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

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Decision Making for the Intuitionistic Fuzzy Score Function with the KL-Divergence on Multi-criteria 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Lee, Sanghyuk Makhmudov, Muzaffar New Uzbekistan Univ Tashkent 08544 Uzbekistan

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

The score function has been proposed to discriminate attributes for the multi-criteria problem based on the KL-Divergence. The existing research on the scoring function has been introduced, and their difficulty to decision making has been analyzed. From the information theory, KL-Divergence has been applied to intuitionistic fuzzy sets (IFSs) data. Simplified structure is proposed to calculate IFSs. Proposed scoring function is applied to the multi-criteria decision making, and the calculation results of the illustrative example showed relevant results with clear comparison.

关键词： Score Function Multi-Criteria Decision Making Cross Entropy

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Guiding the Design of Effective Learning Factories: Requirements of a Design Approach for Resilience 14th

Guiding the Design of Effective Learning Factories: Requirem...

引用

14th International Conference on Learning Factories (CLF)

作者： Massa, Janneke Lutters, Eric Univ Twente Dept Design Prod & Management Enschede Netherlands Stellenbosch Univ Dept Ind Engn Stellenbosch South Africa

ISBN: (纸本)9783031653995;9783031654008

The design of effective learning factories is far from trivial, requiring the proper integration of different perspectives (such as education and technology) to achieve unique learning objectives, while remaining adaptable to evolving technologies and emerging challenges. Despite their potential, current implementations of learning factories often face limitations that prevent them from maximising their primary goal: effective learning. To understand the essential characteristics of effective learning factories, this paper explores the importance of embracing multi-dimensionality, promoting constructive alignment, and addressing constraints through context-specific solutions. It introduces the concept of resilience as a fundamental strategy for creating effective learning environments from the outset. The aim of the paper is to lay the groundwork for a design approach that supports the development of resilient learning factories capable of evolving dynamically to meet shifting needs. It seeks to outline the requirements for such a design approach by examining the characteristics of these learning factories. In the future, the verified requirements form the foundation for a dynamic design guide capable of envisioning potential futures for learning factories.

关键词： learning factory design design approach resilience requirement specification

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Implementation of an Industry 4.0 Module in the International Educational Project ERASMUS+WORK4CE 21st

Implementation of an Industry 4.0 Module in the Internationa...

引用

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

作者： Arras, Peter Parkhomenko, Anzhelika Parkhomenko, Illia Katholieke Univ Leuven Campus De Nayer JP De Nayerlaan 5 B-2860 St Katelijne Waver Belgium Univ Appl Sci & Arts Otto Hahn Str 23 D-44227 Dortmund Germany Natl Univ Zaporizhzhia Polytech Zhukovskogo Str 64 UA-69063 Zaporizhzhia Ukraine

ISBN: (纸本)9783031618901;9783031618918

TheERASMUS+ WORK4CE(Cross-domain competences for healthy and safe work in the 21st century) is a European funded educational project, which aims at bringing patterns, methods and competences for the projectized and digitalized future of Industry and society. The Industry 4.0 educational module was developed as part of this project with the purpose of giving students introductory knowledge on the key new technologies that are the core of Industry 4.0 so that they can understand the technological challenges of digital transformation. The paper presents the results of developing a framework for implementing the case method for a multidisciplinary project when studying Industry 4.0 module.

关键词： Industry 4.0 Case Method Wire Bending Machine Multidisciplinary Project Virtual and Physical Prototypes Virtual and Augmented Reality Human Machine Interface

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Artificial Intelligence Methods for Pet Emotions Recognition 1

引用

19th International Conference on Dependability of Computer systems (DepCoS-RELCOMEX)

作者： Mazurkiewicz, Jacek Wroclaw Univ Sci & Technol Fac Informat & Commun Technol Ul Wybrzeze Wyspianskiego 27 PL-50370 Wroclaw Poland

ISBN: (数字)9783031618574

ISBN: (纸本)9783031618567;9783031618574

Analyzing emotions in cats is a subject that comes with difficulties in interpretation. The subtle facial expressions of these animals make deciphering their emotional signals a challenge. The work focuses on the task of classifying feline emotions from images. It aims to test whether deep learning networks can recognize the primary emotional states of these animals on real (non-laboratory) image data. The results obtained in this work provide a basis for further research in this area. Future studies can focus on refining the parameters of existing models, developing advanced data analysis techniques, and exploring new classification models. Further research has the potential to contribute to a better understanding of emotional states in cats and improve the effectiveness of classification processes based on authentic images.

