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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9894 条记录，以下是1701-1710 订阅

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A Virtual Lab of Matrix-Assisted Laser Desorption Ionization MALDI-TOF Protocols for Microbiology Students 21st

A Virtual Lab of Matrix-Assisted Laser Desorption Ionization...

引用

21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Datta, Soma Syed, Ibrahim Ibaad Univ Houston Clear Lake Houston TX 77058 USA

ISBN: (纸本)9783031618901;9783031618918

This study is a practical way of teaching software engineering and microbiology in a virtual setting, which is beneficial during natural calamities, including the recent pandemic. This project details how the software engineering students developed a virtual lab for the microbiology students that started as a class project. The benefit of creating the project for the software engineering students was that it helped to develop their soft skills and the details of collecting requirements. Similarly, it allowed the microbiology students to collaborate with software engineering students to educate them on the protocol and eventually practice the MALDI-TOF experiment before they do it in their labs. Input from microbiology students seems crucial in ensuring that the virtual lab accurately reflects the real-world lab environment and meets the needs of those conducting experiments. This study explains how students learned to communicate in developing real-world software as a class project. The study exemplifies how technology can bridge the gap between theoretical knowledge and practical skills.

关键词： Virtual Lab Software Engineering Microbiology Virtual Reality

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Data-Driven Decision-Making Framework for Cost-Efficient Energy Retrofit of Italian Residential Building Stock

Data-Driven Decision-Making Framework for Cost-Efficient Ene...

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Intelligent systems Conference (IntelliSys)

作者： Khodabakhshian, Ania Cecconi, Fulvio Re Politecn Milan Built Environm & Construct Engn Dept Architecture Via Ponzio 31 I-20133 Milan Italy

ISBN: (纸本)9783031477201;9783031477218

Strategic decision-making to invest in building stock energy retrofit is a time-consuming task, requiring a significant amount of complex and technical data with high acquisition costs in its conventional form. Besides cost data of various retrofit alternatives, needing unit-based calculations, the monetary value of resulting benefits, like saved energy, should be considered for making cost-efficient decisions by policymakers. On the other hand, novel techniques for building retrofit are gaining increasing attention due to their vital role in sustaining the built environment and lowering energy consumption, especially in countries like Italy, where a significant share of the residential building stock is outdated. With advancements in data-collection methods and data-driven decision support systems, more data is available, based on which these decisions can be automated and optimized. This research aims to provide a comprehensive framework for an automated cost-benefit analysis for various energy retrofit scenarios given their energy-saving potential, implementation cost, and associated investment payback period. Based on Italian National databases, i.e., CENED (Building Energy Certificate), TABULA, and Superbonus Cost data of the Lombardy Region, this study proposes a building stock clustering using energy labels, building technologies, and construction period to identify building archetypes. Moreover, the maximum investment amount of each cluster (archetype) for different payback periods is calculated using Monte Carlo Simulation and is compared to the estimated retrofit cost based on regional price lists for each archetype. This cost-benefit analysis using estimated retrofit cost and saved energy cost contributes to faster, more objective, factual, and cost-optimized decision-making for urban-level energy retrofit decision-making, highlighting the importance of government funding and subsidies like Superbonus in achieving sustainability, energy efficiency, and de

关键词： Energy Retrofit Clustering Building Archetypes Cost-Benefit Analysis Payback Period Retrofit Cost

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Industrial Data Sharing Ecosystems: An Innovative Value Chain Traceability Platform Based in Data Spaces 12th

Industrial Data Sharing Ecosystems: An Innovative Value Chai...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Freitas, Josue Sousa, Cristovao Pereira, Carla Pinto, Pedro Ferreira, Ricardo Diogo, Rui Campus FEUP INESC TEC Rua Dr Roberto Frias P-4200465 Porto Portugal Polytech Porto ESTG Rua CurralCasa Curral P-4610156 Felgueiras Portugal

ISBN: (纸本)9783031602207;9783031602214

Considering the great challenge of implementing digital tools to improve collaboration in the value chain and promote the adoption of circularity strategies, as is the case with digital traceability tools and digital product passports. This paper presents an innovative proposal for implementing an industrial data sharing ecosystem, namely an architecture and platform for digital traceability between entities based on Data Spaces. To validate our proposal, a use case scenario was implemented as part of the BioShoes4All project.

