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

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Deep Learning Techniques for Predicting Hypoglycemic Events in Diabetic Patients 1

引用

16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Pujol, Francisco A. Ramirez, Tamai Mora, Higinio Univ Alicante Dept Comp Technol & Computat Alicante Spain

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

This study investigates the application of deep learning, particularly Recurrent Neural networks (RNNs), to predict hypoglycemic events in diabetic patients. Using continuous glucose monitoring data, the research aims to improve patient comfort and reduce the need for emergency interventions. Deep learning models are trained on high-quality, real-world data, focusing on short-term prediction horizons to enable timely preventive actions. The results demonstrate the potential of these models to accurately predict hypoglycemia, significantly improving diabetes management and patient quality of life. This research contributes to the field of Ambient Assisted Living (AAL) by integrating advanced AI techniques into chronic disease management, highlighting the significant role of AI and machine learning in healthcare innovation.

关键词： Hypoglycemia Prediction Deep Learning Recurrent Neural networks Continuous Glucose Monitoring Ambient Assisted Living

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Assessing Users' Resistance Towards a New Information System: An Empirical Study Based on Status Quo Bias 13th

Assessing Users' Resistance Towards a New Information System...

引用

13th Computer Science Online Conference

作者： Youssef, Abdelrahman Hajek, Petr Univ Pardubice Fac Econ & Adm Sci & Res Ctr Studentska 84 Pardubice 53210 Czech Republic

ISBN: (纸本)9783031702846;9783031702853

Upgrading IT infrastructure to enable additional business benefits is increasingly common and critical today, accelerated by the Covid-19 pandemic and the shift towards digitization, especially in medium and large enterprises. Change often entails challenges from the user perspective, which we call user resistance. In this paper, we therefore examine the drivers of user acceptance and resistance to the introduction of a new information system in order to recommend better ways of managing the implementation process. We do so by developing a model to test user resistance in a large enterprise with global setting for a large-scale CRM information system change by integrating the literature on technology acceptance and user resistance with the status quo bias perspective. The status quo bias theory can help understand the user decision-making process that results in acceptance or rejection of change. Our results show that switching costs, switching benefits, and organizational support play key roles in the user decision-making process. Switching costs have a positive effect on user resistance towards a new information system, switching benefits have a positive effect on perceived value and a negative effect on user resistance, while organizational support has an indirect effect on user resistance through its negative effect on switching costs.

关键词： Information system Digitization CRM User resistance User acceptance Status quo bias theory Change management

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Artificial Intelligence in Small and Medium-Sized Enterprises: Requirements and Barriers 1

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3rd International Symposium on Industrial Engineering and Automation

作者： Gruenbichler, Rudolf Salimbeni, Sergio Univ Technol Fac Mech Engn & Econ Sci Inst Business Econ & Ind Sociol Graz Austria Univ Salvador Fac Ingn Inst Invest Ciencia & Tecnol Buenos Aires DF Argentina

ISBN: (数字)9783031704659

ISBN: (纸本)9783031704642;9783031704659

Small and medium-sized enterprises (SMEs) are the backbone of the economy and in recent years have become the focus of several studies. To promote intelligent and sustainable growth, research and innovation projects are encouraged to create a favorable ecosystem. SMEs are generally adaptable and innovative in terms of their processes and products. Due to the continued competitive pressures that small organizations endure, they are gradually becoming more proactive when it comes to innovation. Digital technologies are changing society and the production sector, and Industry 4.0 (I4.0) marked a new era. The basic idea of I4.0 is automation and comprehensive connectivity, both vertical and horizontal, connecting machines, products and people throughout the entire value chain. Many SMEs began to implement technologies for smart and connected manufacturing and operation systems. The application of digital techniques to companies has had an important effect on the way of living and working. The use of artificial intelligence (AI), virtual reality and robots, among others, is generating different work modalities, and, therefore, education and training. That is why it is intended, from now on, that I4.0 focus on people and sustainability, which is beginning to be known as Industry 5.0 (I5.0). The aim of this work is to be able to answer two important questions: what obstacles to the implementation of AI face SMEs in the manufacturing sector and what requirements they must meet to adopt it. For this purpose, a bibliographic review and five qualitative studies were carried out in Argentina.

