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Technology in Engineering Education: The Sustainable Enterprise Business Game 3rd

Technology in Engineering Education: The Sustainable Enterpr...

引用

3rd International Symposium on Industrial Engineering and Automation

作者： Fontanella, Sabrina Fraccascia, Luca Nonino, Fabio Baldissin, Nicola Sapienza Univ Rome I-00185 Rome Lazio Italy Univ Twente NL-7522 NB Enschede Overijssel Netherlands Business Game I-33100 Udine Fvg Italy

ISBN: (纸本)9783031704642;9783031704659

The aim of the article is to describe the reasons and the creation model for a business game designed to simulate a sustainable business model, a game that will then be applied within engineering education. Our research acknowledges the key relationship between the crucial role played by businesses embracing sustainable business models and the increasing use of digital platforms for education on sustainability goals. By integrating these components into the university curriculum, a comprehensive approach emerges that fosters the development of knowledge, essential skills, attitudes, and values dedicated to creating sustainable businesses of the future, developed by tomorrow's managers. Through the business game, individuals not only gain an understanding of the complexities of sustainability but also actively engage in initiatives aimed at promoting social impact and ensuring a sustainable future for generations to come. This digital business game for sustainability education is primarily dedicated to university students: especially those in engineering, but also those in other faculties, with the aim of providing instructions on how to start entrepreneurial activities through sustainable business models. This study contributes to the understanding of sustainable business practices and innovative educational methodologies, in line with the global imperative of sustainability.

关键词： Sustainable education Business game New educative technologies Reskilling and Training

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HR Analytics in Retail: Predicting Employee Churn with Machine Learning

HR Analytics in Retail: Predicting Employee Churn with Machi...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Erden, Serhan Berke Erisen, Mert Sarigul, Yavuz Nuri Eken, Buse Ozcan, Tuncay Istanbul Tech Univ Dept Management Engn TR-34367 Istanbul Turkiye

ISBN: (纸本)9783031671913;9783031671920

The retail sector is facing operational inefficiencies and high recruitment costs due to the increasing turnover rate. This project focuses on identifying and analyzing the key factors leading to the departure of qualified personnel. The data discussed is a real-life HR analytical case of a company working in the retail industry. Using advanced machine learning algorithms such as LGBM, XGBoost, AdaBoost, and CatBoost, the study seeks to reveal the relationship between variables like education level, city, and age. The project provides actionable insights that can inform strategic decisions by using both qualitative and quantitative data sources. According to the results, the most successful model is discovered as CatBoost. The findings indicate that the employee's average sales and its coefficient of variation, trends of sales, and age of employee play crucial roles in employee churn. To interpret these, an increase in an employee's sales rates correlates with a higher likelihood of retaining their position. Actions taken in light of the project's findings can contribute to companies predicting employee churn in advance, thereby reducing turnover rates and improving operational costs.

关键词： Employee Churn Machine Learning HR Analytics Turnover Statistical Tests ANOVA Catboost LGBM XGBoost AdaBoost

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Novel Design Templates for OTT Platform Thumbnails to Engage the Viewers 8th

Novel Design Templates for OTT Platform Thumbnails to Engage...

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Supritha, K. R. Mamatha, G. S. R V Coll Engn Bangalore Karnataka India

ISBN: (纸本)9789819713257;9789819713264

This study explores novel design templates for OTT platform thumbnails to effectively engage viewers. With the increasing popularity of OTT platforms, it is crucial to create visually appealing and attention-grabbing thumbnails that attract and retain viewers. This study focuses on developing innovative design templates that incorporate elements such as bold typography, captivating imagery, and vibrant color schemes. These templates aim to enhance the visual impact of thumbnails, providing a glimpse into the content and enticing viewers to click and explore further. The study's findings provide insights on improving thumbnail design for enhanced viewer engagement and, as a result, higher viewership on OTT platforms. This abstract underscores the intricate interplay between innovation and usability. Balancing visually arresting designs with user-friendliness and accessibility is a central challenge. While ushering viewers into a world of visual marvels, it also underscores the significance of maintaining authenticity and trust. The journey through this abstract culminates in the realization that, as OTT platforms evolve, the marriage of novel design templates and purposeful engagement is a catalyst for a new dimension of viewer interaction, forging a dynamic synergy between creativity and content.

