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European Conference on Electrical engineering and computer Science (EECS)

作者： Christos Loizou George Evripides Paul Christodoulides Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Faculty of Engineering and Technology Cyprus University of Technology Limassol Cyprus

The intima media thickness (IMT) of the common carotid artery (CCA) as well as texture features extracted from the intima media complex (IMC) of the CCA may be used to evaluate the prevalent clinical cardiovascular disease (CVD) and the risk of stroke. This study investigated the association between the IMT and the texture features of the IMC of the CCA and the prevalent clinical CVD using structural equation modeling (SEM). Six hundred twelve (612) longitudinal-section ultrasound images of the left and right CCA were obtained from 306 subjects (158 men and 148 women), 42 of which had clinical CVD. Each of these images was intensity normalized and despeckled. Forty (40) texture features were extracted from the IMC through a semi-automated segmentation system. To this end, we proposed a new approach on how to analyze the above data and provide an evaluation of the stroke risk. SEM is an elegant procedure employed in this study for a conceptual model of relationships between 7 different factors (unobserved constructs and observable variables) extracted from the IMC ultrasound images. The main findings of this study are: (i) Out of seven IMC texture feature groups (factors) investigated, six of them showed good fit to the conceptual model. (ii) Six hypothesized paths in the conceptual model for the impact of each texture feature group on the IMT were tested. It turned out that five of the chosen factors have a significant impact on IMT. (iii) However, as the fits of both the measurement and the structural models are not so good, the obtained results need to be improved taking certain measures in relation to the SEM. Future work will investigate the relationships between IMC texture features and IMT in relation to CVD and the carotid side.

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Estimating the AGV load and a battery lifetime based on the current measurement and random forest application

Estimating the AGV load and a battery lifetime based on the ...

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IEEE International Conference on Big Data

作者： Krzysztof Hanzel Damian Grzechca Adam Ziebinski Lukas Chruszczyk Artur Janus Department of Telecommunications and Teleinformatics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Distributed Systems and Informatics Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Student of Electrical Engineering Faculty of Electrical Engineering Silesian University of Technology Gliwice Poland

The paper describes the energy consumption from the battery based on the current measurements for various cases, i.e., speed (PWL adjustment) and loads. The main purpose of the research is to have additional and reliable information about power consumption and battery life estimation for autonomous guided vehicles (AGV). The authors propose a two-step algorithm. In the first step, a linear classifier was proposed. Then, the KNN classifier was tested; however, it did not give satisfactory results, so it was finally decided to use the random forest to estimate the load and PWL. The time domain current measurement is evaluated, and the beforementioned algorithms process the selected statistical measures. It has been proven that a two-step algorithm allows for achieving high accuracy. Based on the current observation, the paper is a good starting point for further investigation of the AGV because it is usually implemented in the AGV – so it does not require additional hardware. Moreover, it can lead to better energy management and increase battery lifetime.

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Assessment of Post-Disaster Concerns using Social Network Analysis and Machine Learning: A Study of 2018 Palu Disaster

Assessment of Post-Disaster Concerns using Social Network An...

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International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)

作者： Tyanita Puti Marindah Wardhani Subhajyoti Samaddar Hirokazu Tatano Zulkifli Tahir Sudip Roy Department of Informatics Faculty of Engineering Universitas Hasanuddin Makassar Indonesia Disaster Prevention Research Institute Kyoto University Kyoto Japan Centre of Excellence in Disaster Mitigation and Management (CoEDMM) Department of Computer Science and Engineering Indian Institute of Technology Roorkee India

ISBN: (数字)9798350367928

ISBN: (纸本)9798350367935

Post-disaster needs assessment plays a critical role in developing emergency response programs and disaster preparedness. An assessment of needs identifies possible interventions or assistance and the necessary resources for emergency responses. This emergency need assessment assists stakeholders in defining possible response options, evaluating the priorities of needs of affected communities, and determining what support will be required immediately. The prevalent use of social media in Indonesia highlights its significance as a crucial means of acquiring prompt, effortless, individualized, and geo-specific information regarding the demands and requirements of communities impacted by a calamity. This study aims to analyze the tweets posted by local communities affected by the 2018 Central Sulawesi earthquakes, tsunami, and liquefaction using the Social Network Analysis (SNA) method based on machine learning and natural language processing. Through this analysis, we intend to observe the spatial interaction and relationship among the affected areas of communities for the needs and concerns after the disaster to enhance the relief operation. We found that social media users, government, and humanitarian organizations effectively shared information during the disaster. This study also underlined that the behavioral responses of individuals to disasters were not limited to the disaster-stricken areas but extended far beyond them. This action suggests that they were willing to exhibit a more empathetic, benevolent, and philanthropic demeanor in the face of such traumatic events.