关键词： Industry 5.0 Manufacturing Qualitative survey

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Demystifying Complex Algorithms: A Visual Guide Through the DSA Visualizer 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Matalia, Jeet Kathiriand, Shreya Patel, Priyanka Charotar Univ Sci & Technol CHARUSAT Chandubhai S Patel Inst Technol Fac Engn & Technol Smt Kundaben Dinsha Patel Dept Informat Technol Changa 388421 Gujarat India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

The foundation of computer science is made up of data structures and algorithms (DSA), which are necessary for creating effective software solutions and resolving challenging issues. But learning the nuances of DSAs can be difficult and frequently poses a big barrier to entry for both programmers and students. DSA Visualizers have become indispensable resources for improving the acquisition and comprehension of these important ideas in response to this challenge. This paper focuses on the visualization of data structures and algorithms. A web application has been developed to help students understand step-by-step working of different data structures and algorithms. Aim behind implementation of this paper is to make a clear understandability of various algorithms of data structures. This web app will simulate the data structure operations such as searching and sorting. In array, stack, queue, and linked list as well. Data structure and algorithm learning has been made easier thanks in large part to DSA Visualizers. Their visual and interactive method breaks down difficult ideas into easily understood models, allowing students to become more proficient in problem-solving and programming. DSA Visualizers are invaluable resources that help people of all skill levels, from beginners to experts in programming, understand DSAs, and make it easier to use them in real-world computer science applications.

关键词： Data structure and algorithm Analysis of algorithm Complexity and applications Visual representation Searching and sorting algorithm Algorithm design

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Heart Diseases Classification by ECG Trace Images Using Deep Learning 4th

Heart Diseases Classification by ECG Trace Images Using Deep...

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

作者： Ali, Sajad M. Daway, Hazim G. Kadhim, Ahlam M. Mustansiriyah Univ Coll Sci Dept Phys Baghdad Iraq

ISBN: (纸本)9783031686498;9783031686504

Recently, many deep learning algorithms have emerged as advanced techniques in the medical field for diagnosing diseases, including heart disease. In this study, an approach was followed that is based on electrocardiogram (ECG) images to detect different heart diseases. Pre-processing was performed for the data images using morphology technology to remove lines from the background ECG paper image to obtain an image containing only the changes of electrical activity for the potion's heart. The pre-processed data images are trained at a rate of 80% of each class data image in the training stage and 20% of each class image used for the testing stage in the efficiency evaluating stage of each model. Seven classification models have been proposed in binary classification. Models 1-7 have been trained to classify the natural ECG case (Nrm) with the other diseases. Models' efficiency is calculated using four measures, where the accuracy reaches 100%, the precision reaches 100%, the specificity is 100%, and the f1-score is 100%. For models 6 and 7, the results of the accuracy reached (88.1366 and 91.0978)%, precision (80.7443 and 91.0834)%, specificity (79.1734 and 88.8665)%, and f1-score (79.4476 and 89.8999) %. The proposed diagnostic system is fast, accessible, more sensitive, and harmless. It is also more cost-effective than any other diagnostic method.

关键词： CNN Deep Learning ECG images pre-processing data

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Uncovering Dark Patterns - Learning Through Serious Gameplay About the Dangers of Sharing Data 1

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

作者： Tjostheim, Ingvar Wales, Chris Waterworth, John A. NLA Hauge Sch Management Oslo Norway Umea Univ Umea Sweden

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

Dark patterns refer to tricks used in websites and apps to make you do things that you do not intend to do. This paper presents the board-game Dark Pattern, in which players install apps, draw dark patterns cards, and make choices about the sharing of personal data. To win the game, a player must share as little data as possible and play cards that punish other players. Two groups, the first with 56 students and the second with 45 students, played the game and then answered a survey with questions controlling their knowledge about the dark patterns types featured in the game. In addition, a further 50 students answered the same survey without playing the game. In this paper we present key findings about the dark patterns knowledge generated by playing the game. Then we present an exploratory analysis using Partial Least Square - Structural Equation modelling (PLS-SEM). We analysed whether dark patterns knowledge and risk perception, the likelihood of negative incidents due to data sharing, could predict the players behavioural intention to take proactive privacy steps. The two PLS-SEM models have a variance explained (R-2) of 0.34 and 0.35 indicating that approximately 35% of the variance could be accounted for by the two variables included in the model. Taken together, the analyses indicated that playing the Dark Pattern game had a positive effect on behavioural intention to proactive privacy steps as a result of by playing the game.