关键词： Over-the-top (OTT) platforms Thumbnails

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The Implementation of Quantum Annealing for Ensemble Pruning 1

引用

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

作者： Yulianti, Lenny Putri Trisetyarso, Agung Santoso, Judhi Surendro, Kridanto Inst Teknol Bandung Sch Elect Engn & Informat Bandung 40132 Indonesia Bina Nusantara Univ Sch Comp Sci Dept Math Jakarta 11480 Indonesia

ISBN: (数字)9789819733057

ISBN: (纸本)9789819733040;9789819733057

Ensemble pruning stands as a pivotal strategy in simplifying ensemble complexity while maintaining its accuracy. Although optimization-based methods have historically dominated this field due to their comprehensive solutions, issues with local optima and time-intensive processes persist. Consequently, this study proposes quantum annealing as a quantum-based solution to address these limitations. The approach involves four key stages: formulating pruning problems, embedding formulations into the D-Wave solver, annealing, and reading out the optimal solution. The pruning process aims to maximize ensemble accuracy while ensuring the inclusion of at least one trained learner. The evaluation was conducted across five datasets, focusing on ensemble size and accuracy metrics. A comparative analysis was performed against bagging, AdaBoost, hybrid QA, hybrid QA pruned using particle swarm optimization, and proposed method. The results demonstrate that while the proposed method may not significantly reduce ensemble size compared to particle swarm optimization, it exhibits exceptional performance in all datasets, highlighting its potential to enhance accuracy.

关键词： Quantum annealing Pruning Ensemble Accuracy

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Low Cost Machine Vision for Insect Classification 1

引用

Intelligent systems Conference (IntelliSys)

作者： Brandt, Danja Tschaikner, Martin Chiaburu, Teodor Schmidt, Henning Schrimpf, Ilona Stadel, Alexandra Beckers, Ingeborg E. Hausser, Frank Berliner Hsch Tech Berlin Germany UBZ Listhof eV Reutlingen Germany

ISBN: (数字)9783031477157

ISBN: (纸本)9783031477140;9783031477157

Preserving the number and diversity of insects is one of our society's most important goals in the area of environmental sustainability. A prerequisite for this is a systematic and up-scaled monitoring in order to detect correlations and identify countermeasures. Therefore, automatized monitoring using live traps is important, but so far there is no system that provides image data of sufficient detailed information for entomological classification. In this work, we present an imaging method as part of a multisensor system developed as a low-cost, scalable, open-source system that is adaptable to classical trap types. The image quality meets the requirements needed for classification in the taxonomic tree. Therefore, illumination and resolution have been optimized and motion artefacts have been suppressed. The system is evaluated exemplarily on a dataset consisting of 16 insect species of the same as well as different genus, family and order. We demonstrate that standard CNN-architectures like ResNet50 (pretrained on iNaturalist data) or MobileNet perform very well for the prediction task after re-training. Smaller custom made CNNs also lead to promising results. Classification accuracy of >96% has been achieved. Moreover, it was proved that image cropping of insects is necessary for classification of species with high inter-class similarity.

关键词： Computer vision Image classification Insect monitoring Biodiversity

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MS-ETL: An Architecture for the Multiple Data Source Extraction, Transformation, and Load Applied to Solar Flares Data 1

引用

Intelligent systems Conference (IntelliSys)

作者： Silveira, Carlos Roberto, Jr. Ribeiro, Marcela Xavier Fed Univ Sao Carlos UFSCar Dept Comp Sci Sao Carlos Brazil

ISBN: (数字)9783031477249

ISBN: (纸本)9783031477232;9783031477249

Enabling the knowledge discovery in Series of Satellite Images is a challenging task. Spatiotemporal and non-traditional data constitute this domain, i.e., images and semi-structured textual data. Although there is a massive amount of applicability for this knowledge, we still face a lack of work that addresses the challenges. The gap is even worse when working with the Series of Solar Satellite Images (SSSI). Thus aiming to enable the extraction of knowledge in SSSI, we proposed a new Extraction, Transformation, and Load (ETL) architecture called Multiple data-source Solar ETL (MS-ETL). MS-ETL extracts SSSI data from multiples source and joins it in a single source of truth, enabling knowledge extraction: The solar images are extracted from a data source that is a different SSSI textual data source. After the extraction, MSETL transforms the textual data into structured data and loads it to a database allowing simple out-of-the-box analysis. In the end, we obtain a single source of truth for SSSI of almost two solar cycles in a reasonable amount of time. Now that information is available and can be used to apply advanced machine learning techniques. Notably, the proposed approach collects well-suited data for input in deep learning techniques.

关键词： Extraction Transformation and load Multiple data source extraction Satellite images series Solar flares

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A Pilot Study of a Human-Readable Robotic Process Automation Language 20th

A Pilot Study of a Human-Readable Robotic Process Automation...

