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

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Business Intelligence System Adoption Project in the Area of Investments in Financial Assets 1

引用

International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Dratwinska-Kania, Beata Ferens, Aleksandra Univ Econ Fac Finance Ul 1 Maja 50 PL-40287 Katowice Poland

ISBN: (数字)9789819984794

ISBN: (纸本)9789819984787;9789819984794

Organizations often adopt business intelligence (BI) systems to improve the standardization and speed of collecting multidimensional information related to their business activity. This study highlights the benefits of implementing a BI system and presents an original project that transforms a traditional information system into a BI system, focusing on investments in financial assets in a hypothetical enterprise. The authors believe this project is unique and valuable because no similar study has been conducted before. The study examines the necessary data using proposals of OLAP cubes and demonstrates the advantages of implementing a BI system, although the research is limited to investments in financial assets due to the complexity of building a comprehensive BI system. The information obtained from the BI system project will aid managerial staff in making effective decisions, which is essential for organizational competitiveness and survival. The study aims to describe the construction and benefits of BI systems and present an original, simplified project of the BI system in an organization related to investments in financial assets. The research methods include a critical literature analysis and a case study. The study provides initial confirmation of the research hypothesis that implementing a BI system positively impacts decision-making processes related to investments in financial assets.

关键词： Business intelligence Financial assets OLAP cubes

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Optimizing Endurance in Fixed Wing UAVs 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Sasane, Atharva Borkar, Srujan Majety, Prithvi Singh, Smriti Shahane, Priti Symbiosis Int Deemed Univ Symbiosis Inst Technol Pune Maharashtra India

ISBN: (数字)9789819713295

ISBN: (纸本)9789819713288;9789819713295

This paper aims to explore the feasibility of current unmanned aerial vehicle (UAV) implementations, focusing on their long-range capabilities and potential for enhanced efficiency. It will also provide designs for one such implementation, in an effort to improve accessibility. By assessing existing UAV systems, this study identifies areas for improvement that could lead to more cost-effective access to this technology. Through a comprehensive analysis, this paper contributes to advancing the understanding of optimizing UAV performance while minimizing financial barriers. The proposed UAV relies on off-the-shelf components and offers flexibility for different scenarios. The UAV relies on the glider archetype, allowing a longer flight time compared with general aircrafts of its size today. An effort has been made to improve the control experience while in flight. This vehicle contains onboard GPS, barometric sensor, accelerometer, gyroscope, as well as a communication module for line-of-sight control. A dual core microcontroller has been used to run an RTOS for future iterations.

关键词： UAV Autonomous Monitoring Traffic Transport Imaging Optimization Return to home (RTH) Wireless Low power Low consumption

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Correlation-Based Feature Selection for Enhanced Arrhythmia Classification

Correlation-Based Feature Selection for Enhanced Arrhythmia ...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Al Khaldy, Mohammad Univ Petra Amman Jordan

ISBN: (纸本)9783031671944;9783031671951

The accurate diagnosis of cardiac arrhythmias relies on analyzing patterns in electrocardiogram (ECG) signals. However, ECG datasets typically contain a large number of input features relative to the sample size, which can negatively impact model performance. This study evaluates feature selection techniques to identify an optimal subset of input features that maximizes arrhythmia classification accuracy. Eight feature selection methods encompassing filters, wrappers, and embedded approaches were compared on the UCI Arrhythmia dataset containing 279 features. The selected feature subsets were evaluated by training three classifiers - random forest, J48, and reduced error pruning tree. Results indicate that correlation-based feature selection (CFS) identified the best feature subset of 32 features, improving classification accuracy over all features by 10 Random forest achieved the highest accuracy of 86.4% with the CFS subset. Redundant and irrelevant features decreased performance for other selection methods. The analysis provides a guideline for applying feature selection in clinical applications and demonstrates methods to improve generalization and prevent overfitting in high-dimensional biomedical datasets.

关键词： Feature Selection Wrapper Method Embedded Method Clinical Data Arrhythmia Disease

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A Numerical Approach for the Fractional Laplacian via Deep Neural networks

A Numerical Approach for the Fractional Laplacian via Deep N...

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Computing Conference

作者： Valenzuela, Nicolas Univ Chile Fac Phys & Math Sci Dept Math Engn Santiago Chile

ISBN: (纸本)9783031622793;9783031622779;9783031622762

In this paper we consider the linear fractional elliptic problem with Dirichlet boundary conditions on a bounded and convex domain D of IRd, with d >= 2. This work is devoted to the approximations of such a PDE solutions via deep neural networks, even if the solution does not have an analytical expression. We have used that the PDE solution has a stochastic representation, and therefore we can use Monte Carlo approximations to generate train data related to the solution. With such a train data we perform a stochastic gradient descent (SGD) like algorithm to find a deep neural network that approximates the PDE solution in the whole domain D. The DNN found will be considered to have a fixed number of hidden layers and neurons per hidden layer. Additionally, we provide four numerical examples with different settings on the boundary condition and source term to test the efficiency of the approximation given by our algorithm, and each example will be studied for many values of alpha is an element of(1, 2) and d >= 2.

