajammal, K. Murali, N. Tamilselvi, M. Kavitha, M. E.G.S. Pillay Engineering College Dept. of Cse Nagapattinam India Roever Engineering College Dept. of Cse Perambalur India A.V.C. College of Engineering Dept. of Cse Mayiladuthurai India

ISBN: (纸本)9789380544519

Facial expression is very essential in interpersonal relationships. Human-machine interaction is a recently emerging field in which the Facial Expression Recognition System (FERS) is a key aspect in determining the emotional state of a person. this paper proposes a unique way for automatically identifying face expressions from images using Principal Component Analysis (PCA). the proposed approach employs Haar features of the image to detect the face component. the PCA approach is then employed to extract the efficient Haar facial features, resulting in the Eigenvectors, which include dimensionality reduction. A SVM classifier with a kernel function is used to recognize common human emotions such as happiness, fear, sadness, etc. the experimental results demonstrate that the technique proposed in this research is more effective at classifying various expressions and has a higher recognition rate than traditional approaches. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Emotion Recognition Image Processing Kernel Function Radial Basis Kernel Support Vector Machine

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Sustainability Analysis and Improvement of Model Driven engineering and Model Transformation Languages 15

Sustainability Analysis and Improvement of Model Driven Engi...

引用

15th international conference on Information and knowledge Technology, IKT 2024

作者： Lano, Kevin Rahimi, Shekoufeh Kolahdouz Informatics Dept King’s College London London United Kingdom School of Arts University of Roehampton London United Kingdom

ISBN: (纸本)9798331522254

software sustainability has been an increasing concern in recent years due to global initiatives to reduce the greenhouse gas emissions and energy use of industrial society, aimed at limiting climate change. Model-driven engineering (MDE) could have an important role in reducing the resources required to develop software, and in optimising software products to reduce their environmental impact. Here we will focus on the energy use of MDE itself, and particularly the resource requirements of model transformations (MT), which are a core process within MDE. We compare the UML-RSDS and ATL transformation languages with regard to their energy use, and evaluate optimisation techniques for the reduction of MT energy use. © 2024 IEEE.

关键词： Greenhouse gas emissions

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Detecting Semantic-level Polysemy Ambiguity by Fusing External Semantic knowledge 36

Detecting Semantic-level Polysemy Ambiguity by Fusing Extern...

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36th international conference on software engineering and knowledge engineering, SEKE 2024

作者： Yang, Huishan Peng, Fengyong Wu, Xi Zhao, Yongxin Li, Yongjian Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China The University of Sydney Australia State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)1891706594

Sentence with polysemous words can easily be interpreted as different meanings by different people even in a specific context, which will significantly reduce the quality of requirements documents. However, existing ambiguity detection mainly considers the sentence structure and cannot solve this problem well. In this paper, we consider sentence semantics and perform sentence ambiguity detection by introducing external semantic knowledge to explicitly modeling the different semantics of polysemy. Specifically, we determine the target polysemy in the given sentence according to the ambiguous vocabulary list. Furthermore, based on the fusion strategy we designed, we model the different semantics of polysemous word by introducing external semantic knowledge and predict the possible semantics of the sentence by measuring the the gap between different semantic fusion results and the original sentence. this is also the first work to introduce external semantic knowledge into ambiguity detection. the experimental results illustrate that our accuracy is higher than the baseline accuracy of ambiguity in existing research. © 2024 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Latent semantic analysis

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MICROBIAL CONTAMINATION COMPARISON BETWEEN SUSTAINABLE AVIATION FUEL (SAF) AND JET A-1 18

MICROBIAL CONTAMINATION COMPARISON BETWEEN SUSTAINABLE AVIAT...

引用

18th international conference on Stability Handling and Use of Liquid Fuels, IASH 2024

作者： Nicoletti, Danika Carter, Timothy Bjorndahl, Paul Schmidt, Jordan LuminUltra Technologies Ltd. 520 King Street1 Fredericton NBE3B 6G3 Canada Centre for Water Resources Studies Department of Civil and Resource Engineering Dalhousie University 1360 Barrington Street HalifaxNSB3H 4R2 Canada Department of Mathematics & Statistics Dalhousie University 6316 Coburg Road PO BOX 15000 HalifaxNS Canada

