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IEEE World Forum on Internet of Things (WF-IoT)

作者： Giacomo Neri Federico Montori Lorenzo Gigli Luca Bedogni Marco Di Felice Luciano Bononi Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center in Electronic Systems University of Bologna Italy Department of Physics Informatics and Mathematics University of Modena and Reggio Emilia Italy

The recent years have witnessed the rise of an enormous number of software algorithms that implement pe-dometers (or step counters), which led to the development of several context-aware IoT-based smartphone apps for sports and healthcare, among others. While the number of scientific works in this context is high, there is no comparison study that analyzes the different proposal at implementation level. In this paper we first perform a literature review of software implementations of pedometers for smartphones and then classify them into a taxonomy. With this, we highlight the similarities of their scheme, which is based on a number of defined steps to be applied in a pipeline. We then develop a smartphone application that implements all the configurations of these steps found in literature and evaluates them in various scenarios. Finally, we present comparative results obtained by running extensive and real tests that show the importance of a carefully designed filtering step.

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Comparative Analysis of Network Congestion on IP and Named Data Network

Comparative Analysis of Network Congestion on IP and Named D...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Hasan Nur Arifin Nana Rachmana Syambas Jupriyadi Adi Sucipto Eki Ahmad Zaki Hamidi School of Electrical and Informatics Engineering Institut Teknologi Bandung Bandung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia

Today's data communication needs have shifted from client-server data communication to peer-to-peer. The user's focus is currently on the immediately requested data or the so-called Named Data Network (NDN). Changes to the nature of the app, user needs, and usage patterns have changed significantly, and apps on networks like YouTube, Facebook, and other social networks have revolutionized the idea of user- generated content. One of the problems in the network is network congestion or network failure. Network congestion occurs due to the need for network resources exceeding the capacity of network resources. When network congestion occurs, the NDN forwarding mechanism facilitated by FIB on the IP router cannot detect the congestion condition and will still use the same path. At the same time, the NDN router can detect congestion conditions and react by using alternative paths. The simulation results show that on the NDN router, the forwarding mechanism can maximize the use of link bandwidth faster than the forwarding mechanism on the router-based IP network. In the topology designed, NDN can achieve maximum bandwidth in the 3rd second compared to IP in the 5th second.

关键词： Video on demand Social networking (online) Network topology Simulation Bandwidth Topology Peer-to-peer computing

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Vehicular Ad-hoc Network (VANET) – A Review

Vehicular Ad-hoc Network (VANET) – A Review

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Communication and Information Technologies (IICCIT), Iraqi International Conference on

作者： Ahmed Ghassan Hameed Mahmoud Shuker Mahmoud Computer Sciences Department of Informatics Institute for Postgraduate Studies Al-Khawarizmi College of Engineering University of Baghdad Baghdad Iraq Al-Mansour University College Baghdad Iraq

ISBN: (纸本)9781665472210

This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.

关键词： Cellular networks Privacy 5G mobile communication Scalability Vehicular ad hoc networks Routing protocols Information and communication technology

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Seeking the Necessary and Sufficient Causal Features in Multimodal Representation Learning

arXiv

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arXiv 2024年

作者： Chen, Boyu Liu, Junjie Li, Zhu Yang, Mengyue Institute of Health Informatics University College London United Kingdom Department of Aeronautics Imperial College London United Kingdom Gatsby Computational Neuroscience Unit University College London United Kingdom Department of Computer Science University College London United Kingdom School of Engineering Mathematics and Technology University of Bristol United Kingdom

Probability of necessity and sufficiency (PNS) measures the likelihood of a feature set being both necessary and sufficient for predicting an outcome. It has proven effective in guiding representation learning for unimodal data, enhancing both predictive performance and model robustness. Despite these benefits, extending PNS to multimodal settings remains unexplored. This extension presents unique challenges, as the conditions for PNS estimation—exogeneity and monotonicity—need to be reconsidered in a multimodal context. We address these challenges by first conceptualizing multimodal representations as comprising modality-invariant and modality-specific components. We then analyze how to compute PNS for each component while ensuring non-trivial PNS estimation. Based on these analyses, we formulate tractable optimization objectives that enable multimodal models to learn high-PNS representations. Experiments demonstrate the effectiveness of our method on both synthetic and real-world data. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

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By Machine Learning Techniques Predicting Post-COVID-19 Condition