关键词： Fractional laplacian Deep neural networks Approximation

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On the Design of Experiments Methodology for the Optimal Design of a New Machinery 10th

On the Design of Experiments Methodology for the Optimal Des...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Veneziano, Salvio De Simone, Marco Claudio MEID4 Via Giovanni Paolo II 132 I-84084 Fisciano Italy Univ Salerno Dept Ind Engn Via Giovanni Paolo II 132 I-84084 Fisciano Italy

ISBN: (纸本)9783031662676;9783031662683

The object of this study concerns the validation of the DOE (Design Of Experiments) methodology applied to the optimal design of new machines. In particular, this technique was tested on an aging test machine for a new class of intelligent railroad seats. The authors intend to implement this technique using the proprietary software Minitab. Instead, Matlab computational software was chosen to emulate the machine in a virtual environment to test the various configurations considered for statistical analysis. Following the numerical analysis, this method was tested on the physical prototype recently built in the Applied Mechanics Laboratory of the Department of Industrial Engineering at the University of Salerno. The use of DOE on the real machine revealed a lack of correlation between the main measured quantities, thus highlighting the incorrect distribution of the assumed transducers. This information allowed to redefine the sensors to be installed, improving the performance of the instrumented seat.

关键词： DOE Minitab Multibody Matlab Dynamics Machines

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Early Detection of Mechanical Faults in Loads Coupled with Asynchronous Electric Motor 4th

Early Detection of Mechanical Faults in Loads Coupled with A...

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

作者： Byou, Abdelilah Derouich, Aziz Saadi, Adil Said, Mahfoud Houssam, Ech-chaouy Abderrahman, El Idrissi Sidi Mohamed Ben Abdellah Univ Higher Sch Technol Ind Technol & Serv Lab Fes 30000 Morocco Sultan Moulay Slimane Univ Polydisciplinary Lab Sci Technol & Soc Khenifra Morocco

ISBN: (纸本)9783031686740;9783031686757

Optimising methods for diagnosing and monitoring asynchronous electric motors (AEM) requires a methodical and integrated approach. This experimental work proposes to adopt the spectral analysis of vibrations based on the Fast Fourier Transform (FFT). It is obvious that the FFT fails to provide temporal information and to manage the identification of several faults with their time of appearance, however it remains the most widely used signal processing technique that provides useful information on frequency content, and it is often adopted in industries with a large number of vibration monitoring points, such as heavy industry plants. This is because FFT can identify and characterise the frequency signatures associated with mechanical faults, such as imbalance and misalignment, providing an in-depth understanding of structural anomalies. By performing a preliminary spectral analysis, the specific frequency characteristics of mechanical defects become clear, enabling early and accurate identification. This approach has several advantages, including greater sensitivity to weak signals and the ability to distinguish mechanical anomalies from normal fluctuations. The adoption of the FFT of the vibration signals from the AEM, in the presence and absence of mechanical faults for an 11 kw machine as part of this experimental work, clearly demonstrates the value of the frequency analysis of vibration signals using the FFT.

关键词： AEM- Mechanical faults- Vibration analysis FFT

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Ethics and Security in the Era of Big Data: Innovative Challenges and Educational Strategies 12th

Ethics and Security in the Era of Big Data: Innovative Chall...

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

作者： Palomino-Flores, Paola Cristi-Lopez, Ricardo Medina La Plata, Edison Paul, David Univ Peruana Ciencias Aplicadas Sch Commun Lima 15023 Peru Univ Andres Bello Sch Educ Santiago 8370134 Chile Univ Peruana Ciencias Aplicadas Business Sch Lima 15023 Peru Univ Penn Business Sch Philadelphia PA 00337 USA

ISBN: (纸本)9783031602146;9783031602153

This study explores the integration of ethical and security principles within the Information Technology (IT) curriculum, focusing on Big Data. It examines key ethical issues like data privacy and management, alongside establishing secure handling guidelines for sensitive information. The research also identifies best practices for educational data protection and potential cybersecurity threats in academic settings. Using a mixed-methods approach combining qualitative and quantitative research, the study analyzes survey responses from 500 systems Engineering students, offering insights into their perceptions of ethical and security training. The findings highlight the need for curriculum innovation that integrates ethical and security education, advocating for case studies and scenario-based learning to equip students with practical data management skills. Furthermore, the study emphasizes the urgency of IT education reform, stressing the inclusion of comprehensive ethical and security training. It also underlines the importance of academia-tech industry collaboration to align educational standards with industry demands, preparing graduates to navigate the ethical and security challenges in the digital world.

