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

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Optimal Allocation of Soft Open Points on Distribution Power Grid with High Penetration of Renewable Energy to Reduce Energy Loss for One day 7th

Optimal Allocation of Soft Open Points on Distribution Power...

引用

7th International Conference on Green Technology and Sustainable Development

作者： Hai Van Tran Tan Minh Phan Anh Viet Truong Thang Trung Nguyen Trieu Ngoc Ton Ho Chi Minh City Univ Technol & Educ Fac Elect & Elect Engn Ho Chi Minh City Vietnam Ho Chi Minh City Univ Ind & Trade Fac Elect & Elect Engn Ho Chi Minh City 700000 Vietnam Ho Chi Minh City Univ Technol & Educ Fac Elect & Elect Engn Ho Chi Minh City 700000 Vietnam Ton Duc Thang Univ Fac Elect & Elect Engn Ho Chi Minh City 700000 Vietnam Fac Elect & Elect Engn Thu Duc Coll Technol Ho Chi Minh City 700000 Vietnam

ISBN: (纸本)9783031762314;9783031762321

In the power system (PS), power loss (PL) accounts for 13% of the total power generation. So, reducing PL is a crucial matter that many researchers and power companies are interested in. This study focuses on optimizing the placement and size of soft open points (SOPs) in the IEEE 33-node distribution network (DN) to minimize power and energy losses with three cases: Case 1) Optimal allocation of SOPs in the original DN;Case 2) Optimal allocation of SOPs in the DN with high penetration levels of one wind turbine generator (WT), and two photovoltaic generators (PVs);Case 3) Inherits the results from Case 2 and optimizes the operation of SOPs over one day when load demand (LD), WT, and two PVs changed by the time. The research proposes the Equilibrium Optimizer (EO), which has been proven to be more effective than the War Strategy Optimization Algorithm(WSOA) in determining the optimal size and location of SOPs to reduce power loss. In Case 1 and Case 2, the active power loss was 210.9983 kW before installing SOPs. After placing SOPs, the power loss decreased below this value. Especially with optimal operation of the SOPs device throughout one day in Case 3, System 2 has significantly decreased energy losses compared to the Original system (OS) and System 1. Therefore, using SOPs can reduce power and energy losses in the distribution grid.

关键词： Soft open points (SOPs) Equilibrium Optimizer (EO) power loss (PL) voltage profile (VP) distribution network (DN)

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Image-Based Body Shape Estimation to Detect Malnutrition

Image-Based Body Shape Estimation to Detect Malnutrition

引用

Intelligent systems Conference (IntelliSys)

作者： MohammedKhan, Hezha Guven, Cicek Balvert, Marleen Postma, Eric Tilburg Univ Tilburg Sch Econ & Management Zero Hunger Lab Tilburg Netherlands Tilburg Univ Tilburg Sch Human & Digital Sci Cognit Sci & AI Tilburg Netherlands

ISBN: (纸本)9783031477232;9783031477249

The detection of malnutrition in children contributes to the United Nations' second Sustainable Development Goal (SDG2): Zero Hunger. One of SDG2's indicators is the prevalence of malnutrition among children under the age of five. Certain body measures such as stature (height) and head circumference are typically used to assess growth and malnutrition in children. In this paper we examine the feasibility of using convolutional neural networks (CNNs) to infer body shape directly from images. We aim to (i) predict three body measurements: height, head circumference and waist circumference, and, (ii) using a parameterised body model, predict the body-shape parameters from images. We created a multi-view collection of images of human bodies based on the CAESAR and AGORA datasets. Our predictions of the three body measurements are competitive with those obtained in a recent study for stature and head circumference, but not for waist circumference. Our predictions of the body-shape parameters, yields reasonable estimates of the body shape parameters, that seem to be hampered by pose and size variations. Our findings lead us to conclude that imagebased assessment of body shape seems feasible. Further work is needed to assess the potential of parameterised body models and the generalisation to in-the-wild assessment of child malnourishment.

关键词： Digital detection of malnutrition Image based body shape estimation Convolutional neural networks AI and society

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Simulation of the Lubrication of High-Speed Jet-Lubricated Gears: Study of the Impact of the Oil Droplet Suspension on the Power Losses 1

引用

3rd International Symposium on Industrial Engineering and Automation

作者： Concli, Franco Della Torre, Augusto Free Univ Bolzano Bozen Fac Engn I-39100 Bolzano Italy Politecn Milan Fac Energy Via Lambruschini 4 I-20156 Milan Italy

ISBN: (数字)9783031704628

ISBN: (纸本)9783031704611;9783031704628

With the rising power density and the need for increasingly reliable mechanical geared transmissions, lubrication has become as a primary design focus. An efficient optimization of lubricant supply involves not just minimizing power losses and enhancing system efficiency but also lowering operating temperatures and improving overall reliability. This paper aims at presenting two Finite Volume Eulerian compressible multi-phase approaches developed in the open-source environment OpenFOAM((R)) for the simulation of the windage power losses of a jet-lubricated spur gear pair operating at high speed. The numerical results have been compared with experimental measurements performed by the Ohio State University on a back-to-back test rig under different operating conditions. The analysis has underlined the fundamental role of the droplet concentrations (oil suspension) in the generation of windage power losses.

