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Transfer of Industry 4.0 Knowledge to SME Employing the Concept of a Learning Factory as a Roadshow 14th

Transfer of Industry 4.0 Knowledge to SME Employing the Conc...

引用

14th International Conference on Learning Factories (CLF)

作者： Prell, Bastian Gunther, Norman Wilbers, Simon van de Sand, Ron Reiff-Stephan, Jorg Univ Appl Sci Wildau Hsch Ring 1 D-15745 Wildau Germany

ISBN: (纸本)9783031653995;9783031654008

This contribution reports on the roadshow, a collection of Industry 4.0 applications operated by the department of smart production of the University of Applied Sciences Wildau. It targets the transfer between the institutions of higher education and small- and medium-sized enterprises but also integrates the transfer between students and university respective industry. The roadshow compiles several use cases for Industry 4.0 applications in a linked production system, arranged around the task of producing awooden 3D puzzle. Thus, the roadshowis a mobile-mounted Learning Factory on a truck that can be transported to various locations, such as company events or fares. Participants can choose from different options of digital support for the respective task at hand. E.g., for the assembly of the 3D puzzle the options consist of a traditional paper-based manual, an interactive assembly guide through Mixed Reality (MR) via Microsoft HoloLens, a voice-controlled laser projection, or a tablet application also using MR. Once all steps are finished, the customised 3D puzzle is handed out to the visitor. Such a setup allows for sensitising participants and building up their acceptance toward the technologies of Industry 4.0. The contribution closes by presenting results achieved so far in terms of lessons learned as well as a first validation of the effectiveness of such a transfer approach considering vital data through a model for technostress.

关键词： Industry 4.0 Knowledge Transfer Mixed Reality Technostress and Learning Vital Data Technology Acceptance

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Human Motion Trajectory Prediction Using the Social Force Model for Real-Time and Low Computational Cost Applications 6th

Human Motion Trajectory Prediction Using the Social Force Mo...

引用

6th Iberian Robotics Conference (Robot)

作者： Gil, Oscar Sanfeliu, Alberto CSIC UPC Inst Robot & Informat Ind Barcelona Spain

ISBN: (纸本)9783031586750;9783031586767

Human motion trajectory prediction is a very important functionality for human-robot collaboration, specifically in accompanying, guiding, or approaching tasks, but also in social robotics, self-driving vehicles, or security systems. In this paper, a novel trajectory prediction model, Social Force Generative Adversarial Network (SoFGAN), is proposed. SoFGAN uses a Generative Adversarial Network (GAN) and Social Force Model (SFM) to generate different plausible people trajectories reducing collisions in a scene. Furthermore, a Conditional Variational Autoencoder (CVAE) module is added to emphasize the destination learning. We show that our method is more accurate in making predictions in UCY or BIWI datasets than most of the current state-of-the-art models and also reduces collisions in comparison to other approaches. Through real-life experiments, we demonstrate that the model can be used in real-time without GPU's to perform good quality predictions with a low computational cost.

关键词： Human Motion Prediction Social Force Model Generative Adversarial Network Conditional Variational Autoencoder

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Using Simulated Data for Deep-Learning Based Real-World Apple Detection 1

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Intelligent systems Conference (IntelliSys)

作者： Hasperhoven, Dylan Aghaei, Maya Dijkstra, Klaas NHL Stenden Univ Appl Sci NL-8917 DD Leeuwarden Netherlands

ISBN: (数字)9783031477249

ISBN: (纸本)9783031477232;9783031477249

Object detection using CNNs requires a large amount of data to achieve decent performance in real-world scenarios. The creation of traditional datasets involves acquiring numerous images and manually annotating them. In this paper, we introduce a method for simulating apple orchards utilizing the Unity 3D engine. We created a tool that uses this simulator to generate fully bounding-box annotated (simulated) datasets. We trained YOLOv5 models of different sizes on simulated data, real-world data, and a combination of both, and later tested the models on a real-world dataset to evaluate the suitability of our generated dataset. Our experiments show that object detection models trained on simulated data can achieve results on real-world images that are very similar to results of models trained solely on real-world data. We demonstrate that simulated data has the potential to eliminate the need for real-world datasets, thus saving a substantial amount of time. In this research, we focused our tests on a real-world dataset acquired under controlled settings, future work can be dedicated to evaluate the generalization ability of models trained on simulated datasets on more challenging real-world datasets.

关键词： Simulated Data Apple Detection Apple Orchards Visual Inspections YOLOv5

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(Re)thinking Teacher Training in the Digital Age: Teacher Training Models for Online Practice 12th

(Re)thinking Teacher Training in the Digital Age: Teacher Tr...