关键词： artificial intelligence emotions cat

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Artificial Intelligence Tools and Chatbots for Design Education 8th

Artificial Intelligence Tools and Chatbots for Design Educat...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Shreya, H. R. Kumar, Tarun PES Univ Bengaluru 560085 Karnataka India Indian Inst Sci Bengaluru 560012 Karnataka India

ISBN: (纸本)9789819713127;9789819713134

Rapid advancements in computing power and artificial intelligence (AI) have propelled the development of advanced tools and chatbots for design education. These generative AI tools can provide inspiration to solve problems based on prompts. ChatGPT is a natural language processing (NLP) model, but it is limited to generating verbal responses and basic images. Hence, it cannot contribute heavily to the design process due to the inability to generate complex images and 3D models. Other AI tools, like Craiyon, Sloyd, and 3dfy, can process text to produce images or 3D models using convolutional neural networks. In this paper, these tools are used in the design process by employing prompt engineering. A sample project is documented, and different conceptual design phases are identified. In each phase, assistive AI tools are incorporated and the outputs-with and without AI tools-are compared and analysed. It is inferred that AI tools can potentially transform the domain by making the process faster and more effective. Currently, these AI tools are assistive, however, in the future, they might contribute more significantly to the process. Hence, AI tools should be integrated into the design curriculum, reducing the time spent on gathering resources and increasing the creativity of solutions.

关键词： Artificial intelligence Design education AI tools Chatbots

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Cost Effective Predictive Railway Track Maintenance 12th

Cost Effective Predictive Railway Track Maintenance

引用

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

作者： Harikrishnan, Sri Dorner, Verena Sohi, Shahrom Vienna Univ Business & Econ Inst Digital Econ Welthandelspl 1 A-1020 Vienna Austria Vienna Univ Business & Econ Inst Data Proc & Knowledge Management Welthandelspl 1 A-1020 Vienna Austria

ISBN: (纸本)9783031603273;9783031603280

Efficient railway track maintenance is crucial due to the increasing demand for rail transportation. Reducing costs by optimizing maintenance procedures and operations is essential, and predictive maintenance approaches are necessary to achieve this. We summarized previous literature on track geometry and developed a predictive model for maintenance cost management. We test random forest and SVM predictions on a simulated dataset This information can assist railway companies in improving maintenance practices, planning costs, and enhancing network performance and efficiency.

关键词： predictive maintenance rail operations data modelling

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Real-Time Drowsiness Detection and Health Status System in Agricultural Vehicles Using Artificial Intelligence 6th

Real-Time Drowsiness Detection and Health Status System in A...

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6th Iberian Robotics Conference (Robot)

作者： Soares, Beatriz Oliveira, Daniel Lau, Nuno Palaio, Helio Contente, Olga Albuquerque, Daniel Marques, Daniel Aveiro Univ IEETA LASI DETI Aveiro Portugal ProjectBox Viseu Portugal Polytech Inst Viseu Viseu Portugal TIS Coimbra Portugal

ISBN: (纸本)9783031591662;9783031591679

This study presents a real-time monitoring system for preventing accidents in agricultural vehicles by monitoring the farmer and driving conditions. The system employs vital signals monitoring, using a bracelet to assess the farmer's health status, and drowsiness detection, utilizing a camera and Artificial Intelligence to evaluate the level of drowsiness. In emergencies, the system communicates with a central station to identify the triggering factor. Driving conditions are monitored using inertial and GPS data. The focus of this paper is on the farmer's monitoring aspect. Health status is determined by analyzing Heart Rate and Oxygen Saturation values measured by the bracelet. While currently measuring two values, the system is designed to accommodate additional measurements. Multiple algorithms for driver drowsiness detection were tested, highlighting the need to consider different approaches in the final solution. This research proposes an integrated system to enhance safety and prevent accidents in agricultural vehicles, addressing the specific requirements of the farming industry.

