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Research on Plant Allocation of Sponge City Construction Based on Deep learning 1

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4th international conference on 3D Imaging Technologies- Multidimensional Signal Processing and Deep learning, 3D IT-MSP and DL 2022

作者： Wang, Huishan Zhao, Xiang Chen, Jiating School of Architecture and Civil Engineering Xiamen Institute of Technology Fujian Xiamen361021 China

ISBN: (数字)9789819911455

ISBN: (纸本)9789819911448

Since the construction of Sponge City in China, the research on the construction of Sponge City has mostly focused on the engineering level, and the research on the selection, function and configuration of plants has lagged behind, resulting in unreasonable plant selection, lack of "localization" of plant design, and lack of systematic and targeted consideration and design of plant landscape configuration, which has restricted the construction and development of Sponge City to some extent. Mian city can reduce urban waterlogging, improve the utilization rate of water resources, and meet the requirements of green environmental protection development in China. through analysis, the functions of plants in Sponge City are summarized as landscaping and ecological protection. Based on the clues of meeting these two functions, combined with in-depth learning, this paper proposes the principles of plant selection and configuration under the concept of Sponge City, which provides a theoretical basis for the selection of plants in the construction of Sponge City. the paper summarizes the plants that can be used in sponge cities, and draws the common plant configuration patterns in low impact development facilities during the research process, providing relevant theoretical basis and experience for further construction of sponge cities in China. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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4th international conference on smart Sensors and Application: Digitalization for Societal Well-Being, ICSSA 2022

4th International Conference on Smart Sensors and Applicatio...

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4th international conference on smart Sensors and Application, ICSSA 2022

ISBN: (纸本)9781665499811

the proceedings contain 34 papers. the topics discussed include: dual-band funny-face wi-fi energy harvester for indoor battery-less wireless sensor;inverted global sensor for automated guided vehicle localization and navigation;an integrated handheld biosensing device with IoT system for in-situ and rapid detection of multi-mycotoxins;development of predictive maintenance system for hemodialysis reverse osmosis water purification system;machine learning techniques for intrusion detection in smart healthcare systems: a comparative analysis;performance analysis of passively q-switched fiber laser by SWCNT-PVA saturable absorber;depth estimation from video using computer vision and machine learning with hyperparameter optimization;load balancing in software-defined data center with fat tree architecture;a bio-inspired territorial predator scent marking algorithm in software-defined data center;and blockchain-based distributed file system security and privacy: a systematic mapping study.

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Space and Time in Hybrid Teaching and learning Environments: Two Cases and Design Principles 7th

Space and Time in Hybrid Teaching and Learning Environments:...

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7th international conference on smart learning ecosystems and regional development, SLERD 2022

作者： Leinonen, Teemu Mäkelä, Tiina School of Arts Design and Architecture Aalto University Helsinki Finland University of Jyväskylä Jyväskylä Finland

ISBN: (纸本)9789811952395

the opportunities and challenges of teaching and learning in the same and different space and time have been discussed in the field of distance education for several decades. Within COVID-19, a new type of experimenting and research interest in so-called hybrid learning has emerged. In this article, we present the results from exploring "hybridity" from the perspective of classical categorizations of different forms of learning in terms of time and space. We explored the phenomenon through two cases with the same high-level strategic objective, serving hybrid interaction. In case A, we evaluated university library spaces renovated to serve hybrid teaching and learning. In case B, the focus was on the implementation of a university course redesigned during the pandemic from blended learning to include more hybrid interaction. Multifaceted data was collected, including video recordings (case A), recorded videoconference sessions, and written student feedback (case B). Qualitative data analyses relied on ethnography and contextual inquiry. Based on the analyses of the case studies, we propose five design principles for designing hybrid teaching and learning that aim to overcome the limitations of the same space and time: (1) Ensuring access to required tools, infrastructure, and support;(2) Design primarily for same time, different place learning;(3) Design primarily for same time, same place learning;(4) Less is more;and (5) "Le bon Dieu est dans le détail." these design principles provide guidance to the design process of hybrid teaching and learning to increase the chances of reaching a successful solution. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Video recording