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

作者： Goncalves, Bruno F. Vaz-Rebelo, Piedade Pessoa, Maria Teresa R. Goncalves, Vitor Polytech Inst Braganca Basic Educ Res Ctr Braganca Portugal Univ Coimbra Ctr Interdisciplinary Studies 20th Century Coimbra Portugal

ISBN: (纸本)9783031602238;9783031602245

In recent years, the need to train teachers to teach online has been highlighted, not only because of the exponential growth of technologies in all economic sectors of society, but also because of the very need for education to modernize and, through this, innovate in the digital sphere. The covid-19 pandemic has only demonstrated, now unequivocally, the urgency of teacher training in the field of online teaching, as well as the need for instructional design and evaluation of training models to support learning. It is precisely because of these two assumptions that there is an urgent need to develop research in the area that allows us to (re)think teacher training in the digital age so that teachers can participate in training actions and, through them, acquire fundamental skills for the realization of online teaching. In this sense, through a systematic review of the literature, we sought to identify and characterize training models geared towards teaching practice in online education. In this way, it may be possible to contribute to the development of a matrix for the instructional design of a teacher training model that prepares these professionals for online education. The results show that, although the literature has made an indispensable contribution to reflection on teacher training models, we recognize that more research is needed in the area, since the literature is deficient in terms of the subject under analysis.

关键词： Digital technologies Instructional design Online teaching Teacher training Training models

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Linkage Length Optimization of a Climbing Inspection Robot Using an Area Overlap Method 27th

Linkage Length Optimization of a Climbing Inspection Robot U...

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27th International Conference on Climbing and Walking Robots and Mobile Machine Support Technologies (CLAWAR)

作者： Wu, Shijia Han, Linyan Jackson-Mills, George Barber, Andrew Richardson, Robert C. Univ Leeds Sch Mech Engn Leeds LS2 9JT W Yorkshire England

ISBN: (纸本)9783031707216;9783031707223

This paper develops a new area overlap method (AOM) to optimize the linkage length of a ladder-climbing robot. Unlike the traditional path generation methods that use precise synthesis points, AOM evaluates the optimisation result by the area overlap ratio of two enclosed trajectories. The proposed method is suitable for the case that trajectory planning of a mechanism moves over obstacles, where the generated desired trajectory must completely contain the target area. Since the linkage trajectory optimized by AOM will not intersect with the target area, the AOM's result will help prevent the robot from being interfered with by obstacles during climbing. Based on the AOM, this paper optimizes the standard Hoeken linkage structure. The simulation results show that the AOM performs better than the traditional path generation method in this case. To further verify the effectiveness of the proposed method, a ladder-climbing robot driven by one motor was designed. The experimental evaluations show that the robot can successfully climb a ladder.

关键词： Climbing Robots Area Overlap Method Linkage Length Optimization

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Proportional Intuitionistic Fuzzy EDAS Method: Its Application to Cloud Service Provider Selection 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Kadikoylu, Seren Kahraman, Cengiz Istanbul Tech Univ Dept Ind Engn TR-34367 Istanbul Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

One of the best extensions for managing uncertainty in the decision-making process is intuitionistic fuzzy sets. Decision-makers and specialists can justify their decisions with a more detailed membership function on a bigger surface thanks to its two-dimensional membership functions. Proportional Intuitionistic Fuzzy sets (PIFs) are a further fuzzy set extension that incorporates proportion relations between an intuitionistic fuzzy set's parameters to better represent uncertainties in decision criteria and capture membership and non-membership degrees. This results in a more accurate representation of expert judgments. One of the conventional multi-criteria decision-making techniques, the EDAS (The Evaluation Based on Distance from Average Solution), is updated using this fuzzy extension. The challenge of choosing a cloud service provider, which affects an organization's performance, security, scalability, and cost-effectiveness in the quickly changing cloud computing landscape, has been tackled with the help of the suggested technique (PIF-EDAS). The application results demonstrate that the suggested PIF-EDAS provides reliable and significant rankings.

关键词： proportional intuitionistic fuzzy sets multi-criteria decision making EDAS cloud service provider selection

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Optimizing Ambulance Routing for Timely Delivery and Pick-Up of Nursing Teams Visiting Patients Undergoing Home Therapy 28th

Optimizing Ambulance Routing for Timely Delivery and Pick-Up...

引用

2024 International Conference Automation

作者： Szwarc, Eryk Wojcik, Robert Bocewicz, Grzegorz Banaszak, Zbigniew Koszalin Univ Technol Fac Elect & Comp Sci Koszalin Poland Wroclaw Univ Sci & Technol Fac Informat & Commun Technol Dept Comp Engn Wroclaw Poland

ISBN: (纸本)9783031782657;9783031782664

This paper proposes a comprehensive approach to optimize ambulance scheduling, considering various factors such as patient needs, nursing team availability, route optimization, and real-time tracking. The goal is to enhance efficiency, reduce delays, and prioritize urgent cases, ultimately improving the overall quality of home healthcare services by routing a fleet of ambulances responsible for delivering and receiving nursing teams without the constraint of requiring the same vehicle for both operations. Focusing on proactive/reactive routing strategies, the proposed declarative modeling-based framework aims to optimize resource utilization while contributing to the overall success of home therapy programs. Through a case study and results of conducted computer experiments, we demonstrate the effectiveness of the developed reference model in ensuring efficiency and adaptability in scenarios where vehicle consistency is not a strict requirement.

