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

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Use of Analytical Methods in Variant Forecasting Tasks 9th

Use of Analytical Methods in Variant Forecasting Tasks

引用

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

作者： Kukartsev, V. V. Borodulin, A. S. Zamolotskii, S. A. Nelyub, V. A. Glinscaya, A. R. Bauman Moscow State Tech Univ Moscow 105005 Russia Siberian Fed Univ Krasnoyarsk 660041 Russia Reshetnev Siberian State Univ Sci & Technol Krasnoyarsk 660037 Russia

ISBN: (纸本)9789819732883;9789819732890

The article presents an overview of modern data analytics methods and techniques used in forecasting tasks and considers key aspects of using data analytics in the context of the hospitality industry. The hospitality industry is particularly dependent on accurate forecasts, as effective management of occupancy, pricing, and guest service is critical to the successful operation of hotels. The application of data analytic techniques to forecast various phenomena and events and to assess the quality of forecasts is emphasized. The application of such techniques can reduce costs, increase revenue, and improve overall guest satisfaction.

关键词： Labor market Socio-economic development Sustainable economic development Economy Society

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Impact of Police Communication Channels on the Police and the Suburban and Rural Community During the COVID-19 Pandemic 1

引用

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

作者： Radic, Ivana Minist Interior Pozesko Slavonska Cty Police Adm Pozega Croatia

ISBN: (数字)9789819735624

ISBN: (纸本)9789819735617;9789819735624

The COVID-19 pandemic has changed how the police work in various segments, including the communication between the police and the communities they serve. Still, there is a lack of scientifically verified knowledge on the effects of these changes that could be applied in future crises. This study aims to investigate the impact of the police use of live and virtual communication channels during the COVID-19 pandemic on the institution (which is measured through police procedural correctness) as well as on the suburban and rural community (which is measured through police legitimacy). Quantitative research using a voluntary and anonymous survey method was conducted on a sample of 367 police officers from two police departments in Croatia, which cover predominantly suburban and rural areas. The results of the Jonckheere-Terpstra trend test and the non-parametric (Spearman) correlation test showed that police officers who intensified remote communication with citizens during the pandemic perceived an improvement in the legitimacy of the police in the community, while those who continued to communicate in person did not perceive such changes. However, live communication was unrelated to public respect for the police and the public's trust in the police, while remote communication was related to these variables, albeit relatively weakly. Given that the main limitation of this research is that the sample consisted of police officers only and not citizens, future research should include citizens to obtain their perceptions of police communication not just during but also after the COVID-19 pandemic. Thus, the practical implications of this research related to the necessity of digital communication of the police in crises will gain additional support.

关键词： Police COVID-19 pandemic Communication channels Police procedural correctness Police legitimacy

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Dynamics of Sea-Level Pressure and Wind Velocity: A Study of Volatility at Airports Using Statistical Time-Series Analysis

Dynamics of Sea-Level Pressure and Wind Velocity: A Study of...

引用

Intelligent systems Conference

作者： Scott, Darren Chhabria, Viren Ahmad, Khurshid Trinity Coll Dublin Sch Comp Sci Dublin 2 Ireland Technol Univ Dublin City Campus Dublin Ireland

ISBN: (纸本)9783031664304;9783031664311

The constant increase in the number of flights across the world means that aircraft safety today has become an even greater priority. Sudden changes in weather within the earth's boundary layer, for example wind shear create many risks for take-offs and landings. The key wind variables here are sea-level pressure (SLP), wind speed (w(s)) and wind direction (w(d)), together with humidity and air temperature: it is the change in the values of these variables that can cause wind shear and subsequent turbulence. The literature on wind shear deals with the values of these variables: these values are highly correlated and can introduce the so-called level effect. Usually, the logarithm of the ratio of two successive values of a variable, also called the return, is used in time-series analysis. Returns behave like a random variable which is ideal for statistical analysis. The use of changes or returns of w(s), and w(d), and SLP, for investigating the onset and duration of wind shear is explored in this paper. This use of returns of a variable, rather than the variable itself, is a methodological point and distinguishes our work from that of others. Returns behave like a random variable but in rapidly changing situations they appear to cluster, leading to system-wide instability or volatility. We report on the statistical properties of the returns for wind speed and direction, and sea-level pressure, at three airports using a time series over a seven-year period (2016-2023). As it is the clustering that signifies volatility in weather patterns, we investigate two methods of estimating the clustering: first, model-free estimates of volatility based on squared returns, and second, model-based estimates, like GARCH, that use returns.

关键词： Log return Low-level wind shear Statistical time-series analysis High-frequency data Volatility Air-traffic monitoring and control Stylistic facts Conditional variance Heteroskedastic models GARCH models

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Research Towards an Optimal Method of Modeling and Regulating a Cement Mill Using AI Algorithms 28th

Research Towards an Optimal Method of Modeling and Regulatin...