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Fashion Recommendation System Using Machine learning 4

Fashion Recommendation System Using Machine Learning

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4th international conference on smart Electronics and Communication, ICOSEC 2023

作者： Sivaranjani, Lingala Rachamadugu, Sandeep Kumar Reddy, B.V. Suresh Basi Reddy, A. Sakthivel, M. Depuru, Sivakumar School of Computing Mohan Babu University Tirupati India G. Pulla Reddy Engineering College Dep. of Cse A.P Kurnool India Koneru Lakshmaiah Education Foundation Dept. Of. Cse A.P Vaddeswaram India Tirupati India

ISBN: (纸本)9798350300888

For the past few years, fast fashion has become very popular, which has had a great impact on the textile and fashion industries. Fashion is an integral part of one's daily lives, and it has a significant impact on identity and self-expression. With the increasing availability of digital platforms and e-commerce websites, the fashion industry has transformed, and the way one shops for clothing has evolved. the rise of e-commerce has brought about a rise in the use of fashion recommendation systems. these systems aim to offer personalized product recommendations to users according to their interests and preferences. the field of machine learning has made significant strides in the development of image processing techniques, parsing techniques, image classification, segmentation, and networking, making it an ideal candidate for powering these recommendation systems. With these advancements in technology, the potential for fashion recommendation systems to provide even more accurate and individualized product recommendations is substantial. In this study, the dataset is used and the main technique is to use machine learning by splitting into training and testing data of the dataset. the convolutional neural network is used to produce similar items in the recommendation system. the CNN layers are upgraded by using RESNET50 and the filtering content is based on data provided for the product. the RESNET50 helps in overcome the problem of vanishing gradient. then KNN algorithm is used to recommend similar items. the main idea behind KNN is Euclidean distance and Cosine Similarity which helps in producing similar products. the user's past behavior is significant here and the convolutional neural networks (CNN) model was also utilized for picture categorization and recognition. the experimental results of the system achieved retrieval accuracy and outperformed the baseline. © 2023 IEEE.

关键词： Image recognition

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development of Secure Hardware Architectures for Preventing Side-Channel Attacks and Protecting Sensitive Data in VLSI Systems 4

Development of Secure Hardware Architectures for Preventing ...

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4th international conference on smart Electronics and Communication, ICOSEC 2023

作者： Kumara, Varuna Jayakumar, S. Rani, D. Leela Maranan, Ramya Ramesh, D. Raja Deivakani, M. Moodlakatte Institute of Technology Kundapura Department of Artificial Intelligence and Machine Learning Karnataka Kundapura576217 India Sri Sairam College of Engineering Anekal Department of Electronics and Communication Engineering Bengaluru562106 India School of Engineering Mohan Babu University Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India Saveetha School of Engineering Department of Research and Innovation Tamil Nadu Chennai602105 India Chintalavalasa Department of Electronics and Communication Engineering Vizianagaram535005 India PSNA College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Dindigul624622 India

ISBN: (纸本)9798350300888

this research paper has been developed by targeting to develop the secure hardware architecture for preventing the potential threats like side channel attack and protecting sensitive data in VLSI systems. In this context, major of the key security frameworks like information theory, cryptography, online threats protector has been implemented in this study. It has been found, on the basis of extensive simulations, that the innovative design effectively protects against side-channel assaults and cuts the chance of mistakes by half, from 16 to 1. this concept has the potential to deliver considerable advantages for a variety of different sectors, including the Internet of things, the military, and aerospace. In order to improve the design's overall performance and investigate the ways in which it could be applicable to other VLSI systems, more study could be carried out. © 2023 IEEE.

关键词： Computer software

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A Multi-Attention Mechanisms Based Transfer learning Framework for State of Health Estimation of Lithium-ion Battery 4

A Multi-Attention Mechanisms Based Transfer Learning Framewo...