关键词： Artificial Intelligence Vital Signals Monitoring Drowsiness Detection Real-time Farmer Monitoring

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NL2Code: Harnessing Transformers for Automatic Code Generation from Natural Language Descriptions 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Pavitha, N. Patrawala, Alimurtuza Kulkarni, Tejas Talati, Vidit Dahiya, Shubham Vishwakarma Univ Fac Sci & Technol Dept Comp Engn Pune Maharashtra India

ISBN: (数字)9789819713264

ISBN: (纸本)9789819713257;9789819713264

In an era where there's a lot of information and a big demand for things to be done automatically, combining the power of understanding human language with computer programming has become really important. This research paper introduces an achievement in this domain. The software which we have developed can convert natural language problem statements into their equivalent Python code, hence making it easier to write code for a normal human. The heart of our software lies in the transformer model which is trained on an extensive corpus of diverse Python codes. This corpus encompasses a wide spectrum of programming concepts and syntactic structures, enabling our model to discern intricate patterns and nuances in the language of code. This idea is really important for things like quickly testing ideas, making software, and teaching. It helps connect regular language with computer language, making it easier for people and machines to work together. This could change the way we use computers in a big way. We have also done an analysis regarding the related works in this domain and shared our findings in this paper. Our methodology includes how we processed the data and the steps taken to build a fully functional software prototype. This section also offers the architecture used to build this software. A brief comparison between the existing solutions has also been done. In conclusion, this research represents a milestone in the pursuit of human-computer interaction. Our model has the potential to revolutionize the way programs are written.

关键词： Code generation Natural language processing (NLP) Transformer Python

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An Xlnet Based Target Dependent Sentiment Classification Along with a Smart Webapp for Post-disaster Management Using Django 8th

An Xlnet Based Target Dependent Sentiment Classification Alo...

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Rachel, J. Julanta Leela Bhuvaneswari, A. Vellore Inst Technol Sch Comp Sci & Engn Chennai India

ISBN: (纸本)9789819713288;9789819713295

In the aftermath of a calamity, a substantial number of individuals engage in communication through direct means or via social media platforms in order to seek assistance from governmental entities or organizations dedicated to disaster relief and recovery. In the event that an individual impacted by a particular issue chooses to communicate their thoughts or seek assistance through social media platforms or helpline services, there is a significant likelihood that their message may become obscured within the vast volume of incoming communications. The prevalence of excessive tweeting and the scarcity of individuals seeking assistance contribute to the challenge faced by organizations in manually filtering large volume of messages. So limiting their ability to respond promptly will be a challenging task. The current disaster management strategies are prevalent in various locations due to several drawbacks. To overcome the existing flaws, a smart web application is designed in which the peoples need will be met by meeting their requirements. It tracks the location where disaster occurs via tweets using target sentiment classification and the required items will be delivered as quick as possible which serves as a comprehensive platform that offers hotline services, contributing to the promotion of public welfare and the facilitation of efficient catastrophe management. This service serves as a platform for individuals to request essential items such as food, medicines, and groceries required at the time of disaster which helps in managing the welfare of the public efficiently during emergency situation. HTML, CSS, Bootstrap, Django, and Python has been used to develop the application. XLNet is used to perform classification of tweets. The maximum accuracy achieved though classification is 85% which is above all the other existing models.

关键词： Bidirectional encoder representations from transformers (BERT) Classification Hyper text markup language (HTML) Cascading style sheet (CSS) Bidirectional gated recurrent unit (BiGRU) XLNet and geo-locators

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A Convolutional Model to Generate Human and Anime Faces Using DCGAN 1

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5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Singh, Shreshtha Rani, Ritu Sharma, Arun Dev, Amita Indira Gandhi Delhi Tech Univ Women Delhi India

ISBN: (数字)9789819720538

ISBN: (纸本)9789819720521;9789819720538

Generative Adversarial networks are one of the primary sources of booming Artificial Intelligence-based Art generation. Nowadays Generative Adversarial networks possess many applications including Text to Image Translation, Face Frontal View Generation, and Generating fresh human poses. GANs have been extensively used for image synthesis in recent years, including generating synthetic human and anime-style images. In this paper, a modified GAN architecture has been proposed to generate human faces and anime images that are visually appealing, detailed, and diverse. This paper describes the architecture of a GAN model, which incorporates a combination of a generator model and a discriminator model, and the training procedure using Anime Face Dataset and CelebFaces Attributes Dataset available. The evaluation of the execution of the suggested GAN model is performed using various metrics, including visual inspection, loss functions and the real and fake score of the discriminator model. The outcomes demonstrate that proposed working GAN design can generate good-quality anime and human face images that are visually similar to real images and exhibit diversity in terms of style, character, and background.

关键词： Generative adversarial networks Convolutional networks Neural networks Human images Anime images

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