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Data-Driven Mobility and Transport Planning in Municipalities: Smart Solutions for Limited Resources 21st

Data-Driven Mobility and Transport Planning in Municipalitie...

引用

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

作者： Hoehne, Erik Teich, Tobias Scharf, Oliver Leonhardt, Sven Schlachte, Maximilian Trommer, Martin Mewes, Christoph Kraus, Manoel Bergelt, Susan Queck-Haenel, Silvia City Zwickau Hauptmarkt 1 D-08056 Zwickau Germany Univ Appl Sci Zwickau Kornmarkt 1 D-08056 Zwickau Germany

ISBN: (纸本)9783031619045;9783031619052

The research paper highlights the importance of data-driven approaches in urban and mobility development for local communities. Tailor-made solutions, based on a precise understanding of local challenges, are essential, especially for smaller or financially weaker municipalities. Implementing a data-gathering infrastructure, particularly within Smart City concepts, often presents challenges due to limited technical and financial resources, as well as a lack of expertise. To address these issues, a video-based traffic detector was developed to enable flexible and minimally invasive traffic measurement. This technology differs from traditional AI models through its miniaturization and application to less powerful embedded systems. The 'Machine Learning on the edge' approach was tested in Zwickau, Saxony, Germany, where its robustness and reliability were confirmed by comparison with manual traffic counts. The field study demonstrated that reliable data collection is possible even with minimal technical resources. This contrasts with traditional traffic detection technologies, which rely on induction loops and compute-intensive systems. The novel approach offers a cost-efficient alternative, particularly suitable for minor townships with limited fiscal capacity. The study's conclusions recommend promoting data-based approaches in municipal planning, investing in cost-effective technologies like video-based traffic detectors, emphasizing scalability and adaptability, and continuously monitoring and improving data solutions. This enables the implementation of Smart City concepts even in financially challenged municipalities, contributing to the improvement of local quality of life.

关键词： Tiny Machine Learning video-based detection AI model

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Robust Fuzzy Control for Intelligent Pneumatic Vibration Isolation

Robust Fuzzy Control for Intelligent Pneumatic Vibration Iso...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Liu, Xiaoxia Xu, Shaofeng Liu, Bao Wang, Jili Wang, Yixuan Sun, Zhibo Shi, Yan Beihang Univ Beijing 100191 Peoples R China Zhejiang Easun Pneumat Sci & Technol Co Ningbo Peoples R China

ISBN: (纸本)9783031671913;9783031671920

Pneumatic vibration isolation is a critical system for maintaining a clean, micro-vibratory work environment for precision instruments and semiconductor manufacturing. Passive pneumatic isolation cannot meet the demand for low-frequency vibration isolation and even produces resonance phenomenon. In this study, an active pneumatic vibration isolator was developed to suppress the interference of low-frequency vibration using an intelligent control method. Firstly, the working model of linearization at the working point of the system is established. Then, based on the robust H-infinity control theory, a controller capable of suppressing low-frequency vibration perturbations with high robustness is designed, and a serial double-loop control method is adopted to realize the vibration isolation effect while increasing the bandwidth of the system. Finally, an excitation signal of 1-10 Hz is applied to test the performance of the pneumatic vibration isolation system in the case of intelligent control and compare it with the passive vibration isolation effect. The experimental results unambiguously demonstrate that the active control method enhances vibration isolation performance in the low-frequency range, effectively mitigating resonance peaks associated with the passive isolator.

关键词： Pneumatic vibration isolation Intelligent control Frequency shaping

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Monkeypox Lesion and Rash Stage Classification Using Deep Learning Technique 1

引用

20th International Conference on Computing and Information Technology (IC2IT2)

作者： Chunhapran, Orawan Maliyeam, Maleerat Quirchmayr, Gerald King Mongkuts Univ Technol North Bangkok Fac Informat Technol & Digital Innovat Bangkok Thailand Univ Vienna Vienna Austria

ISBN: (数字)9783031585616

ISBN: (纸本)9783031585609;9783031585616

Timely identification of Monkey pox symptoms stands as a key goal in averting a global pandemic. Furthermore, accurately assessing the disease stage and duration of Monkeypox rashes is imperative. The utilization of deep learning algorithms has become increasingly popular for the efficient diagnosis of diseases through medical imaging. In this research, the classification of Monkeypox lesions and rash stages is suggested through the application of deep learning techniques. The dataset comprises pictures of skin lesions and different stages of rashes. In the experiment, data augmentation methods were utilized to augment the sample size in both the training and testing sets. By employing a MobileNetV2 model, the outcome demonstrated an accuracy of 90.68% for pox and 90.62% for the pox rash stage. This approach aids healthcare professionals in crafting precise treatments tailored to the unique disease stage, offering accurate recommendations based on early-stage rash characteristics for each patient. Furthermore, it improves overall life expectancy by enabling more effective treatment strategies.