关键词： Social networking (online) Disasters Government Information sharing Machine learning Tsunami Natural language processing Stakeholders Open data Videos

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A Review of Android and iOS Operating System Security

A Review of Android and iOS Operating System Security

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2022 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2022

作者： Khan, Shahnawaz Yusuf, Ammar Haider, Mohammad Thirunavukkarasu, K. Nand, Parma Imam Rahmani, Mohammad Khalid Faculty of Engineering Design and Information and Communications Technology Bahrain Polytechnic Isa Town Bahrain Applied Science University College of Arts and Science Bahrain Saudi Electronic University College of Computing and Informatics Dammam Saudi Arabia Galgotias University Department of Computer Science and Engineering Greater Noida India Sharda University School of Engineering and Technology Greater Noida India Saudi Electronic University College of Computing and Informatics Riyadh11673 Saudi Arabia

ISBN: (数字)9781665469197

ISBN: (纸本)9781665469197

Mobile devices are an inseparable part of our lives. They have made it possible to access all the information and services anywhere at any time. Almost all of the organizations try to provide a mobile device-based solution to its users. However, this convenience has arisen the risk of losing personal information and has increased the threat to security. It has been observed recently that some of the mobile device manufacturers and mobile apps developers have lost the private information of their users to hackers. It has risen a great concern among mobile device users about their personal information. Android and iOS are the major operating systems for mobile devices and share over 99% of the mobile device market. This research aims to conduct a comparative analysis of the security of the components in the Android and iOS operating systems. It analyses the security from several perspectives such as memory randomization, application sandboxing, isolation, encryption, built-in antivirus, and data storage. From the analysis, it is evident that iOS is more secure than Android operating system. However, this security comes with a cost of losing the freedom. © 2022 IEEE.

关键词： Android (operating system)

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Expert System Integrated with Medical Record for Infectious Diseases using Certainty Factor 6

Expert System Integrated with Medical Record for Infectious ...

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6th IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022

作者： Istiadi Sulistiarini, Emma Budi Joegijantoro, Rudy Suksmawati, Affi Nizar Nugroho, Kuncahyo Setyo Akbar, Ismail Widyagama University of Malang Department of Informatics Engineering Malang Indonesia Widyagama Husada College of Health Department of Environmental Health Science Malang Indonesia Gadjah Mada University Faculty of Mathematics and Natural Sciences Yogyakarta Indonesia Brawijaya University Faculty of Computer Science Malang Indonesia Maulana Malik Ibrahim State Islamic University Faculty of Science and Technology Malang Indonesia

ISBN: (数字)9781665497428

ISBN: (纸本)9781665497428

Humans with weak immune systems are very susceptible to infectious diseases. Infectious diseases can cause the risk of premature death if not handled properly. This research integrates an expert system with a health care system to diagnose and treat infectious diseases. The integration system aims to optimize the database of medical records of patients. The result of the integration system is that physicians can use the medical record data in the health care system as initial instructions for examinations, and expert systems can use the medical record data to acquire new knowledge. Tests on the expert system were carried out using the Certainty Factor (CF) method on 35 medical record data. The test results obtained an accuracy value of 80%, which indicates that the expert system can diagnose the disease quite well. © 2022 IEEE.

关键词： Expert systems

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Zero-watermarking of light field images using fractional-order radial harmonic fourier moments and chaotic logistic-may map

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Alexandria engineering Journal 2025年 128卷 597-610页

作者： Mohamed Meselhy Eltoukhy Faisal S. Alsubaei Mohamed M. Darwish Khalid M. Hosny Department of Information Technology College of Computing and Information Technology at Khulais University of Jeddah Jeddah 21959 Saudi Arabia Department of Cybersecurity College of Computer Science and Engineering University of Jeddah Jeddah 21959 Saudi Arabia Department of Computer Science University College of Al Wajh University of Tabuk Tabuk Saudi Arabia Department of Computer Science Faculty of Computers and Information Assiut University Assiut 71516 Egypt Department of Information Technology Faculty of Computers and Informatics Zagazig University Zagazig 44519 Egypt

Unlike traditional images, light field images capture comprehensive scene information, enabling novel post-capture manipulations. However, this very richness makes them vulnerable to tampering. This paper proposes lossless copyright protection of light-field images based on a robust zero-watermarking algorithm without modifying the original image. First, the fractional-order radial harmonic Fourier moments (FrRHFMs) for light-field images were computed accurately. The FrRHFMs and chaotic Logistic and May maps (LOMAS) were combined to produce a light-field images robust zero-watermarking algorithm. Due to the excellent geometric invariance of FrRHFMs and the chaotic system's initial value sensitivity, the proposed algorithm's robustness to geometric attacks and security was improved. The experiments' results demonstrated that this algorithm outperformed other algorithms and was resilient to conventional image processing and geometry attacks.

关键词： Electronic warfare Supply chain security Cyber defense technologies Zero-watermarking Light-field images Fractional-order radial harmonic Fourier moments

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Cybersecurity of Sensors on Smart Vehicles: Review of Threats and Solutions

Cybersecurity of Sensors on Smart Vehicles: Review of Threat...

