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

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Multimodal ML Strategies for Wind Turbine Condition Monitoring in Heterogeneous IoT Data Environments 1

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2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Jameel, Syed Shahryar Raazi, Syed Muhammad Khaliq-ur-Rahman Jameel, Syed Muslim Muhammad Ali Jinnah Univ MAJU Karachi Pakistan Atlantic Technol Univ Galway Ireland

ISBN: (数字)9783031628719

ISBN: (纸本)9783031628702;9783031628719

Addressing the pressing need for efficient wind turbine monitoring in the sustainable energy sector, this paper begins with an extensive literature review focused on condition monitoring techniques specific to wind turbines. This foundational review uncovers significant gaps, particularly in managing diverse and voluminous data streams that are characteristic of wind turbine operations. The core objective of this research is to thoroughly analyze the unique characteristics of heterogeneous data environments in wind turbine monitoring, tackling challenges like data diversity, volume, and reliability, where their effectiveness in interpreting complex data is scrutinized. This analysis provides critical insights into the applicability of these models in practical monitoring situations. Further, the research broadens its scope to assess the implications of these findings within the Artificial Intelligence of Things (AIoT) domain. It highlights the potential of AI and IoT integration in revolutionizing wind turbine monitoring, leading to smarter, more resilient renewable energy systems. The study sets a foundation for future advancements in AIoT, especially in enhancing the efficiency and intelligence of renewable energy infrastructures. It paves the way for the development of more sophisticated AI-driven tools for energy management, envisioning a future where renewable energy systems are managed with greater efficiency and intelligence.

关键词： Artificial Intelligence of Things Renewable Energy Wind Turbines Condition Monitoring Multi-Modal ML

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Kernel Methods for Conformal Prediction to Detect Botnets 1

引用

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

作者： Quang-Vinh Dang Thai-Ha Pham Ind Univ Ho Chi Minh City Ho Chi Minh City Vietnam

ISBN: (数字)9789819984763

ISBN: (纸本)9789819984756;9789819984763

Botnets are networks of compromised computers controlled by malicious actors and are responsible for a wide range of cyberattacks. Detecting botnets is a critical task in cybersecurity, and machine learning techniques have been widely employed for this purpose. In this paper, we present a novel approach for botnet detection based on kernel methods and conformal prediction. Our method leverages the power of kernel functions to capture complex patterns in network traffic data and uses conformal prediction to provide confidence measures for the predictions. Through extensive experiments on real-world datasets, we demonstrate the effectiveness of our approach in accurately identifying botnet activities while maintaining a low false positive rate. Furthermore, we show that our method is robust to concept drift and can adapt to evolving botnet behaviors. Overall, our work contributes to the advancement of machine learning-based botnet detection and provides a reliable tool for safeguarding network systems against botnet threats.

关键词： Botnet Cybersecurity Conformal prediction

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Is It Time for a Borderless Real Estate Platform?

Is It Time for a Borderless Real Estate Platform?

引用

Computing Conference

作者： Odhiambo, Walter Okoth Univ Arkansas Little Rock AR 72204 USA

ISBN: (纸本)9783031622755;9783031622731;9783031622724

The digital transformation of various industries has led to the adoption of responsive software applications that incorporate genuine user feedback and enable end-to-end implementation. While long established in IT, this approach has also been embraced by other sectors like construction. Multi-sided platforms (MSPs) continue to be an important research area. Like global trends, post-COVID-19 migration within the United States has seen people relocating to more affordable states, cities, or even outside the country. Remotework has further enabled this flexibility, resulting in heightened demand for real estate inventories in certain areas over others. This paper hypothesizes that current global conditions necessitate improving the real estate supply chain delivery mechanism through an MSP-based Borderless Real Estate Platform (BRP). It aims to advance comprehension of emerging technological trends in digital transformation, specifically regarding multi-sided platforms. To evaluate this hypothesis, we define the BRP, analyze it with respect to existing MSP research, and conclude based on relevant literature. This leaves room for future research across industries from a global perspective and further BRP design developments.