关键词： Digital Product Passport Digital Traceability Information Sharing International Data Spaces

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A Proposal for Mediative Fuzzy Control

A Proposal for Mediative Fuzzy Control

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Melin, Patricia Castillo, Oscar Tijuana Inst Technol TecNM Tijuana 22379 BC Mexico

ISBN: (纸本)9783031671913;9783031671920

We are presenting the utilization of mediative fuzzy logic (MFL) in control. MFL was initially put forward with the idea of modeling contradictory knowledge among two or more experts. In this case, an MFL solution could be a better alternative in a control problem. We are extending fuzzy control to the MFL realm for cases where there are at least two experts and fuzzy controller design is based on their knowledge. Simulation results in a nonlinear plant show the feasibility of the proposal by surpassing alternative approaches. This conceptualization and its applications have no been previously presented in the literature.

关键词： Control Mediative Fuzzy Logic

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Setting Vector Quantizer Resolution via Density Estimation Theory 15th

Setting Vector Quantizer Resolution via Density Estimation T...

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15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM)

作者： Taylor, Josh Offner, Stella Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9783031671586;9783031671593

We introduce a framework for selecting the number of codebook vectors in a vector quantizer based on local characteristics of the data density, the degree to which the process of VQ distorts the representation of this density, and the theoretical efficiency of estimators of these densities. In our analysis, L-2 theory from kernel density estimation relates the number of VQ prototypes to observed sample size, dimension, and complexity, all of which intuitively influence codebook sizing.

关键词： Vector Quantization Variable Kernel Density Estimation

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How Can Pneumatics Be Trained with Augmented Reality in the Context of Training for Industrial-Technical Professions? 21st

How Can Pneumatics Be Trained with Augmented Reality in the ...

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21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Terschueren, Jan-Niklas Varney, Valerie Mueller, Larissa Cologne Univ Appl Sci Proc Engn Energy & Mech Syst Cologne Germany

ISBN: (纸本)9783031618901;9783031618918

Augmented reality (AR) holds promise as a technology for creating hands-on learning environments. This paper presents the development of an AR-based training program for pneumatics teaching, aiming to investigate the effects of different elements of AR visualization on learning and knowledge acquisition. Two concepts for AR visualization elements were developed: a realistic replica of the pneumatic system and a concept that incorporates additional AR elements, such as airflow tracking and an X-ray view. A mixed-methods approach study was conducted with fifteen first-year industrial mechanics apprentices. The participants were divided into three groups (traditional learning method, concept 1, concept 2) and performed two practical exercises on pneumatics. The results indicated that AR-based training can be an effective method for imparting knowledge in the field of pneumatics. However, the type of visualization used significantly impacts the learner's knowledge absorption. Visualizations conveying additional information, such as airflow tracking and an X-ray view, proved to help learners better understand and internalize complex relationships and functionalities. This study suggests that AR-based training is an effective way to teach pneumatics, but the choice of visualization is crucial. Visualizations providing additional information, such as airflow tracking and an X-ray view, enhance learners' understanding and internalization of complex relationships and functionalities. More research is needed to validate these findings and explore additional ways to use AR to improve the learning experience in pneumatics and other technical fields.

关键词： augmented reality AR-training education pneumatics didactics

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Integration of Smart IoT Sensors into the Home Environment in a ZigBee Network 13th

Integration of Smart IoT Sensors into the Home Environment i...

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13th Computer Science Online Conference

作者： Strelec, Peter Horak, Tibor Kovac, Szabolcs Sido, Jan Csekei, Martin Ruzarovsky, Roman Slovak Univ Technol Bratislava Fac Mat Sci & Technol Trnava Inst Appl Informat Automat & Mechatron Trnava Slovakia Slovak Univ Technol Bratislava Fac Mat Sci & Technol Trnava Inst Mfg Technol Trnava Slovakia

ISBN: (纸本)9783031702990;9783031703003

Nowadays, people interact with various smart devices daily. The high transmission speed, accessibility, easy user experience, and low cost have contributed to the increasing popularity of these devices. The digitization and automation of the entire society, individual production systems and the development of artificial intelligence are undoubtedly gaining momentum. These are important means of increasing efficiency, productivity, and quality and contributing to cost reduction. The need for connectivity, monitoring, and tracking has been transferred not only to companies but also to households. With a smart home, we can control the entire household remotely, automate and simplify our daily activities, contribute to sustainability and greening, e.g., by regulating and monitoring energy consumption, and secure the entire household against damage and robbery. The aim of this article is to present the use of devices - sensors in the home to protect the property, pointing out the need to integrate them properly.