引用

20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Gago, Piotr Jablonski, Daniel Voitenkova, Anna Debelyi, Ihor Skorupska, Kinga Grzeszczuk, Maciej Kopec, Wieslaw Polish Japanese Acad Informat Technol Warsaw Poland

ISBN: (纸本)9783031665936;9783031665943

In this paper, we explore the usability of a custom eXtensible Robotic Language (XRL) we proposed. To evaluate the user experience and the interaction with the potential XRL-based software robot, we conducted an exploratory study comparing the notation of three business processes using our XRL language and two languages used by the leading RPA solutions. The results of our study show that the currently used XML-based formats perform worse in terms of conciseness and readability. Our new XRL language is promising in terms of increasing the readability of the language, thus reducing the time needed to automate business processes.

关键词： RPA HCI robotic process automation human-centered computing business processes software robots

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Coronary Vessel Segmentation in X-ray Using U-Net 5th

Coronary Vessel Segmentation in X-ray Using U-Net

引用

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

作者： Anand, H. S. Dhanya, S. Kumar, K. Manoj Anjali, S., V Chinmaya Vishwavidyapeeth Inst Sci & Technol Ernakulam Kerala India Muthoot Inst Technol & Sci Ernakulam Kerala India

ISBN: (纸本)9789819720811;9789819720828

Cardiovascular disease remains a significant global health concern, causing substantial morbidity and mortality. This study addresses the limitations of subjective variability in traditional diagnostic modalities, particularly angiography, which assesses coronary artery blockages using X-ray images and radio opaque dye. Employing deep learning, the research utilizes a pre-trained U-Net model to efficiently recognize coronary artery structures in X-ray angiography images. Despite challenges like weak contrast and deformable vessel shapes, the model accurately performs image segmentation and calculates vessel stenosis. Achieving a mean F1 score of 0.921, precision of 0.938, and accuracy of 0.915, the model consistently outperforms benchmarks with lower standard deviations. Stenosis identification demonstrates significant prediction accuracy. The study's future implications include predicting stent placement positions and estimating post-stenting circulation success. This innovative approach offers an objective analysis, enhancing diagnostic accuracy in cardiovascular health.

关键词： Cardiovascular disease Coronary artery segmentation U-Net architecture

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Decoder-Only Transformers: The Brains Behind Generative AI, Large Language Models and Large Multimodal Models

Decoder-Only Transformers: The Brains Behind Generative AI, ...

引用

2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Naik, Dishita Naik, Ishita Naik, Nitin Birmingham City Univ Birmingham W Midlands England King Edward VI Five Ways Sch Birmingham W Midlands England Aston Univ Sch Comp Sci & Digital Technol Birmingham W Midlands England

ISBN: (纸本)9783031744426;9783031744433

The rise of creative machines is attributed to generative AI which enabled machines to create new contents. Wherein the introduction of the advanced neural network architecture known as a transformer revolutionized the landscape of generative AI. A transformer transforms one sequence into another sequence, and is primarily used in natural language processing and computer vision tasks. Which determines the relationship between tokens or words in a sequence to understand the context, while processing these tokens or words simultaneously. Transformers were built to resolve various issues of its previous neural networks, such as a Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM);and are now the brains behind majority of generative AI models, for example Large Language Models (LLMs) and Large Multimodal Models (LMMs). This paper will explain about the transformer and its architectural components and working. Subsequently, it will illustrate the decoder-only transformer architecture and its components and working including the reason why this type of transformer architecture is used in most generative AI models such as LLMs and LMMs.

关键词： Transformer Attention Encoder Decoder GPT Generative Pre-trained Transformer Unsupervised Pre-training SFT Supervised Fine-tuning LLMs Large Language Models LMMs Large Multimodal Models NLP Natural Language Processing GenAI Generative AI

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Design of a 3D-Printed Accessible and Affordable Robotic Arm and a User-Friendly Graphical User Interface 1

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4th Congress on Intelligent systems (CIS)

作者： Bell, Daniel Secco, Emanuele Lindo Liverpool Hope Univ Sch Math Comp Sci & Engn Robot Lab Liverpool Merseyside England

ISBN: (数字)9789819990375

ISBN: (纸本)9789819990368;9789819990375

This paper presents the design, manufacturing and software integration of a 3D-printed robotics arm. The robot design is made of a rotational base combined with a five degrees of freedom arm with a gripper. An intuitive and user-friendly Graphical User Interface is also implemented and integrated with the robotic device. Preliminary tests are performed showing that the system has the potential to be used in different contexts and applications, as well as manufacturing environments where pick and place tasks could be performed in a low-cost fashion.

关键词： 3D-printed prototyping 3D-printed robotics Human-robot interface Intuitive interface User-friendly human-robot interaction

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