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2024 International Conference Automation

作者： Pawus, Dawid Paszkiel, Szczepan Opole Univ Technol Fac Elect Engn Automat Control & Informat Proszkowska St 76 PL-45758 Opole Poland

ISBN: (纸本)9783031782657;9783031782664

This research explores the optimization of modeling and control strategies for a cement mill using advanced Artificial Intelligence (AI) techniques. Neural Nonlinear AutoRegressive with eXogenous input (NNARX) models are employed to capture the nonlinear, multivariable dynamics of the cement grinding process. The Levenberg-Marquardt algorithm demonstrated superior training performance, achieving high accuracy in predicting key process parameters like inlet chamber fill and main drive current. The study also presents a neural control approach based on inverse modeling, enabling precise input predictions to maintain desired output conditions, stabilizing product quality and minimizing energy usage. Comparisons of neural network configurations suggest that simpler models are effective, with only slight benefits from more complex networks.

关键词： non-linear models artificial neural networks expert system NARX comparative study cement mill process control practical approach

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Zero-Emission Heavy-Duty Trucks in Logistics: A Systematic Review and Analysis of Relevant Adoption Parameters 1

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3rd International Symposium on Industrial Engineering and Automation

作者： Roman, Giacomo Zadek, Hartmut Otto Von Guericke Univ Univ Pl 2 D-39106 Magdeburg Germany

ISBN: (数字)9783031704659

ISBN: (纸本)9783031704642;9783031704659

This study examines the challenges and potential solutions associated with the adoption of Zero-Emission Heavy-Duty Trucks in the automobile logistics sector in Europe. A comprehensive systematic literature review was conducted using a forward and backward research methodology to identify relevant parameters in the adoption process of Battery Electric Trucks and Hydrogen Fuel-Cell Electric Trucks. The analysis reveals a complex set of technological, operational, and infrastructural factors that currently affect the widespread implementation of Zero-Emission Heavy-Duty Trucks. Based on a structured, adapted PESTEL framework, which takes into account operational factors, a descriptive analysis categorizing these factors is presented. In addition, expert interviews were conducted to validate and enrich the completeness of the analysis and to attribute an importance scale to the different parameters. Through this approach, the paper improves the decision-making process in the adoption phase of Zero-Emission Heavy-Duty Trucks by ensuring that no essential aspect is overlooked. This research contributes to the existing body of knowledge by presenting a comprehensive overview, providing clarity and transparency on the state-of-the-art in Zero-Emission Heavy-Duty Trucks adoption to assist researchers and practitioners in further endeavors. This information is then used to derive strategic measures addressed to stakeholders for exploiting the benefits of such vehicles and for conducting further applied research aimed at improving the adoption potential of these technologies throughout the industry.

关键词： Heavy-duty trucks Electric vehicles Sustainable transport logistics Decarbonization Road freight transport

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Skill Awareness Framework for Learning Design - Re-focusing Experiential Learning Towards Skills that Matter Most in Times of GenAI 14th

Skill Awareness Framework for Learning Design - Re-focusing ...

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14th International Conference on Learning Factories (CLF)

作者： Nelles, Jochen Mueller, Fabian Alexander Ramnane, Kiran Blackwell, Erin Atre, Mandar P. De Guzman, Chris Lacopeta, Cinzia Bingen, Sarah Hammer, Markus McKinsey & Co Inc Kennedydamm 24 D-40027 Dusseldorf Germany

ISBN: (纸本)9783031653995;9783031654008

The authors introduce a Skills Awareness Framework for Learning Design (SAFLD) to provide guiding principles for learning. Corporate learning is in a state of flux due to disruptive influences such as COVID-19 and the digitalization of the world of work, even into the home office. In the age of generative AI where knowledge is seemingly available at the touch of a button, corporate learning is more than ever challenged to re-focus on teaching critical and relevant skills. Therefore, in the sense of self-reflection, it will be discussed that learning in the moment will still need to be complemented by experiences that change behaviors. These include both cognitive and motor skills and are based on inter- and intra-action of learners and trainers both individually and as a team. When it comes to re-focusing experiential learning towards skills that matter most, learning factories, e.g., the Innovation and Learning Centers or Model-Factories-in-a-Box, play an even more important role than ever before. This hypothesis is supported by Bloom's taxonomy which classifies learning objectives and illustrates that some skills or higher proficiency levels of skills might be acquired by digital, self-paced e-learning or by virtual, instructor-led learning sessions, whereas other skills or higher proficiency levels of skills and deep learning that change behavior might be better acquired by experiential learning. Finally, learning factories can also play a role in bringing the emerging GenAI to life in an application-oriented environment such as a shop floor.