关键词： IoT smart home IoT sensors Zigbee protocol

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Targeted Image Reconstruction by Sampling Pre-trained Diffusion Model

Targeted Image Reconstruction by Sampling Pre-trained Diffus...

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Intelligent systems Conference (IntelliSys)

作者： Zheng, Jiageng Lehigh Univ Dept Comp Sci Bethlehem PA 18015 USA

ISBN: (纸本)9783031477201;9783031477218

A trained neural network model contains information on the training data. Given such a model, malicious parties can leverage the "knowledge" in this model and design ways to print out any usable information. Therefore, it is valuable to explore the ways to conduct such an attack and demonstrate its severity. In this work, we proposed ways to generate a data point of the target class without prior knowledge of the exact target distribution by using a pre-trained diffusion model. The result shows that the attacker can generate images that are similar to the attacking target by leveraging a pre-trained diffusion model.

关键词： Model Inversion Attack Latent Variable Generative Model Diffusion Model

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Beaver Habitat Terrain Identification Using Aerial Imagery 9th

Beaver Habitat Terrain Identification Using Aerial Imagery

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9th International Congress on Information and Communication Technology (ICICT)

作者： Chawathe, Swanand Pravin Saffaf, Rahaf Garbagna, Lorenzo Saheer, Lakshmi Babu Oghaz, Mandi Maktabdar Wheeler, Helen C. Anglia Ruskin Univ Fac Sci & Engn Cambridge CB1 1PT England

ISBN: (纸本)9789819735556;9789819735563

Beavers are important species with a strong influence on ecosystems, their damming activities transform ecosystems through wetland creation and consequent hydrological change. As such they are known as ecosystem engineers. This study concerns the real-world problem of understanding the distribution of beavers by identifying their habitat and terrains using drone imagery. Experiments are performed to investigate several state-of-the-art Convolutional Neural networks ranging from the custom designed and pre-trained classification models such as ConvNeXt to segmentation models such as Mask RCNN to identify beaver habitats (including dams and lodges) and different terrains. Efforts are made to improve the explainability of the models through spatial heatmaps overlays. This research offers accurate identification of beaver habitats using aerial images by achieving high accuracy rates of 98% which is crucial for effective decision-making related to beavers and understanding the changes that their populations create.

关键词： Beavers Terrain identification Deep learning Image segmentation Convolutional neural networks

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A Systematic Literature Review on Regression Machine Learning for Urban Flood Hazard Mapping 4th

A Systematic Literature Review on Regression Machine Learnin...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： El Baida, Maelaynayn Boushaba, Farid Chourak, Mimoun Hosni, Mohamed Zahaf, Toufik Sabar, Hichame Mohamed 1st Univ Natl Sch Appl Sci Oujda Lab Modeling & Sci Computat LMCS Oujda 60000 Morocco Mohammed 1st Univ Natl Sch Appl Sci Oujda Mech & Appl Math Dept Ind & Seism Engn Res Team Oujda 60000 Morocco Moulay Ismail Univ MOSI ENSAM Meknes L2M3S Meknes Morocco Mohammed 1st Univ Fac Sci Oujda FSO Appl Geosci Lab LGA Oujda Morocco

ISBN: (纸本)9783031686498;9783031686504

Regression and classification serve as indispensable machine learning (ML) tasks in urban flood hazard mapping. While a machine learning classifier can effectively predict flood hazard, employing a regression model proves instrumental in estimating and predicting flood characteristics within urban areas. This approach reduces the computational time associated with the hydrodynamic models. This paper provides a systematic literature review (SLR) of the current state-of-the-art regression ML models applied in urban flood hazard mapping. A total of 30 articles published between 2018 and 2023 were collected from Five online libraries, i.e., Scopus, Web of Science, IEEE Xplore, Springer, MDPI, and Taylor and Francis. The SLR addresses the raised research questions and reveals that Convolutional Neural Network (CNN) emerged as both the most accurate and frequently employed model. Additionally, the SLR extends its scope to investigate aspects such as flood type, the input data, and the spatial scale of the study area.

关键词： Machine learning Regression Flood Urban flood

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