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

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PrimARy: Intelligent System Based on Mixed Reality for Diagnosis and Assistance in Primary Care 1

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： del Hoyo, Pablo Schez-Sobrino, Santiago Garcia, Francisco Cardoso, Jorge C. S. Albusac, Javier Vallejo, David Univ Castilla La Mancha Dept Comp Sci Ciudad Real 13071 Spain Univ Coimbra Dept Informat Engn CISUC Rua Silvio LimaUniv Coimbra Polo 2 P-3030790 Coimbra Portugal

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

This research aims to improve the diagnostic and support capabilities of healthcare professionals in primary care settings. We present PrimARy, a system that enables primary care workers to follow medical protocols in a guided manner using Mixed Reality and Artificial Intelligence. These protocols, defined using a node-based visual editor, can be automatically integrated into the Mixed Reality application, extending the system's capabilities to different healthcare scenarios. The protocols can be enriched with documents and multimedia, and serve as the basis for the virtual assistant built into PrimARy to guide users in following a medical protocol. This functionality makes use of a Large Language Model deployed on a dedicated server for inference processes. As a practical application, the integration of a visual triage process to assess overweight and obesity is proposed. The ultimate goal is to scale our proposal for use in primary care centers, patients' homes, and emergency situations by medical and nursing staff.

关键词： Primary Care Mixed Reality Virtual Assistant LLM

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Multiclass Intrusion Detection in IoT Using Boosting and Feature Selection 12th

Multiclass Intrusion Detection in IoT Using Boosting and Fea...

引用

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

作者： Hamdouchi, Abderrahmane Idri, Ali Mohammed VI Polytech Univ Benguerir Morocco Mohammed V Univ Rabat Software Project Management Res Team ENSIAS Rabat Morocco

ISBN: (纸本)9783031602207;9783031602214

The proliferation of Internet of Things (IoT) devices has resulted from the continuous evolution of interconnected computing devices and emergence of novel network technologies. Intrusion Detection systems (IDSs) play a pivotal role in ensuring IoT network security. Nonetheless, the development of a robust IDS with high performance for detecting specific anomalies to prevent attacks remains a challenging task. This study systematically evaluated and compared two classifies XGBoost and LightGBM employing five filter-based feature selection methods (ANOVA, Kendall's test, Mutual Information, Maximum Relevance Minimum Redundancy, and Chi-square) with distinct selection thresholds. The evaluation was conducted over the NF-ToN-IoT-v2 dataset using the Scott-Knott test and Borda Count system. A total of 152 classifier variants were assessed to determine the most effective model. Results demonstrated that utilizing XGBoost in conjunction with 200 estimators, ANOVA and MI as the feature selection combination, and selecting the top 18 features, constituted an effective and powerful model compared to alternative methods.

关键词： Intrusion detection system ensemble learning boosting imbalanced data IoT NF multiclass classification

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Data Augmentation Techniques to Detect Cervical Cancer Using Deep Learning: A Systematic Review 19th

Data Augmentation Techniques to Detect Cervical Cancer Using...

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

作者： Wubineh, Betelhem Zewdu Rusiecki, Andrzej Halawa, Krzysztof Wroclaw Univ Sci & Technol Fac Informat & Commun Technol Wroclaw Poland

ISBN: (纸本)9783031618567;9783031618574

Computer-assisted systems have been widely used as tools to support medical experts in various fields, including the analysis of cervical cytology. However, due to patient privacy and ethical considerations, processing the model is challenging due to insufficient data in medical imaging. Data augmentation has gained popularity as a solution to this problem, especially in sectors where large datasets are unavailable, thereby increasing the size of a training dataset. This study aimed to identify a data augmentation technique to detect cervical cancer. To conduct this analysis, we systematically reviewed secondary studies published between 2017 and 2023 using the search term 'data augmentation', 'cervical cancer' and 'deep learning' from databases including Scopus, Web of Science, PubMed, IEEEXplore, Science Direct, and conducted a manual search on Google Scholar. The results showed that data augmentation techniques are categorized as basic methods and artificial image generation. Among basic data augmentation techniques, rotation and flipping are the most widely used. In the generation of artificial images, DCGAN is used to create high-quality synthetic images. Basic augmentation is used for both segmentation and classification tasks, while artificially generated techniques are used exclusively for classification tasks. Consequently, all these techniques enhance the performance and generalizability of deep learning models by increasing the size of the dataset.