By Machine Learning Techniques Predicting Post-COVID-19 Cond...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Pei-Rong Huang Chih-Hung Chang Wen-Ching Chen Che-Lun Hung Po-Yu Liu Ting-Kuang Yeh Hsiu-Wen Wang Yu-Chun Yen William Cheng-Chung Chu Dept. of Computer Science and Communication Engineering Providence University Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taiwan Division of Infectious Diseases Taichung Veterans General Hospital Taiwan Clinical Information Department Quality Management Center Taichung Veterans General Hospital Dept. of Computer Science Tunghai University Taiwan

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

As the COVID-19 pandemic continues, a growing number of recovered patients report persistent symptoms such as fatigue, muscle weakness, sleep issues, anxiety, and depression, lasting months or even over a year. Severe cases often show significant lung damage and sometimes reduced kidney function. This study examines a dataset from recovered COVID-19 patients, using machine learning to assess the likelihood of developing Post-COVID-19 conditions. We applied several models, including XGBoost, Decision Trees, and Random Forest, to predict outcomes based on data from a specific hospital. Our approach included detailed data preprocessing-filling in missing values, feature engineering, and standardizing data to improve model accuracy and applicability. Results showed the Random Forest model as the most accurate, demonstrating the power of machine learning in making precise predictions from complex health data. Feature importance analysis revealed critical factors predicting Post-COVID-19 conditions, offering vital guidance for healthcare professionals in managing recovered patients.

关键词： COVID-19 Accuracy Pandemics Lung Predictive models Muscles Data models

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Identification of Images in Mechatronics through a Neural Network

Identification of Images in Mechatronics through a Neural Ne...

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2020 International Multi-Conference on Industrial engineering and Modern Technologies, FarEastCon 2020

作者： Soldatov, G. Ruchkin, V. Solovev, Denis B. Ryazan State University Department of Informatics Computer Engineering and Informatics Teaching Methods Ryazan Russia Vladivostok Branch of Russian Customs Academy City of Vladivostok Russia

ISBN: (纸本)9781728169514

The article is a continuation of the study of the use of neural networks and image identification for work in industries using conveyor means for transporting and sorting goods. Optimization of production, namely the sorting part, allows not only saving man-hours, but also increasing the overall productivity of transportation units. © 2020 IEEE.

关键词： Conveyors

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Theoretical and Numerical Investigation of Acoustic Cavitation Bubble Based on the Impact of Ultrasound Frequency

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Bulletin of the Russian Academy of Sciences: Physics 2023年第Suppl 3期87卷 S341-S347页

作者： Ahmed K. Abu-Nab Abu-Bakr, Ali F. Zain Abu Shaeer Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom32511 Egypt Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Moscow oblast Dolgoprudny141700 Russia Department of Basic Science Higher Institute of Engineering and Technology Kafr El Sheikh33511 Egypt

Abstract: Acoustic cavitation is the expansion and contraction of existing microbubbles in liquids brought on by an ultrasonic field. The dynamics of oscillations at higher pressures and temperatures when the cavitation bubbles collapse can be used to characterize cavitation dynamical behavior. This work deals with the theoretical and numerical investigation of acoustic cavitation in viscoelastic media considering the influence of ultrasound frequency. An acoustic pressure equation combined with a modified Rayleigh–Plesset equation forms the theoretical framework for ultrasound cavitation dynamics. The numerical solutions of the given cavitation bubble model were obtained taking into account the effect of acoustic pressure, using the exponential B-Spline collection method. The dynamics of the cavitation bubbles’ radius and the internal pressure of acoustic cavitation were examined at different values of viscosity and the impact of physical parameters on the monatomic, diatomic, and adiabatic gas-filled spherical bubble’s collapse dynamics for (k = 7/5, 5/3, 1) respectively. © Pleiades Publishing, Ltd. 2023. ISSN 1062-8738, Bulletin of the Russian Academy of Sciences: Physics, 2023, Vol. 87, Suppl. 3, pp. S341–S347. Pleiades Publishing, Ltd., 2023. ISSN 1062-8738, Bulletin of the Russian Academy of Sciences: Physics, 2023. Pleiades Publishing, Ltd., 2023.