the use of Sustainable Aviation Fuel (SAF) in commercial aviation can reduce CO2emissions by up to 80%, playing an important role in the international Air Transport Association's (IATA) goal of achieving net zero carbon emissions by 2050. As demand grows, production volumes will continue to increase for SAF which will require clean storage to maintain product quality. Previous studies have investigated microbial contamination in Jet A-1 fuel storage, however, there is a gap in knowledge for the susceptibility of SAF to microbial contamination. In this laboratory study, the microbial community dynamics of contaminated fuels were monitored and characterized. Microcosms were set up with either SAF or Jet A-1 and Bushnell Haas medium to simulate tank bottoms water. the same hydrocarbon-degrading inoculum was applied to each microcosm along with a no-substrate control. the microcosms were incubated over 12 weeks and were sacrificed and analyzed at regular intervals for testing adenosine triphosphate (ATP) concentration, qPCR for total prokaryotes, and 16S rRNA gene sequencing for total microbial community analysis. ATP concentration results revealed higher microbial activity in SAF microcosms over the course of the experiment by an order of magnitude compared to Jet A-1 microcosms, while qPCR and 16S rRNA gene sequencing analyses revealed a comparable microbial community structure over time between the two substrates. this study aims to address the gap in knowledge of SAF susceptibility to microbial contamination providing insight into the risks involved in its storage compared to Jet A-1 fuel. © 2024 Proceedings of the 18th international conference on Stability Handling and Use of Liquid Fuels, IASH 2024. All rights reserved.

关键词： Adenosinetriphosphate

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Changes of Indoor Air Quality System in Korea 18

Changes of Indoor Air Quality System in Korea

引用

18th international conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Kim, Yoon Shin Kim, Jo-Chun Sunwoo, Young Lee, Cheol Min Seoul Korea Republic of Department of Civil and Environmental Engineering Konkuk University Seoul Korea Republic of Department of Chemical & Environmental Engineering Seokyeong University Seoul Korea Republic of

ISBN: (纸本)9798331306816

the purpose of this study was to introduce how the Korea Ministry of Environment's indoor air quality policies have changed from the late 1980s to the present and what policies will be established in the future. Korean Ministry of Environment (KMOE) enacted "Act of Underground Air Quality Management" in 1996 and the ‘Act of Indoor Air Quality Management in Public facilities" in 2004 was enacted to control air quality management in multi-use facilities to improve indoor air quality (IAQ) after designating standards for five pollutants and guidelines for five pollutants for the first time in the world. In addition, the updated Indoor Air Quality Management Act (IAQMA) was established in 2013 to protect the health of the people and prevent risks arising from various indoor air pollutants. In addition, KMOE is promoting development of indoor air quality industry through domestic and international market surveys. In this study, the "Indoor Air Quality Management Act" in Korea is mainly discussed to focus on the process of system change. © 2024 18th conference of the international Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - conference Program and Proceedings. All rights reserved.

关键词： Indoor air pollution

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Land Cover Extraction from Satellite Imagery using U-Net Model 18

Land Cover Extraction from Satellite Imagery using U-Net Mod...

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18th INDIAcom;11th international conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Rani, K. Pushpa Sreedevi, Pogula Dastagiriah, C. Rao, K. Srinivas Subbaraju, G.V. Padmavathi, Jasti Mlr Institute of Technology Dept. of Computer Science and Engineering Hyderabad India G. Pulla Reddy Engineering College Dept. of Computer Science and Engineering Kurnool India Anurag University Dept. of Computer Science and Engineering Hyderabad India Scetw Dept. of Computer Science and Engineering Hyderabad India Hyderabad India

ISBN: (纸本)9789380544519

Satellite imagery offers extensive information that can be used for a variety of societal applications, from the number of buildings in a metropolis to the land cover types of a specific area. However, extracting such information is a difficult task. In the past, images were scanned manually by domain experts to extract features like buildings, infrastructure, and vegetation, which would take weeks or even months depending on the image size. To address this challenge, we trained our model using U-Net architecture, a deep learning model, because of its advantages in multiscale feature learning and faster processing. Data augmentation is done on the dataset in order to enhance the amount of data and prevent overfitting artificially. the trained model achieved an F1 score of 92% and an impressive precision score of 95%. this automated method can be scaled to large sets of data, reducing the need for human labeling. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Data augmentation Deep learning Machine learning Multiscale feature learning U-Net architecture

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software Testing Effort Estimation Based on Machine Learning Techniques: Single and Ensemble Methods 16

Software Testing Effort Estimation Based on Machine Learning...

引用

16th international conference on knowledge Discovery and Information Retrieval, KDIR 2024 as part of 16th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2024

作者： Hosni, Mohamed Medarhri, Ibtissam Carrillo de Gea, Juan Manuel MOSI Research Team LM2S3 ENSAM Moulay Ismail University of Meknes Morocco MMCS Research Team LMAID ENSMR Rabat Morocco Department of Informatics and Systems Faculty of Computer Science University of Murcia Spain