关键词： Multi-sided platform Construction platform Real estate platform

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The VAST Collaborative Multimodal Annotation Platform: Annotating Values 1

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

作者： Petasis, Georgios Ruskov, Martin Gradou, Anna Kokol, Marko Natl Ctr Sci Res NCSR Demokritos Inst Informat & Telecommun GR 153 10POB 60228 Athens Greece Univ Milan Dept Comp Sci Via Celoria 18 I-20133 Milan Italy Semantika Doo Semantika Res Zagrebska 40a Zagreb 2000 Slovenia

ISBN: (数字)9783031456510

ISBN: (纸本)9783031456503;9783031456510

In this paper, we present the VAST Collaborative, Multimodal, Web Annotation Tool. It is a collaborative, web-based annotation tool built upon the Ellogon infrastructure, adapted to the content creation and annotation needs of digital cultural heritage. With the help of an annotation methodology and guidelines, the tool has been used to analyse and annotate intangible artifacts (mainly narratives) with moral values. This paper presents the tool and its capabilities, and an evaluation study for assessing its usability.

关键词： annotation tools inter-annotation reliability collaborative annotation web-based annotation moral values

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On the Volatility of Functional Costs in E-Health and E-Prescriptions 1

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Goli, Gnana Prakash Migliardi, Mauro Univ Padua Dept Comp Engn I-35131 Padua Italy

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

Self-sovereign identity and blockchain technology are two features that give decentralized e-prescription systems a substantial edge over traditional centralized ones. Secure hashes are used by these systems to guarantee data integrity, improve security, and grant patients total control over their health data. Because they can now access their prescription history, patients are empowered by this decentralization, which encourages patient participation in their care and treatment. Technology also increases patient safety by lowering prescription fraud related to paper prescriptions and enabling safe prescription transfers. Nonetheless, a significant obstacle is the instability of cryptocurrencies utilized for payments, which may have an impact on cost of operations. This article argues for the use of stablecoins and decentralized finance (DeFi) systems as more dependable payment mechanisms and examines how the volatility of popular cryptocurrencies like Ethereum and Bitcoin affects these expenses.

关键词： e-prescriptions DLT Cost Management

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Person Detection for Monitoring Individuals Accessing the Robot Working Zones Using YOLOv8 7th

Person Detection for Monitoring Individuals Accessing the Ro...

引用

7th International Conference on Green Technology and Sustainable Development

作者： Van-Truong Nguyen Cong-Duy Do Tien-Dung Hoang Dinh-Tan Nguyen Ngoc Tuyen Le Hanoi Univ Ind Sch Mech & Automot Engn Hanoi Vietnam East Asia Univ Technol Fac Mech Engn Hanoi Vietnam Ming Chi Univ Technol Dept Elect Engn New Taipei Taiwan Ming Chi Univ Technol Ctr Reliabil Engn New Taipei Taiwan

ISBN: (纸本)9783031761966;9783031761973

In active workshops, methods to warn of dangerous areas are essential to ensure worker safety. However, traditional methods such as having guards, posting warning signs, etc. are not enough. With the strong development of object-tracking technologies, algorithms have achieved high accuracy and are applied in practice. This study proposes the YOLOv8 algorithm to monitor human posture in robot working zones. We use the Shapely library to create warning zones and check for intruders. Finally, the python-telegram-bot library sends a warning about Telegram. The system is tested and evaluated in normal and low-light environmental conditions, with one person or many people. The model achieves good performance, responding in real-time.

关键词： Warning area YOLOv8 Deep Learning Robot

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Reconstruction of One-Dimensional Signals and Two-Dimensional Images Through the Use of Sobolev-Type Orthogonal Moments 4th

Reconstruction of One-Dimensional Signals and Two-Dimensiona...

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

作者： El-khanchouli, Karim Bencherqui, Ahmed Joudar, Nour-Eddine Hafid, Abdelatif Sayyouri, Mhamed Sidi Mohamed Ben Abdellah Univ Natl Sch Appl Sci Engn Syst & Applicat Lab Fes Morocco Sidi Mohamed Ben Abdellah Univ Dept Math Modelling & Math Struct Lab FST Fes Morocco Higher Sch Engn Appl Sci Analyt Lab Fes Morocco

ISBN: (纸本)9783031686740;9783031686757

We propose an innovative approach for the reconstruction of 1D signals and 2D images utilizing Sobolev-type orthogonal moments, specifically Krawtchouk-Sobolev moments KSOMs. This method capitalizes on unique discrete measures, leveraging the connection relations and difference equations that characterize these polynomial families. The weighted polynomials derived from Krawtchouk polynomials KOPs are applied in a sophisticated reconstruction algorithm. This approach significantly enhances accuracy and efficiency compared to traditional techniques, emphasizing the structural relationships and recurrent properties of the polynomials. The efficacy and performance of this technique are demonstrated through rigorous testing, marking a significant advancement in the field of signal processing and digital imaging.