关键词： Gears Windage Churning Power Losses Jet-Lubrication

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Galactostack: A 3-In-1 Stack Game for Tackling Social Media Addiction in Children Post-pandemic 8th

Galactostack: A 3-In-1 Stack Game for Tackling Social Media ...

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Mudlapur, Vaishnavi Kumar, Tarun PES Univ Bangalore 560085 India Indian Inst Sci Bangalore India

ISBN: (纸本)9789819713288;9789819713295

After the global coronavirus pandemic, children are using social media a lot more than usual, and this worries parents because it might not be good for their minds, feelings, and bodies. 'Galactostack' is a novel game that attempts to reduce this addiction by employing interactive elements and gamification. Instead of children spending too much time on social media, they can play this game which is fun and educational. The game combines three unique parts: a game to play, things to learn, and elements to make them feel better. The idea is to keep them engaged and happy, so they do not use social media and reduce screen time. This study discusses the core concepts of the game, its features, and how it could positively impact children's online behaviour, reactions and emotions. User evaluation and feedback show positive results: children became more aware and felt more engaged after playing the game. In the post-pandemic era, this design approach offers an innovative and practical way to reduce the adverse impacts of social media addiction. It helps children build healthier connections with technology and the people in their lives.

关键词： Social media addiction Gamification Post-pandemic Mental health Design Interactive learning

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Power Consumption in HPC-AI systems 6th

Power Consumption in HPC-AI Systems

引用

6th International Conference on Cloud Computing and Artificial Intelligence-Technologies and Applications

作者： Nana, Roblex T. Tadonki, Claude Dokladal, Petr Mesri, Youssef Mines Paris PSL Ctr Rech Informat CRI Fontainebleau France Mines Paris PSL Ctr Morphol Math CMM Fontainebleau France Mines Paris PSL Ctr Mise Forme Mat CEMEF Sophia Antipolis France

ISBN: (纸本)9783031786976;9783031786983

Beside the need for speed that has led to HPC, energy has become a crucial concern that is addressed in HPC hardware and software solutions. There are several aspects when it comes to energy in computing systems: cost, source, heat, carbon, lifetime, and more. From the standpoint of embedded systems, devices are battery-powered, thus the available amount of energy to proceed with is limited. In critical cases like these, it is vital to optimize all sources of substantial power consumption. Regarding more standard computing systems, including supercomputers, the question of energy saving mainly translates into electricity cost and carbon emission. Indeed, the overall energy required to run an HPC infrastructure including cooling systems represents an important part of the maintenance budget. In addition, considering heat dissipation, lifetime of the hardware is reduced as well as MTBF (mean time between failures). One the major topic from the application standpoint that HPC has to consider carefully is artificial intelligence (AI). Indeed, this processing paradigm has tremendously grew up with more and more ambitious perspectives. The pervasiveness of AI solutions and the noticeable computing time required for at least the training phases exacerbate the concern of power consumption in this context. The purpose of this chapter is to explore and illustrate the issue of power consumption in HPC-AI systems so as to make the issue more clear to the reader and highlight the main solutions and perspectives.

关键词： HPC AI energy power consumption carbon footprint

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Study of Digital Maturity Models Considering the European Digital Innovation Hubs Guidelines: A Critical Overview 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Babo, Daniel Pereira, Carla Carneiro, Davide Inst Politecn Porto ESTG CIICESI Rua Curral P-4610156 Margaride Felgueiras Portugal Inst Politecn Porto ESTG INESCTEC Rua Curral P-4610156 Margaride Felgueiras Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

Nowadays the concept of digitalization and Industry 4.0 is more and more important, and organizations must improve and adapt their processes and systems in order to keep up to date with the latest paradigm. In this context, there are multiple developed Maturity Models (MMs) to help companies on the processes of evaluating their digital maturity and defining a roadmap to achieve their full potential. However, this is a subject in constant evolution and most of the available MMs don't fill all the needs that a company might have in its transformation process. Thus, European Digital Innovation Hubs (EDIH) arose to support companies on the process of responding to digital challenges and becoming more competitive. Supported by the European Commission and the Digital Transformation Accelerator, they use tools to measure the digital maturity progress of their customers. This paper analyzes several MMs publicly available and compares them to the guidelines provided to the EDIH.