关键词： Big Data Ethics Curriculum development

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The Role of Electronic Health Records to Identify Risk Factors for Developing Long COVID: A Scoping Review 12th

The Role of Electronic Health Records to Identify Risk Facto...

引用

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

作者： Santos, Ema Fernandes, Afonso Graca, Manuel Rocha, Nelson Pacheco Univ Aveiro Dept Med Sci Aveiro Portugal Univ Aveiro Dept Med Sci IEETA Aveiro Portugal

ISBN: (纸本)9783031602177;9783031602184

Coronavirus disease 2019 (COVID-19) was considered a global pandemic from December 2019 to May 2023. A subset of COVID-19 patients develops long-lasting sequelae, commonly referred to as long COVID. This scoping review aimed to identify risk factors for long COVID reported in multiple studies and to determine the role of the secondary use of Electronic Health Records to identify these risk factors. An electronic search was conducted on Scopus, PubMed, and Web of Science, and 46 studies were included in this review after the selection process. Thirty-one risk factors were identified, with the most referred ones being female sex, age, severity of infection and obesity. In terms of data collection, Electronic Health Records were used by 63.0% of the studies, although only 21.7% were retrospective studies exclusively based on the secondary use of Electronic Health Records data. These results show that the potential of clinical research based on the secondary use of data collected from Electronic Health Records is not yet fully achieved, despite the respective advantages when compared with other data collection methods such as remote surveys.

关键词： Long COVID Post-COVID-19 sequelae Risk Factors Electronic Health Records

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Value Creation via Blockchain Technology: A Systematic Literature Review and Future Research Agenda 9th

Value Creation via Blockchain Technology: A Systematic Liter...

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

作者： Badi, Sulafa M. British Univ Dubai BUiD Fac Business & Law Dubai U Arab Emirates

ISBN: (纸本)9789819732982;9789819732999

Blockchain technology has unprecedented disruptive potential as a decentralised platform for creating and exchanging value. Through scoping out the theoretical landscape of blockchain-based value systems, this paper aims to provide a clear overviewof blockchain value creation research, analyse the significant contributions, and identify future research directions. An exploratory literature landscaping systematic review involving 78 peer-reviewed journal and conference papers was carried out. The outcome of the systematic reviewis the development of an integrative framework describing value creation via blockchain technology with five elements: value creation dimensions, value proposition, value creation mechanisms (value enablers, drivers, and processes that represent how blockchain stakeholders interact with one another for the creation of value), relational characteristics (such as incentives and governance practices that encourage value creation), and value capture and distribution among blockchain participants. This study is the first to synthesise the current academic developments of blockchain technology from a value standpoint. A focus on value is a step towards a need-driven perspective bywhich blockchain applications are tailored to business objectives, social needs, and public ideals.

关键词： Blockchain technology Literature landscaping systematic review Value Value creation

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Unbiasing on the Fly: Explanation-Guided Human Oversight of Machine Learning Decisions 13th

Unbiasing on the Fly: Explanation-Guided Human Oversight of ...

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13th Computer Science Online Conference

作者： Mamman, Hussaini Basri, Shuib Balogun, Abdullateef Oluwagbemiga Imam, Abdullahi Abubakar Kumar, Ganesh Capretz, Luiz Fernando Univ Teknol PETRONAS Dept Comp & Informat Sci Bandar Seri Iskandar 32610 Malaysia Abubakar Tafawa Balewa Univ Dept Management & Informat Technol Bauchi 740272 Nigeria Univ Brunei Darussalam Sch Digital Sci Ludhiana 1410 Punjab India Western Univ Dept Elect & Comp Engn London ON Canada Yale NUS Coll MCS Program Singapore 138527 Singapore

ISBN: (纸本)9783031702990;9783031703003

The widespread adoption of ML systems across critical domains like hiring, finance, and healthcare raises growing concerns about their potential for discriminatory decision-making based on protected attributes. While efforts to ensure fairness during development are crucial, they leave deployed ML systems vulnerable to potentially exhibit discrimination during their operations. To address this gap, we propose a novel framework for on-the-fly tracking and correction of discrimination in deployed ML systems. Leveraging counterfactual explanations, the framework continuously monitors the predictions made by an ML system and flags discriminatory outcomes. When flagged, post-hoc explanations related to the original prediction and the counterfactual alternatives are presented to a human reviewer for real-time intervention. This human-in-the-loop approach empowers reviewers to accept or override the ML system decision, enabling fair and responsible ML operation under dynamic settings. While further work is needed for validation and refinement, this framework offers a promising avenue for mitigating discrimination and building trust in ML systems deployed in a wide range of domains.

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