关键词： Cervical Cancer Data Augmentation Deep learning

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Expectations and Knowledge Sharing by Stakeholders in a Bioproducts Community of Practice: An Exploratory Study 1

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

作者： Oliveira, Leandro Cardoso, Eduardo Luis CBIOS Univ Lusofonas Res Ctr Biosci & Hlth Techno Campo Grande 376 P-1749024 Lisbon Portugal Univ Catolica Portuguesa CBQF Ctr Biotecnol & Quim Fina Lab Associado Escola Super Biotecnol Rua Diogo Botelho 1327 P-4169005 Porto Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The Communities of Practice (CoP) are informal groups of individuals with common interests who come together to share experiences, discuss, and improve a given practice. This work aims to evaluate the perception of knowledge sharing in a community of practices in bioproducts by its participants and their expectations regarding added value, information and available resources/activities, and shared materials. A questionnaire disseminated by CoP and social networks was developed between December 2020 and February 2021. Forty-three responses were collected. Most participants were female (67.4%), with a mean age of 32 years (SD = 9.1 years), and they had a degree (39.5%). Most participants have a very positive perception of knowledge sharing through a community of practice in bioproducts. Participants believe it is an added value to belong to a CoP due to the exchange of information and experiences and would like information on industry trends, scientific events, and innovations to be available. These results will make it possible to promote knowledge sharing at the CoP, adjusting the information, resources, and materials available there, to the expectations and preferences of the participants.

关键词： Communities of Practice Knowledge Sharing Bioproducts Attitudes Expectations

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Evaluation of Energy Management Projects Using Pythagorean Fuzzy Z-Numbers

Evaluation of Energy Management Projects Using Pythagorean F...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Sari, Irem Ucal Istanbul Tech Univ Ind Engn Dept Istanbul Turkiye

ISBN: (纸本)9783031671913;9783031671920

Energy management projects are predominantly recommended by external sources, such as Energy Service Companies, and this can lead to a significant variation in the reliability level of evaluations conducted by top management. Considering the potential absence of direct expertise among decision-makers in these projects, it becomes crucial to account for the reliability levels of their assessments during decision-making. This paper introduces the Pythagorean Fuzzy Z-Analytic Hierarchy Process methodology to account for the reliability levels of decision-makers' judgments and applies it to weigh the selection criteria of energy management projects.

关键词： Pythagorean Fuzzy Z-Numbers Pythagorean Fuzzy Z-Analytic Hierarchy Process Energy Management

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Using Node-Red to Visualize Dairy Production Data via Modbus 28th

Using Node-Red to Visualize Dairy Production Data via Modbus

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2024 International Conference Automation

作者： Samoilenko, Yuliia Smitiukh, Yaroslav Kostiuk, Yuliia Stepashkina, Kateryna Hnatchenko, Dmytro Yaremych, Valentyn Natl Univ Food Technol UA-01033 Kyiv Ukraine State Univ Trade & Econ UA-02156 Kyiv Ukraine

ISBN: (纸本)9783031782657;9783031782664

The dairy industry is under consideration, namely the possibility of collecting data from sensors of the technological process of whipping cream into butter to assess the quality of the finished product. In today's conditions of general digitalization and the Industry 4.0 strategy, the industrial sector is gradually integrating industrial IoT trends that combine automation, big data, IoT, Cloud. In this work, we will try to make it clear how easy it is to store, analyze and visualize data from certain industrial systems with the help of innovative IT developments using the advantages of the Node-RED inter-face. At industrial plants, the set of data on technological parameters is avail-able only to the equipment operator through the HMI. The integration of Node-RED with the cloud application Google Sheet (spreadsheet) is shown for storing data in the cloud, analyzing and visualizing data of technological parameters. Node-RED, along with the Modbus and Dashboard modules, can easily create a web dashboard that can be shared via a web link and viewed in any web browser on the network.

关键词： industrial IoT automation big data cloud applications Node-Red

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Improving Customer Service Through the Use of Chatbot at Enma Spa Huancayo, Peru 12th

Improving Customer Service Through the Use of Chatbot at Enm...

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

作者： Araujo, Elvis Javier, Diana Gamarra, Daniel Univ Continental Fac Engn Huancayo Peru

ISBN: (纸本)9783031603273;9783031603280

This paper shows the implementation of EnmitaBot (chatbot) in the Spa and personal care micro-enterprise, based on the identification of problems through interviews, in order to improve customer service. The platform used was ManyChat, which was developed with a ten-step process from identifying the problem to testing with customers. The key dimensions used to measure chatbot performance were knowledge and personalization. The measurement was carried out from frequent customer surveys, obtaining a Net Promoter Score (NPS) result of 71% and on the Likert scale of 4.03, achieving a high correlation between these two indicators. Measurements by questions and dimensions are presented, and the significant correlation between responses on the Likert scale and NPS is highlighted. The dimensions used to measure were;response time, knowledge and database, personalization, intuition and understanding, natural interaction and language;obtaining the highest NPS in knowledge and database with 72.25% and in personalization with 72.33%. Regarding the lowest NPS obtained, Intuition and comprehension were 63.00% and natural interaction and language with 69.00%.