关键词： Serious games learning user-test exploratory study dark patterns sharing of personal data partial least square modelling

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How to Verify Validity of Non-trivial Logical Syllogisms

How to Verify Validity of Non-trivial Logical Syllogisms

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Murinova, Petra Fiala, Karel Univ Ostrava Inst Res & Applicat Fuzzy Modeling Ostrava Czech Republic

In this publication we will focus on the presentation of several methods by which we are able to verify the validity of generalized Peterson syllogisms. We will focus on a special group of so-called non-trivial syllog... 详细信息

ISBN: (纸本)9783031671913;9783031671920

关键词： Peterson's syllogisms Peterson's rules Peterson's square of opposition Peterson's rules based on grades

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Fuzzy 7x6 Matrix Model for Strategic Enterprise Analysis

Fuzzy 7x6 Matrix Model for Strategic Enterprise Analysis

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Nedosekin, A. Malyukov, Y. Silakov, A. Abdoulaeva, Z. LLC Inst Financial Technol St Petersburg 194017 Russia Kosygin State Univ Russia Moscow 119071 Russia North Western State Med Univ St Petersburg 195067 Russia

ISBN: (纸本)9783031671913;9783031671920

Goal. The report introduces a new 7x6 matrix model for comprehensive strategic analysis of an enterprise. Methodology. The 7x6 matrix model is a development of a similar 4x6 matrix model and involves an increase in the number of strategic perspectives due to a more detailed analysis of the relationships between the company and its key stakeholders. Along the rows of the matrix are strategic perspectives, and along the columns are strategic maps: Threats, Opportunities, BSC, Risks, Chances, Decisions. At the intersection of the rows and columns of the matrix, key indicators of the company's performance are located in the form of fuzzy interconnected linguistic variables. The information basement of the matrix contains all quantitative measurements for the enterprise, which then undergo a fuzzy fication procedure. Result. A method for constructing a 7x6 matrix is demonstrated using a simple example. Conclusion. The 7x6 matrix is a mathematical model of a class of enterprise cybernetic systems and has all the properties of models of this class, including the property of homeostasis.

关键词： 7x6 Matrix Strategic Perspectives Strategic Maps Linguistic Variables Fuzzy Connections

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Quantum Circuits for Fixed Matching Substring Problems

Quantum Circuits for Fixed Matching Substring Problems

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Computing Conference

作者： Cantone, Domenico Faro, Simone Pavone, Arianna Viola, Caterina Univ Catania Catania Italy Univ Palermo Palermo Italy

ISBN: (纸本)9783031622717;9783031622694;9783031622687

Quantum computational models enable the design of algorithms that are often significantly more efficient than their most competitive counterpart classical solutions. Recently, strides have been made to take advantage of the quantum computational framework in tackling problems arising in the context of text processing. Our work fits in such a research direction. We focused on challenges arising from string comparison problems and, specifically, on the alignment of fixed-length substrings that are found within two input strings. To be precise, given two input strings, x and y, both of length n, and a value d <= n, we want to verify the following conditions: the existence of a common prefix of length d, the presence of a common substring of length d starting at position j (with 0 <= j < n) and, the presence of any common substring of length d starting at the same position of both strings. Such problems find applications as sub-procedures in a variety of problems concerning text processing and sequence analysis. Notably, our approach yields polylogarithmic solutions, a stark contrast to the linear complexity inherent in the best classical alternatives.

关键词： Quantum computing Reversible circuits String matching

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Semantic State Prediction in Robotic Cloth Manipulation 1

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Intelligent systems Conference (IntelliSys)

作者： Tzelepis, Georgies Borras, Julia Aksoy, Eren Erdal Alenya, Guillem UPC CSIC Inst Robot & Informat Ind Llorens & Artigas 4-6 Barcelona 08028 Spain Halmstad Univ Ctr Appl Intelligent Syst Res Halmstad Sweden

ISBN: (数字)9783031477188

ISBN: (纸本)9783031477171;9783031477188

State estimation of deformable objects such as textiles is notoriously difficult due to its extreme high dimensionality and complexity. Lack of data and benchmarks is another challenge impeding progress in robotic cloth manipulation. In this paper, we make a first attempt to solve the problem of semantic state estimation through RGB-D data only in an end-to-end manner with the help of deep neural networks. Since neural networks require large amounts of labeled data, we introduce a novel Mujoco simulator to generate a large-scale fully annotated robotic textile manipulation dataset including bimanual actions. Finally, we provide a set of baseline deep neural networks and benchmark them on the problem of semantic state prediction on our proposed dataset.

关键词： Robotics Simulation State estimation Deformable objects

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