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4th international conference on smart Power and Internet Energy Systems (SPIES)

作者： Lu, Dong Cui, Naxin Li, Changlong Shandong Univ Sch Control Sci & Engn Jinan Peoples R China

ISBN: (纸本)9781665489577

Accurate state of health (SOH) estimation is essential for ensuring the stable and safe operation of lithium-ion batteries. However, the adaptability of the estimation method for batteries with different formulations remains challenging. In this paper, partial charging segments are collected and processed. A pre-training convolutional neural network (CNN), which combines attention mechanisms for heightening the estimation performance, is proposed for integrating the inputs and extracting the hidden features automatically. Experiments are performed to show that the proposed method could reduce the estimation error by 80.9%, 41.3% and 25.6% for LCO, LFP and NCA respectively. Moreover, to reduce the computation burden between different kinds of batteries, a transfer learning (TL) strategy is utilized by fine-tuning the dense layers. the transfer learning results show that the estimation root mean square error (RMSE) of LFP and NCA are only 1.3% and 2.6%, respectively.

关键词： Lithium-ion battery state of health (SOH) partial charging segments convolutional neural network transfer learning

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4th international conference on Recent Trends in Advanced Computing - Computer Vision and Machine Intelligence Paradigms for Sustainable development Goals, ICRTAC-CVMIP 2021

4th International Conference on Recent Trends in Advanced Co...

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4th international conference on Recent Trends in Advanced Computing - Computer Vision and Machine Intelligence Paradigms for Sustainable development Goals, ICRTAC-CVMIP 2021

ISBN: (纸本)9789811971686

the proceedings contain 30 papers. the special focus in this conference is on Recent Trends in Advanced Computing - Computer Vision and Machine Intelligence Paradigms for Sustainable development Goals. the topics include: Advanced Algorithmic Techniques for Topic Prediction and Recommendation—An Analysis;Implementation of an Automatic EEG Feature Extraction with Gated Recurrent Neural Network for Emotion Recognition;high Performance Classifier for Brain Tumor Detection Using Capsule Neural Network;Mining Suitable Symptoms to Identify Disease Using Apriori and NBC;background Features-Based Novel Visual Ego-Motion Estimation;livspecs: Design and Implementation of smart Specs for Hearing and Visually Challenged Persons;Self-balancing Robot Using Arduino and PID Controller;a Survey Based on Online Voting System Using Blockchain Technology;convergence Perceptual Model for Computing Time Series Data on Fog Environment;survey on Collaborative Filtering Technique for Recommender System Using Deep learning;a Survey on Power Consumption Indicator Using Machine learning-Based Approach;a Novel Hand Gesture Recognition for Aphonic People Using Convolutional Neural Network;comprehensive Analysis of Defect Detection through Image Processing and Machine learning for Photovoltaic Panels;covid Analysis Prediction Using Densenet Method in Deep learning;Feature Extraction Based on GLCM and GLRM Methods on COVID-19 Dataset;memory Augmented Distributed Monte Carlo Tree Search Algorithm-Based Content Popularity Aware Content Recommendation Using Content Centric Networks;Enhancing Protection Against Scalper Bots with ML;An Enhanced Optimized Abstractive Text Summarization Traditional Approach Employing Multi-layered Attentional Stacked LSTM with the Attention RNN;implementation of Machine learning Methods on Data to Analyze Emotional Health;SMS Spam Classification Using PSO-C4.5.

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8th Workshop on Software Architecture Erosion and Architectural Consistency, SAEroCon 2021, 1st international Workshop on Software Architecture and Machine learning, SAML 2021, 4th international Workshop on Context-aware, Autonomous and smart Architecture, CASA 2021, 5th Workshop on Formal Approaches for Advanced Computing Systems, FAACS 2021, 2nd international Workshop on Model-Driven Engineering for Software Architecture, MDE4SA 2021 and 1st international Workshop on Mining Software Repositories for Software Architecture, MSR4SA 2021 which complemented 15th European conference on Software Architecture, ECSA 2021

8th Workshop on Software Architecture Erosion and Architectu...