关键词： Orthogonal polynomials discrete Sobolev polynomials difference equation 1D signal reconstruction 2D image reconstruction

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Tumor Volume Measurements in Animal Experiments: Current Approaches and Their Limitations 19th

Tumor Volume Measurements in Animal Experiments: Current App...

引用

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

作者： Puskas, Melania Gergics, Borbala Kovacs, Levente Drexler, Daniel Andras Obuda Univ Univ Res & Innovat Ctr Physiol Controls Res Ctr Budapest Hungary Obuda Univ Appl Informat & Appl Math Doctoral Sch Budapest Hungary

ISBN: (纸本)9783031618567;9783031618574

Animal experiments are often used in cancer research as an alternative to clinical trials to determine the effect of various drugs and other biological conditions on tumor behavior. The tumor volume measurement is necessary in these experiments. The operation of imaging devices is expensive, and it is necessary to anesthetize the animals during the measurement. Anesthesiology induces stress and deviation from homeostatic functioning, which greatly affects the results of the experiment. To address these problems, the digital caliper method, which is safe and cost-effective, is applied to measure tumor volume during in vitro studies. However, it is only rarely possible to accurately measure the volume of the tumor with a digital caliper. It is, therefore, important to examine how we can estimate the three-dimensional volume of the tumor from measurements carried out with a digital caliper. This study summarizes the approximation formulas used in the literature and their scope of use and analyzes the advantages and disadvantages of digital caliper measurements. We aim to highlight the importance of creating a noise model in cancer research that generally describes the difference between real tumor volumes and those measured with calipers.

关键词： tumor measurements animal experiments digital caliper measurements noise

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TPDNet: A Tiny Pupil Detection Neural Network for Embedded Machine Learning Processor Arm Ethos-U55 1

引用

Intelligent systems Conference (IntelliSys)

作者： Fiala, Gernot Ye, Zhenyu Steger, Christian Graz Univ Technol Inst Tech Informat Graz Austria ams OSRAM AG INO Innovat Off Semicond Premstaetten Austria

ISBN: (数字)9783031477157

ISBN: (纸本)9783031477140;9783031477157

Augmented reality and virtual reality (AR/VR) systems contain several different sensors including image sensors for gesture recognition, head pose tracking and pupil/eye tracking. The data of all these sensors must be processed by a host processor in real-time. For future AR/VR systems, new sensing technologies are required to fulfill the demands in power consumption and performance. Currently pupil detection is performed with images on resolutions around 300x300 pixels and above. Therefore, deep neural networks (DNN) need host platforms, which are capable to compute the DNNs with such input resolutions to process them in real-time. In this work, the image resolution for pupil detection is optimized to a resolution of 100x100 pixels. A tiny pupil detection neural network is introduced, which can be processed with the ARM Cortex-M55 and the Embedded Machine Learning (ML) processor Arm Ethos-U55 with a performance of 189 frames per second (FPS) with high detection rates. This allows to reduce the power consumption of the communication between image sensor and host for future AR/VR devices.

关键词： Arm Ethos-U55 Arm M55 Augmented reality Deep neural network Machine learning Neural network processor Pupil detection Virtual reality

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Assessing the Feasibility of Implementing Information systems and Management systems Projects Using Fuzzy Modeling Tools 13th

Assessing the Feasibility of Implementing Information System...

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13th Computer Science Online Conference

作者： Bayramov, Imran Y. Yusifov, Salahaddin I. Mayilov, Rauf A. Azerbaijan State Oil & Ind Univ Azadlig Ave 20 AZ-1010 Baku Azerbaijan

ISBN: (纸本)9783031705946;9783031705953

One of the most pressing issues is to assess the feasibility of the given projects to create an information and management system (IMS). To solve this problem, the training procedure of fuzzy cognitive modeling (FCM) was used. Thus, this method allows searching for the best values of factors that reflect the possibility of realization of projects in the case of available resources, in accordance with the contract for the creation of IMS. A learning algorithm is given here, which includes the stage of processing the values of the parameters of the vertices of the graph representing the FCM and the relationships between them. Thus, the values of the vectors consisting of the vertex parameters of the graph representing the FCM were analyzed and if they satisfy all the given constraints, then it was concluded that the developed FCM ensures the realization of the project to create an IMS with the available resources. Otherwise, if at least one value from the vector of the graph's vertex parameters does not satisfy the given constraints, then it is recommended that it is necessary to change the structure of the FCM, that is, to include the vertices of the graph and the connections between them, or to cancel those connections. #CSOC1120.

关键词： Fuzziness Training Procedure Cognitive Modeling Method Management Fuzzy Cognitive Modeling Information systems

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