关键词： Maturity Model Digital Maturity European Digital Innovation Hub (EDIH)

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Gamification in Higher Education Assessment Through Kahoot 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Salazar-Vallejo, Geovanna Rivera-Rogel, Diana Univ Tecn Particular Loja Fac Social Sci Educ & Humanities CP 11-01-608 Loja Ecuador

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The approach of gamified assessments has significant implications in student learning and encourages educators to develop dynamic learning environments with permanent feedback, establishing a formative context that, through dynamic techniques, evaluates the content taught and measures the progress of learning. Responding to this background, the present research determines through a quantitative methodology, the potential of Kahoot in the university evaluation of Clinical Psychology students of the Universidad Tecnica Particular de Loja (UTPL) and establishes a comparison between their average bimonthly evaluation score on the platform and the bimonthly written exam developed in the classroom. It is concluded that students improve their learning with the use of the Kahoot platform, presenting high levels of success in the topics raised throughout the academic course, which demonstrates its feasibility to reinforce the academic results obtained and process knowledge during professional training. In addition, it was established that the use of Kahoot is feasible in preparing students for a final written evaluation.

关键词： Education Gamification Evaluation

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Edge AI on Constrained IoT Devices: Quantization Strategies for Model Optimization

Edge AI on Constrained IoT Devices: Quantization Strategies ...

引用

Intelligent systems Conference

作者： Shabir, Muhammad Yasir Torta, Gianluca Damiani, Ferruccio Univ Torino Dept Comp Sci Cso Svizzera 185 I-10149 Turin Italy Univ Kotli AJ&K Kotli Pakistan

ISBN: (纸本)9783031664274;9783031664281

In the field of deep learning (DL), the deployment of complex Neural networks (NN) models on memory-constrained devices presents a significant challenge. TinyML focuses on optimizing DL models for such environments, where computational and storage resources are limited. The main key aspect of this optimization involves reducing the size of the models without compromising their performance too much. We have investigated the efficacy of various quantization techniques in optimizing DL models for deployment on memory-constrained devices. To understand the challenges of memory requirements of standard deep learning models, we conducted comprehensive literature reviews and identified quantization methods as a potent approach for model size reduction. Our study targets popular NN architectures such as ResNetV1 and V2, MobileNetV1 and V2, and introduces a custom-designed model, examining their suitability to TinyML constraints. We have analyzed CIFAR10 and MNIST datasets to assess the impact of four distinct quantization techniques on model size and accuracy. These techniques include Dynamic Range Quantization, Full Integer Quantization, Float16 Quantization, and Integer 16x8 Quantization. Our aim is to contribute valuable insights into model optimization for efficient deployment in resourcelimited environments.

关键词： Quantization Optimization Deep learning Memory constrained devices Machine learning AI

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How Variables Graphs May Help to Correct Erroneous MAS Specifications

How Variables Graphs May Help to Correct Erroneous MAS Speci...

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Intelligent systems Conference (IntelliSys)

作者： Mermet, Bruno Simon, Gaele CNRS GREYC UMR 6072 Caen France Univ Le Havre Caen France

ISBN: (纸本)9783031477171;9783031477188

This paper is situated in the context of multi-agent systems validation using theorem proving techniques. This document presents a preliminary case study, which is a part of a broader investigation aiming to explore whether such techniques could aid developers in detecting and characterizing errors in MAS specifications. Indeed, regardless of the verification system used (model checking or theorem proving), understanding the reason of a failure in order to correct the specification is most of the time rather difficult. In this article, we propose a method that may help in this task. This method relies on the variables (and their dependencies) that appear in proof obligations generated by GDT4MAS, a specification and verification method dedicated to Multi-Agent systems. Graphs generated thanks to dependencies between variables occurring in an unproved theorem may indeed help to identify certain types of mistakes, giving a way to correct the specification.

关键词： Multi-agent systems Proof failure Debugging

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Prognosis of Dengue Incidences in India Using LSTM with Multivariate Data 4th

Prognosis of Dengue Incidences in India Using LSTM with Mult...

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4th Congress on Intelligent systems (CIS)

作者： Sharma, Shruti Gupta, Yogesh Kumar Banasthali Vidhyapith Dept Comp Sci Jaipur Rajasthan India SVKMs NMIMS Indore STME Indore India

ISBN: (纸本)9789819990399;9789819990405

Monitoring climatic change and its impacts unique to the disease is required for predicting the expansion of dengue. One of the infectious diseases transmitted by vectors with the fastest rate of transmission is dengue. In this study, we have proposed a forecasting model for the prediction of dengue cases by considering the climatic variables for all the states of India for last 12 years. For our study, we have accumulated data with factors like temperature (minimum and maximum), relative humidity, mean wind speed, dengue cases and deaths. For the prediction, the different models ANN, RNN, LSTM, Stacked LSTM, BiLSTM for forecasting time series prediction are implemented and then compared. During our study, it is found that humidity and maximum temperature have a strong correlation with the number of dengue cases. BiLSTM model outperformed all other deep learning model with an accuracy of 98.91%. This study will assist the healthcare practitioners to take informed decisions beforehand.

关键词： Machine learning Forecasting Dengue disease Epidemic disease outbreak Time series

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