ISBN: (纸本)9789897587160

Delivering an accurate estimation of the effort required for software system development is crucial for the success of any software project. However, the software development lifecycle (SDLC) involves multiple activities, such as software design, software build, and software testing, among others. software testing (ST) holds significant importance in the SDLC as it directly impacts software quality. Typically, the effort required for the testing phase is estimated as a percentage of the overall predicted SDLC effort, typically ranging between 10% and 60%. However, this approach poses risks as it hinders proper resource allocation by managers. Despite the importance of this issue, there is limited research available on estimating ST effort. this paper aims to address this concern by proposing four machine learning (ML) techniques and a heterogeneous ensemble to predict the effort required for ST activities. the ML techniques employed include K-nearest neighbor (KNN), Support Vector Regression, Multilayer Perceptron Neural Networks, and decision trees. the dataset used in this study was obtained from a well-known repository. Various unbiased performance indicators were utilized to evaluate the predictive capabilities of the proposed techniques. the overall results indicate that the KNN technique outperforms the other ML techniques, and the proposed ensemble showed superior performance accuracy compared to the remaining ML techniques. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Contrastive Learning

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Analysis of an occupancy-based estimation of cross ventilation rates and effective opening area 18

Analysis of an occupancy-based estimation of cross ventilati...

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18th international conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Yoo, Jihyun Bae, Jaeyun Park, Junseok Hanyang University Seoul Korea Republic of Department of Architectural Engineering Hanyang University Seoul Korea Republic of

ISBN: (纸本)9798331306816

In the pursuit of reducing energy consumption and mitigating indoor pollutants in residential buildings, there has been considerable research on the efficient utilization of natural and mechanical ventilation systems. While previous studies have focused on the behavior of occupants in opening windows, quantitatively assessing the degree of ventilation solely through window opening behavior has proven challenging. Consequently, it becomes difficult to predict energy consumption and indoor pollutant levels accurately. In this study, we estimate natural ventilation rates during window opening considering the occupancy of occupants and derive the effective opening areas of windows accordingly. through the determination of these effective opening areas, proposing a standardized model for window opening behavior among occupants in Korean residential buildings, and predicting energy consumption based on this model, it would be possible to anticipate providing valuable insights for eco-friendly building designs. © 2024 18th conference of the international Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - conference Program and Proceedings. All rights reserved.

关键词： Indoor air pollution

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What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims 24

What do we know about Hugging Face? A systematic literature ...

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18th ACM/IEEE international Symposium on Empirical software engineering and Measurement, ESEM 2024

作者： Jones, Jason Jiang, Wenxin Synovic, Nicholas thiruvathukal, George Davis, James Purdue University West LafayetteIN United States Loyola University Chicago ChicagoIL United States

ISBN: (纸本)9798400710476

Background: software Package Registries (SPRs) are an integral part of the software supply chain. these collaborative platforms unite contributors, users, and code for streamlined package management. Prior work has characterized the SPRs associated with traditional software, such as NPM (JavaScript) and PyPI (Python). Pre-Trained Model (PTM) Registries are an emerging class of SPR of increasing importance, because they support the deep learning supply chain. A growing body of empirical research has examined PTM registries from various angles, such as vulnerabilities, reuse processes, and evolution. However, no synthesis provides a systematic understanding of current knowledge. Furthermore, much of the existing research includes non-quantified qualitative observations. Aims: First, we aim to provide a systematic knowledge synthesis. Second, we quantify qualitative claims. Methods: We conducted a systematic literature review (SLR). We then observed that some of the claims are qualitative, lacking quantitative evidence. We identify quantifiable metrics associated with those claims, and measure in order to substantiate these claims. Results: We identify 12 claims about PTM reuse on the HuggingFace platform, 4 of which lack quantitative support. We tested 3 of these claims through a quantitative analysis, and directly compare the fourth with traditional software. Our most notable findings are: (1) PTMs have a significantly higher turnover rate than traditional software, indicating more rapid evolution;and (2) there is a strong correlation between documentation quality and PTM popularity. Conclusions: Our findings validate several qualitative research claims with concrete metrics, confirming prior research. Our measures motivate further research on the dynamics of PTM reuse. © 2024 Owner/Author.

关键词： software packages

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Investigating the protection effect of gaspers in an aircraft cabin with personalized displacement ventilation 18

Investigating the protection effect of gaspers in an aircraf...

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18th international conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Hou, Yunge You, Ruoyu Department of Building Environment and Energy Engineering The Hong Kong Polytechnic University Kowloon Hong Kong999077 Hong Kong

ISBN: (纸本)9798331306816

Overhead gaspers provide directional fresh airflow, and thus affect the local airflow pattern and contaminant distribution. To investigate gaspers’ protection effect in an aircraft cabin with personalized displacement ventilation, numerical calculations were conducted in a seven-row, single-aisle, fully occupied, economy-class aircraft cabin with the computational fluid dynamics (CFD) method. three receptors with different seat types were considered. We investigated the impact of receptor gasper’s direction and flow rate on his/her exposure. the results showed that turning on a receptor passenger’s gasper with an appropriate setting could be an effective strategy to protect the receptor, and the working mechanism was revealed. © 2024 18th conference of the international Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - conference Program and Proceedings. All rights reserved.

关键词： Cabins (aircraft)

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