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8th Workshop on Software Architecture Erosion and Architectural Consistency, SAEroCon 2021, 1st international Workshop on Software Architecture and Machine learning, SAML 2021, 4th international Workshop on Context-aware, Autonomous and smart Architecture, CASA 2021, 5th Workshop on Formal Approaches for Advanced Computing Systems, FAACS 2021, 2nd international Workshop on Model-Driven Engineering for Software Architecture, MDE4SA 2021 and 1st international Workshop on Mining Software Repositories for Software Architecture, MSR4SA 2021 which complemented 15th European conference on Software Architecture, ECSA 2021

ISBN: (纸本)9783031151156

the proceedings contain 15 papers presendted at a virtual meeting. the special focus in this conference is on Software Architecture Erosion and Architectural Consistency. the topics include: Interactive Elicitation of Resilience Scenarios Based on Hazard Analysis Techniques;Towards an Extensible Approach for Generative Microservice development and Deployment Using LEMMA;applying Knowledge-Driven Architecture Composition with Gabble;architectural Optimization for Confidentiality Under Structural Uncertainty;foundations and Research Agenda for Simulation of smart ecosystems Architectures;Blended Graphical and Textual Modelling of UML-RT State-Machines: An Industrial Experience;toward Awareness Creation of Common Challenges Women are Facing in Academia: A Study from a German Perspective;mapping Source Code to Modular Architectures Using Keywords;hierarchical Code-to-Architecture Mapping;Building the MSR Tool Kaiaulu: Design Principles and Experiences;self-adaptive Machine learning Systems: Research Challenges and Opportunities;behavioral Maps: Identifying Architectural Smells in Self-adaptive Systems at Runtime;an Architectural Approach for Enabling and Developing Cooperative Behaviour in Diverse Autonomous Robots.

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An Automated Human Action Recognition and Classification Framework Using Deep learning 4

An Automated Human Action Recognition and Classification Fra...

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4th international conference on Computing, Mathematics and Engineering Technologies, iCoMET 2023

作者： Waheed, Shamsa Amin, Rashid Iqbal, Javed Hussain, Mudassar Bashir, Muhammad Adeel Uet Department of Computer Sciences Taxila Pakistan University of Chakwal Department of Computer Sciences Chakwal Pakistan University of Sialkot Faculty of Computing and Information Technology Sialkot Pakistan

ISBN: (纸本)9798350335316

Human activity recognition has captivated the interest of researchers due to its significant applications such as smart home health care systems in which this technology can be applied to enhance the patients' rehabilitation. Different sensors can be used in a variety of ways to recognize human activity in a smartly managed environment. It is also used in pedestrian detection, robotics and human-computer interface, etc. Hence, with the development of Artificial Intelligence, researchers are keen to solve problems related to human action recognition and classification. We propose a novel method using Deep learning (DL) algorithm for the task of human action recognition. the suggested framework is trained and evaluated on a publically available database containing recorded movements performed by both male and female participants. We tested various DL architectures and their parameters by changing epochs, learning rates, batch size, and optimizers before reaching the final architecture. the optimal architecture consists is trained on 6 epochs, a mini-batch of 128 on an adam optimizer, and a 0.001 learning rate. the system attained the highest accuracy of 98% on unseen test samples. the results prove the method's robustness and can be deployed for real-time human activity recognition and classification. © 2023 IEEE.

关键词： Patient rehabilitation

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Toward a Recommender System for Planning Montessori Educational Activities 5th

Toward a Recommender System for Planning Montessori Educatio...

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5th international conference on smart learning ecosystems and regional development (SLERD)

作者： Nica, Cristi Olteanu, Alexandru Racec, Emil Univ Politehn Bucuresti Bucharest Romania Devmind Bucharest Romania

ISBN: (纸本)9789811573835;9789811573828

In recent decades, learning methods have evolved, adapted, and reinvented. With these changes, the curriculum has become increasingly complex and there is an opportunity for technology to offer a helping hand in providing superior educational experiences. In this paper, we highlight the need for a recommender system within the Montessori kindergartens while exploring the main techniques of the recommender systems used in large environments such as YouTube, LinkedIn, or Amazon. Our ultimate goal is to obtain a recommender system-similar to an intelligent assistant-that helps teachers in planning learning paths and guides students in making progress.

关键词： Recommender system E-learning Institutional learning Montessori Adaptive learning

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