关键词： OR in health services Vehicle routing Pick-ups and deliveries Time windows Home Healthcare

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A Multi-objective Ant Colony System Method for a Robust Selective Full Truckload Vehicle Routing Problem 7th

A Multi-objective Ant Colony System Method for a Robust Sele...

引用

7th International Conference on Logistics Operations Management (GOL)

作者： El Bouyahyiouy, Karim Bellabdaoui, Adil ENSIAS Mohammed V Univ Rabat ITM Informat Technol & Management Rabat Morocco

ISBN: (纸本)9783031686337;9783031686344

The truck backhauling problem has attracted the interest of many global road transportation companies. The problem is reducing empty truck miles by having truckers carry orders along their route back to their origins. The return orders can vary in terms of their origins and destinations, their profits and their pickup and delivery time windows. Moreover, the travel time from one location to another location can be uncertain and change depending on a number of expected scenarios. This work addresses a robust full truckload commodity selection and multiple depot vehicle routing problem with time windows (RFTSMDVRPTW) under travel time uncertainty. The robustness consists of designing a set of feasible selective routes in all scenarios that maximize overall profit and minimize the worst observation of the total travel time across all scenarios subject to time window constraints. We introduce a multi-objective ant colony system algorithm for solving the RFTSMDVRPTW. We demonstrate the effectiveness and efficiency of the proposed approach through numerical experiments on randomly generated instances for the problem under consideration.

关键词： Commodity selection Full Truckload Multi-objective ant colony system Robust Optimization Uncertain travel time Vehicle Routing

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Intelligent Educational Chatbot for Student Interaction Based on DaVinci Model 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Angeline, R. Adhityaa, C. Ranganathan, V. Pranav Kailash, K. E. SRM Inst Sci & Technol Dept Sci & Engn Chennai Tamil Nadu India

ISBN: (数字)9789819713264

ISBN: (纸本)9789819713257;9789819713264

In current times, the incorporation of artificial intelligence that is AI in the world of education has demonstrated significant potential in reshaping conventional learning methods. Advanced language models, like ChatGPT developed by OpenAI, have emerged as valuable tools for enhancing educational interactions by introducing personalized and interactive learning environments. Within this context, the term "Intelligent Educational Chatbot for Student Interaction based on DaVinci Model" denotes the utilization of AI technology to innovate and create engaging learning experiences. The technology, exemplified by GPT-based models, has the capacity to potentially transform traditional educational approaches by delivering customized, contextually relevant, and captivating educational content. In conventional education systems, an average student lacks personalized learning experience. Also intelligent chatbot experiences like ChatGPT lack proper context and the information it provides does not have proper validation. This drawback can be overcome by adding context to the model trained so that it generates definitive answers. To implement such a model, we use the DaVinci model as a base model and fine tune it in such a way that the answers generated by it are context specific. So, with the implementation of the Intelligent Educational Chatbot for Student Interaction based on the DaVinci model, the lack of context the answers generated by the AI model can be rectified. Moreover, the answers generated by this model will be accurate and can be traced back to a proper source which properly validates the answers generated.

关键词： GPT-based model Context based DaVinci model Smart education

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Drawbacks of Programming Dataflow Architectures and Methods to Overcome Them 1

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2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI)

作者： Korolija, Nenad Univ Belgrade Sch Elect Engn Bulevar Kralja Aleksandra 73 Belgrade Serbia

ISBN: (数字)9783031608407

ISBN: (纸本)9783031608391;9783031608407

Compared to the control-flowparadigm dataflow paradigm is proven to be superior for certain classes of high-performance computing algorithms, such as AI. However, this comes with the cost. Many problems should be solved in order to efficiently utilize dataflow hardware. Some of them are programming dataflow architectures and debugging issues that arise during this process, relatively long simulation time, finding suitable dataflow hardware, and difficulties with the debugging hardware problems that might occur. This paper analyses existing solutions for accelerating high-performance computing algorithms along with problems that each architecture introduces, as well as potential solutions to the aforementioned drawbacks of utilizing the dataflow paradigm for accelerating algorithms. The analysis is performed on both hardware and software levels. Results indicate that dataflow hardware has the potential to be efficiently used along with control-flow hardware using AI. The best performance is achieved when combining control-flow and dataflow hardware on the same chip die.

关键词： High-Performance Computing Control-flow Dataflow

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