关键词： Skill Awareness Framework for Learning Design Experiential Learning Capability Building Learning Factories Skills

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Haptic Field and Force Feedback Generation for Wheeled Vehicle Teleoperation on 2.5D Environments 1

引用

18th International Conference on Intelligent Autonomous systems (IAS)

作者： Kim, Yongjun Kim, Donghyeon Ryu, Jee-Hwan Korea Adv Inst Sci & Technol Dept Civil & Environm Engn Daejeon 34141 South Korea Korea Adv Inst Sci & Technol Robot Program Daejeon 34141 South Korea

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

Path drawing in a complex 2.5D environment in mobile robot navigation can be challenging, significantly when a horizon-parallel camera orientation hampers distance perception. This paper presents an innovative method of addressing this issue by creating a haptic field to provide remote operators with tactile feedback about the environment, enhancing their spatial awareness. Although rendering haptic feedback with point cloud data (PCD) from LiDAR is typically used, it is harsh to deliver dense data due to the bandwidth limitations of the remote networks. This paper proposes a method for creating a haptic field that compresses only the information necessary to distinguish the surrounding environment from primitive PCD and deliver it to the remote operator. The process for rendering continuous haptic feedback from low-resolution haptic fields is also proposed. In the experiment that provided repulsive feedback for obstacles and the bumpy extent of the road surface, the haptic feedback shows that the remote controller helped draw a path similar to the one directly controlled in the field.

关键词： Mobile robot Haptic augmented teleoperation Haptic Feedback

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An Unsupervised Deep Learning Model for Aspect Retrieving Using Transformer Encoder

An Unsupervised Deep Learning Model for Aspect Retrieving Us...

引用

Computing Conference

作者： Dey, Atanu Jenamani, Mamata De, Arijit Indian Inst Technol Kharagpur Kharagpur India Univ Manchester Manchester England

ISBN: (纸本)9783031622793;9783031622779;9783031622762

We introduce a deep-learning-based aspect extraction model called RATE, which stands for Retrieving of Aspects using Transformer Encoder. When doing unsupervised aspect-based sentiment analysis, the process of retrieving aspects is both critical and challenging. Most prior efforts use some kind of topic modeling to extract aspect only. Despite their efficacy, these techniques seldom provide consistent outcomes for highly coherent aspects. Even though some approaches address these issues by employing an attention-based deep neural model, their performance is hindered by their single-headed attention mechanism. Thus, RATE is designed to improve the performance of extracting coherent aspects from the text by using multi-headed attention mechanism with transformer encoder, negative samplings, and word embeddings. This model promotes the proximity in the embedding space of words that arise in similar contexts, as opposed to topic models and other techniques that often presume independently created words. To further enhance the coherence of the aspects, we use multi-headed attention technique in the encoder of the RATE architecture to downplay unimportant words during training. The RATE model outperforms the highest performing unsupervised baseline ones in terms of precision (8.34%), recall (0.94%), and f1-score (5.44%) on the ACOS-Laptop dataset. Again, on the ACOS-Restaurant dataset, RATE enhances precision, recall, and f1-score by 1.4%, 8.87%, and 4.31%, respectively, for finding more significant and coherent aspects.

关键词： Aspect extraction Word embedding Attention mechanism Transformer Encoder Unsupervised deep neural network

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Data Obfuscation Scenarios for Batch ELM in Federated Learning Applications 21st

Data Obfuscation Scenarios for Batch ELM in Federated Learni...

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

作者： Akusok, Anton Espinosa-Leal, Leonardo Atsemegiorgis, Tamirat Bjork, Kaj-Mikael Arcada Univ Appl Sci Grad Sch & Res Jan Magnus Janssons Pl 1 Helsinki 00560 Finland

ISBN: (纸本)9783031619045;9783031619052

The batch formulation of the Extreme Learning Machines (ELM) method fits well with federated learning scenarios. This paper proposes and investigates the strategies for data obfuscation that can be used in combination with ELM to create a secure distributed learning environment. Results show that the model allows for significant levels of added noise with minimal impact on its predictive performance;enabling secure federated learning in tasks that can benefit from it.

关键词： Extreme Learning Machine Federated learning Batch processing

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Accessibility of Online Educational and Scientific Resources 1

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Computing Conference

作者： Todorov, Todor St Cyril & St Methodius Univ Veliko Tarnovo Fac Math & Informat Veliko Tarnovo Bulgaria Bulgarian Acad Sci Inst Math & Informat Sofia Bulgaria

ISBN: (数字)9783031622731

ISBN: (纸本)9783031622755;9783031622731;9783031622724

The paper investigates methods for creation of digitally accessible resources for people with visual impairments. Tools and approaches for automation accessibility testing of web systems are presented. All the developed methodology is applied on university information systems for scientific and educational resources management. Main functionalities of the systems are presented. Test scores of their accessibility to scientists and students with visual disabilities are discussed before and after the process of improvement. All the accessibility problems found are listed and solutions are proposed.

关键词： Accessibility testing Accessibility improvement Education Science

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