关键词： Monkeypox Rash Stage Deep Learning Techniques CNN

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Gender and Use of Digital Banking Products in Cameroon: Is There a Gap? 1

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

作者： Kamdjoug, Jean Robert Kala Teutio, Arielle Ornela Ndassi Tchuente, Diane Ngate ESSCA Sch Management 1 Rue Joseph Lakanal F-49003 Angers France Catholic Univ Cent Africa Fac Social Sci & Management GRIAGES Yaounde 11628 Cameroon

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The development of new technologies is putting more pressure on banks to offer digital solutions to their customers. This issue is even more significant in developing countries where digital investments are growing. In this study, we examine whether the gender digital divide persists in emerging banking environments such as Cameroon, where the digitalization of services is becoming a focal point of marketing strategy. We analyze the gender gap in the influence of perceived ease of use, social influence, perceived security, and perceived trust on the use of digital banking products, as well as the influence of this use on bank notoriety. The partial least square structural equation modeling (PLS-SEM) method is used to test a sample of 347 bank customers, including 221 men and 126 women. The results show that the positive influence of perceived ease of use and social influence on the use of digital banking products is more vital for women than men. Further, the influence of perceived trust is more significant for men than women. There is no gender gap in the influence of perceived security, as well as the impact of the use of digital banking products on bank notoriety. The results also show that women are more open to adopting digital banking products (R-2 = 49.5%) than men (R-2 = 43%).

关键词： Gender gap digital transformation banking products developing countries

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Influence of Community-Based and Service-Learning Initiatives on Learners' Engagement in Promoting Sustainable Development 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Kumar, Deepak Joseph, Shaji Mukherjee, Niladri Symbiosis Int Symbiosis Ctr Informat Technol Pune Maharashtra India

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Community-based and service-learning have now emerged as powerful means for fostering sustainable development. Community-based service-learning programs are considered a practical means of advancing sustainable development. This paper examines the influence of these programs on students' participation in accomplishing Sustainable Development Goals (SDGs) 4 (Quality Education) and 11 (Sustainable Cities and Communities). We tried to adopt an Empirical based Model approach to study the influence of community (Community-Based Learning) and service-based learning projects on student participation in sustainable development initiatives. The research aims to identify the benefits of community-based learning (CBL) and its current limitations in fostering sustainable development. We collected data from students in colleges and universities to shed light on their involvement in CBL activities and how their peers' participation influences their engagement. Students recognize the importance of individual action and learning from peers in promoting sustainable development. Institutions should include service-learning programs to enhance education quality and prompt curriculum redesign to include practical experiences related to SDGs.

关键词： Community-based learning service-based learning Sustainable development goals socio cognitive theory

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Fire Spalling of Concrete 10th

Fire Spalling of Concrete

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Bidzevic, Irfan Dzidic, Sanin Int Burch Univ Fac Engn Nat & Med Sci Sarajevo 71000 Bosnia & Herceg Univ Bihac Tech Fac Dept Civil Engn Irfana Ljubijankica Bb Bihac 77000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

Concrete structures can be compromised by various factors, including fires. However, reinforcement exposure to fire can jeopardize the structural integrity of concrete structures. Such exposure significantly impacts both the load-bearing capacity and serviceability of the structure. Fire spalling, a phenomenon caused by increased temperature or fire, leads to complex microstructural changes in concrete. When concrete is subjected to fire, it undergoes intricate microstructural changes. Above 300 degrees C, a significant amount of strength is lost, and structural capabilities are substantially compromised. The severity of fire spalling increases with the application of high strength and self-compacting concrete. Moisture, present in volatile and chemically combined forms, plays a crucial role in concrete spalling. Researchers have recognized that the underlying causative mechanisms of spalling are largely unique to concrete. Non-explosive spalling may occur after heating for 60 min or more, which can be mitigated through additional strengthening in the concrete member. While spalling does not imply structural failure, it does impact the overall fire resistance of the element. Therefore, it is essential to follow appropriate safety measures to enhance the fire performance of concrete structures.