关键词： Chat implementation ManyChat Platform Customer Service Enhancement NPS (Net Promoter Score) Measurement

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Data Mining and Machine Learning-Based Predictive Model to Support Decision-Making for the Accreditation of Learning Programmes at the Higher Education Authority 9th

Data Mining and Machine Learning-Based Predictive Model to S...

引用

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

作者： Kawesha, Francis Phiri, Jackson Univ Zambia Lusaka 10101 Zambia

ISBN: (纸本)9789819732883;9789819732890

Accreditation of learning programmes is a critical process for ensuring the quality and standards of higher education institutions. This paper presents a predictive model leveraging data mining and machine learning techniques to enhance decision-making in the accreditation of learning programmes at the Higher Education Authority (HEA). The proposed model utilizes historical data, including institutional, programme-specific, and performance-related features, to predict the likelihood of accreditation success. We demonstrate how this predictive model can assist HEA in allocating resources efficiently and making informed decisions about accreditation, ultimately improving the quality and accountability of higher education.

关键词： Accreditation Higher education Data mining Machine learning Predictive model Decision-making Education quality HEA

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The Stages of Creation of LMS Model 9th

The Stages of Creation of LMS Model

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

作者： Rasulovna, Jamoldinova Odinaxon Boltayevich, Elov Botir Qizi, Primova Mastura Hakim Yuldashevna, Xusainova Zilola Raxmatilloyevich, Aloyev Narzillo Uktambay o'g'Li, Khudayberganov Nizomaddin Tashkent State Univ Uzbek Language & Literature Social Sci & Humanities Dept Alisher Navoi Tashkent Uzbekistan Tech Sci Tashkent State Univ Uzbek Language & Lit Tashkent Uzbekistan Tashkent State Univ Uzbek Language & Literature Dept Computat Linguist & Digital Technol Tashkent Uzbekistan

ISBN: (纸本)9789819732982;9789819732999

The recent developments in the sphere of IT are continuously penetrating into all spheres of human activity, including both social and economic ones. The introduction of IT means in educational process is expected to change approaches, methods and forms of education in the near future. At present, e-learning and distance technologies are being actively introduced as complements to traditional forms of education. Teachers are focused on finding effective models of mixed learning. The expected results can be achieved through full compliance with the requirements and rules of the development, design, and implementation of information systems in the activities of the university management. This article analyzes the steps and stages of creation of LMS model based modern education management systems with themeans of up-to-date technology. When creating LMS systems, the LMS is divided into several component group aspects (users, functions, data, communications). Based on this approach, the LMS allows for the full implementation of processes at all stages from design to support, and the use of standards based on project development and documentation.

关键词： LMS Model E-learning Information system Business process re-engineering Design Digital technology

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How GPUs Kill Threads in Neural Network Training 4th

How GPUs Kill Threads in Neural Network Training

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

作者： Mayta Quispe, Marco Fidel Torres Cruz, Fred Juarez Vargas, Juan Carlos Univ Nacl Altiplano Puno Puno Peru

ISBN: (纸本)9783031686597;9783031686603

The optimization and exploration of computing resources continue significant challenges in challenges in the field of neural network training. This paper present an analysis of the effectiveness of several computational architectures, including Graphics Processing Units (GPUs), Central Processing Units (CPUs), and CPUs using threaded techniques, in supporting neural network training. The research highlights the significant differences in training times across different platforms, demonstrating the effectiveness of GPU-based techniques. In order to guarantee a thorough assessment, the research uses two separate datasets: MNIST(Modified National Institute of Standards and Technology), which has 60,000 photos, and USPS(United States Postal Service), which has 7,291 images. These datasets provide the basis of our empirical work, representing a range of dimensions and complexity. The investigation's findings demonstrate the superiority of GPUs in accelerating neural network training, also provide insightful information on how best to use compute resources for these kinds of jobs. This study offers a thorough understanding of the dynamics involved in neural network training by analyzing the minute variations in performance across various computational architectures. Additionally, it lays the groundwork for future investigations into how to make these training procedures more effective, which might result in faster progress in the field of artificial intelligence.

关键词： GPU Threads CPU Neural networks

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