关键词： Dynamics

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3D Modeling Surveying Tasks in Photogrammetry

3D Modeling Surveying Tasks in Photogrammetry

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2020 International Russian Automation Conference, RusAutoCon 2020

作者： Izvozchikova, V.V. Shardakov, V.M. Mezhenin, A.V. Orenburg State University Department of Informatics Orenburg Russia Itmo University Faculty of Software Engineering and Computer Engineering Saint-Petersburg Russia

ISBN: (数字)9781728161303

ISBN: (纸本)9781728161303

The research is aimed at the development of virtual environments of various configurations created by means of 3D computer modeling in such areas as photogrammetry, computer vision systems, robotics at the design stages of devices and systems. In addition, virtual simulators simulating real operating conditions, it is proposed to use for testing and modeling methods of shooting mobile video systems. It is assumed that the means of 3D-graphics emulates not only the environment, shooting conditions, but also the video systems themselves: means of technical vision, onboard cameras of robots and UAVs. The use of such simulators will allow to create, improve and test various algorithms of applied intelligent systems without creating complex expensive stands, will save time for various experiments. The article deals with the evaluation of the quality of recognition and reconstruction systems using a polygonal grid as a data representation. The results of testing these methods: the use of virtual environments and the assessment of the similarity of the polygon meshes. At the stage of segmentation and finding the vertices and segments of the objects under study demonstrated the use of both real images obtained by a real camera and synthesized images. During the reconstruction phase, a set of synthesized images was also used to test one of the reconstruction systems. To assess the similarity of polygonal objects based on the Hausdorff dimension, the corresponding functions were developed and the result of their work is given. © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Detection of Railroad Anomalies using Machine Learning Approach 8

Detection of Railroad Anomalies using Machine Learning Appro...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Nugraha, Ade Chandra Supangkat, Suhono Harso Nugraha, Igb Baskara Trimadi, Harno Purwadinata, Awan Hermawan Sumarni Sundari, Santi School of Electrical Engineering and Informatics Bandung Institute of Technology Department of Computer Engineering and Informatics Bandung State of Polytechnic Bandung Indonesia Smart City and Community Innovation Center Bandung Institute of Technology Bandung Indonesia Director of Railway Infrastructure Directorate of Railway Infrastructure Ministry of Transportation Jakarta Indonesia PT Kereta Api Indonesia Managing Director of Infrastructure Bandung Indonesia

ISBN: (纸本)9781665416979

Maintenance of assets owned by an organization or company is an activity that will never stop. From the time of implementation, maintenance will be more optimal if it is carried out before the asset is in a damaged condition or cannot operate. Pro-active repair model is proven to reduce 15-60% of operational costs. The existence of technology and computing models currently supports big data processing, both in the form of transactional data, historical data and statistical data. The asset maintenance cycle transformed into an autonomous and integrated system, will assist in the decision-making process. A machine learning approach that is supported by big data analysis is one solution that can realize the predictive maintenance process. To accurately predict the condition of critical components, it can be started with data collection, followed by detecting normal and abnormal behavior, and continued by training algorithms to make predictions. Detection of railroad anomalies is used as the initial process in the predictive maintenance of railroads. The process of detecting railroad anomalies can be done by comparing the lateral, longitudinal and vertical acceleration from the sensing results through the accelerometers on both sides of the train wheels. Differences will pay attention to the data acceleration draft rail geometry either angkatan or listringan. The results of rail anomaly detection will indicate the rail maintenance process that can be carried out immediately. © 2021 IEEE.

关键词： Railroads

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Strategic Signaling for Utility Control in Audit Games

arXiv

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arXiv 2022年

作者： Chen, Jianan Hu, Qin Jiang, Honglu The Department of Computer and Information Science Indiana University Purdue University IndianapolisIN United States The Department of Informatics and Engineering Systems The University of Texas Rio Grande Valley BrownsvilleTX United States

As an effective method to protect the daily access to sensitive data against malicious attacks, the audit mechanism has been widely deployed in various practical fields. In order to examine security vulnerabilities and prevent the leakage of sensitive data in a timely manner, the database logging system usually employs an online signaling scheme to issue an alert when suspicious access is detected. Defenders can audit alerts to reduce potential damage. This interaction process between a defender and an attacker can be modeled as an audit game. In previous studies, it was found that sending real-time signals in the audit game to warn visitors can improve the benefits of the defender. However, the previous approaches usually assume perfect information of the attacker, or simply concentrate on the utility of the defender. In this paper, we introduce a brand-new zero-determinant (ZD) strategy to study the sequential audit game with online signaling, which empowers the defender to unilaterally control the utility of visitors when accessing sensitive data. In addition, an optimization scheme based on the ZD strategy is designed to effectively maximize the utility difference between the defender and the attacker. Extensive simulation results show that our proposed scheme enhances the security management and control capabilities of the defender to better handle different access requests and safeguard the system security in a cost-efficient manner. Copyright © 2022, The Authors. All rights reserved.

关键词： Game theory

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