关键词： concrete spalling fire temperature moisture

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Role Adaptation of Human-Robot Physical Interaction Based on the Distribution of Learned Belief 1

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Lu, Weifeng Zhao, Longfei Hu, Zhe Pan, Jia City Univ Hong Kong Hong Kong 999077 Peoples R China Tencent Robot X Shenzhen 518100 Peoples R China Univ Hong Kong Hong Kong 999077 Peoples R China

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

Physical human-robot interaction (pHRI) poses great challenges to the role adaptation between the human and the robot in real time. The robot has several individual tasks attainable, while the human might switch between tasks unpredictably. The capability to estimate the confidence of the expected task is critical to empower the robot to behave properly in cooperation. In this paper, we construct a pHRI controller framework with real-time role adaptation. With the task beliefs learned by a belief estimation module, we mathematically analyze the task confusion index of the robot during its motion. The role adaptation module authorizes the robot to take proactive actions if the confusion index is minor, and vice versa. We deploy a reinforcement learning method on generating the robot assisting force. The proposed pHRI controller framework is validated in both simulation and experiment. More results and videos are available at https://***/view/hrpcrl/.

关键词： Human-robot physical interaction Role adaptation Reinforcement learning

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Advanced Demand Forecasting and Pricing in Moroccan Auto Industry: A CNN-LSTM-Attention and Reinforcement Learning Approach 4th

Advanced Demand Forecasting and Pricing in Moroccan Auto Ind...

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

作者： Amellal, Asmae Amellal, Issam Ech-charrat, Mohammed Rida Abdelmalek Essaadi Univ ENSA Tetouan Tetouan Morocco Hassan 1st Univ ENSA Berrechid Settat Morocco

ISBN: (纸本)9783031686528;9783031686535

This paper presents a novel forecasting model that combines Convolutional Neural Network-Long Short-Term Memory with an Attention mechanism (CNN-LSTM-Attention) and Reinforcement Learning (RL) to enhance impressive utilization in forecasting accuracy on demand for pricing optimization within auto parts industry in Morocco. The performance of the model was determined using Mean Squared Error (MSE) and R-squared (R-2) as evaluation measures for prediction of demand accuracy while "Average Reward per Episode" was applied to measure how well pricing strategy works. The Application Programming Interface (API) utilized CNN-LSTM parameterization for direct spatial computation from images, Recurrent Neural Network (RNN) like sequential information processing and attended timestamps, which resulted in error rates below 1% while producing an R-2 of around 90%. Regarding those metrics, it outperforms normal LSTMs or convolutional long short-term memory networks. By contrast, empirically Deep Q-Network (DQN) was more compatible than conventional Q-Learning when applied towards evolving pricing strategies over time leading up greater rewards and consistency amidst market volatilities. Market trend response was cores dependable, which resulted in significant readiness in supply chain operations. The present research work gives an example where smart predictive analysis can provide a comparative advantage.

关键词： CNN-LSTM-Attention Reinforcement Learning Demand Forecasting Price Prediction Data-driven Decision making Supply Chain Management

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Designing Reactive Route Change Rules with Human Factors in Mind: A UATM System Perspective 9th

Designing Reactive Route Change Rules with Human Factors in ...

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

作者： Kim, Jeongseok Kim, Kangjin SK Telecom Seoul 04539 South Korea Chodang Univ Dept Drone Syst Muan Jeollanam Do South Korea

ISBN: (纸本)9789819745807;9789819745814

This paper investigates the dynamic rerouting of electric vertical takeoff and landing (eVTOL) aircraft in the context of urban air traffic management (UATM). Focusing on the interaction between human managers and the UATM network, we present a novel approach to reactive rerouting based on step-oriented simulation and condition-action rules. Our framework enables human intervention in response to congestion observed at vertiport corridors, allowing managers to request detours for approaching eVTOLs. We formulate the problem within the knowledge representation and reasoning (KR&R) paradigm and employ a multi-shot approach within an Answer Set Programming (ASP) solver to drive the step-oriented simulation. The structure of the paper follows a logical progression, including related work, preliminaries, a problem statement, proposed solutions, and a discussion, followed by a concluding section.

关键词： UAM UATM KRR Answer Set programming Articulating agent

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Frequency Constraints in Optimization of Structures 10th

Frequency Constraints in Optimization of Structures

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Husak, Ermin Mahmic, Mehmed Univ Bihac Tech Fac Irfana Ljubijankica Bb Bihac 77000 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

In this paper an example of the optimization of a truss with ten bars with frequency constraints is given. The objective function is the minimum mass of the structure and the variables are the cross sections of ten aluminium bars. The analysis of the dynamic behaviour of the structure was done using the finite element method. Optimization methods of nonlinear programming and genetic algorithms are used. The optimizations were done by changing the values of the natural frequency of the structure as constraints, and the results are given in this paper. From the obtained results, the dependence of the change in the value of the frequency constraints and the mass of the structure can be seen.

关键词： structures truss optimization frequency constraints

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