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International Conference of computer and informatics engineering (IC2IE)

作者： Prasetyo Adi Wibowo Putro Fetty Amelia Jan Pidanic Heru Suhartanto Imam Arif Rahardjo Ejo Imandeka Faculty of Computer Science Universitas Indonesia Depok Indonesia Cryptographic Hardware Engineering Politeknik Siber dan Sandi Negara Bogor Indonesia Faculty of Electrical Engineering and Informatics University of Pardubice Pardubice Czech Republic Department of Electrical Engineering Universitas Negeri Jakarta Jakarta Indonesia

The use of sensors in smart vehicles brings benefits and vulnerabilities. Different kinds of sensors in smart vehicles are vulnerable to cyber-attack. Until now, the investigation of challenges and solutions for in-vehicle cybersecurity hasn't discussed various sensor objects and their correlation. In this study, we studied the cyber security problems of sensors in smart vehicles and how to overcome them. The research was designed as Systematic Literature Review (SLR) using the Kitchenham methodology with modification in the filtering phase using the artificial intelligence application, Elicit, to identify the problems, conclusions, and methodology description. Seventeen publications from 2016 until 2023 were gained from five databases. As a result, we find that the most discussed object related to cybersecurity sensors on smart vehicles are Electronic Control Units. Spoofing and jamming is still the most addressed threat, and machine learning is the most utilized solution to be implemented in detection systems. Advanced detection systems are incorporating updated attack models. We also suggest using updated attack models and machine learning algorithms to ensure the safety and security of smart vehicle technology. All identified sensor technology correlated using mind maps under the Intelligent Transport System theory.

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A Two-Tier Anomaly-based Intrusion Detection Approach for IoT-Enabled Smart Cities

A Two-Tier Anomaly-based Intrusion Detection Approach for Io...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Mosab Hamdan Arwa M. Eldhai Samah Abdelsalam Kifayat Ullah Ali Kashif Bashir MN Marsono Fabio Kon Daniel Macêdo Batista Department of Computer Science University of Sao Paulo (USP) Brazil Faculty of Engineering University of Science and Technology Sudan Faculty of Mathematical Sciences and Informatics Khartoum University Sudan Department of Computing and Mathematics Manchester Metropolitan University UK Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

The Internet of Things (IoT), like other network infrastructures, requires Intrusion Detection Systems (IDSs) to be protected against attacks. When deploying an IDS in IoT-based smart city environments, the balance between latency and node capacity must be considered, which justifies a distributed IDS with specific classifiers based on the location of the system processing nodes. This paper proposes a two-level classification technique for collaborative anomaly-based IDSs deployed on fog and edge nodes. A Gradient Boosting Classifier (GBC) is used in the lower layer classifier at the edge, while a Convolutional Neural Network (CNN) is used in the upper layer classifier at the fog. Experimentation has demonstrated that the suggested IDS architecture outperforms previous solutions. For instance, in some scenarios, when comparing our proposal with Random Forest, the former obtained an accuracy equal to 99.1%, while the latter obtained 95.3%. Furthermore, our proposal can better select the most important network traffic features, reducing 76% of the data to be analyzed and improving privacy.

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A Dynamic Optimization Framework for Computation Rate Maximization in UAV-Assisted Mobile Edge Computing

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IEEE Transactions on Vehicular Technology 2025年

作者： Chen, Yang Pi, Dechang Yang, Shengxiang Xu, Yue Wang, Bi Qin, Shuo Wang, Yintong Xi'an University of Science and Technology Artificial Intelligence and Computer Science Xi'an China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China De Montfort University School of Computer Science and Informatics LeicesterLE1 9BH United Kingdom Jiangxi University of Science and Technology Faculty of Information Engineering Ganzhou China Xi'an University of Posts and Telecommunications School of Computer Science and Technology Xi'an China Nanjing Xiaozhuang University School of Information Engineering Nanjing China

Mobile edge computing (MEC) significantly boosts the computing power and reduces the energy consumption of Internet of Things (IoT) devices, serving as a valuable complement to cloud computing. The application of unmanned aerial vehicle (UAV) for MEC systems can effectively alleviate the issue of insufficient or damaged communication facilities in remote areas, further expanding the scope of MEC applications. In this article, we present a system model for UAV-assisted wireless-powered MEC systems in a dynamic environment with the objective of maximizing the computation rate of user devices. Due to the complexity of the optimization objective in dynamic environments, we propose a swarm intelligence-based optimization framework with a mechanism for responding to environmental changes, which is intended to enhance population diversity in both static and dynamic environments with the aim of overcoming premature convergence. We integrate particle swarm optimization and harmony search into the proposed framework, naming them DOPSO and DOHS, respectively. Simulation results for two offloading modes in UAV-assisted MEC systems indicate that the proposed framework significantly outperforms other dynamic optimization algorithms. © 1967-2012 IEEE.

关键词： Energy utilization

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Are University Students Independent: Twitter Sentiment Analysis of Independent Learning in Independent Campus Using RoBERTa Base IndoLEM Sentiment Classifier Model

Are University Students Independent: Twitter Sentiment Analy...

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2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021

作者： Sandra, Lidia Marcel Gunarso, Gatot Fredicia Riruma, Olfien W Psychology Department Faculty of Psychology Krida Wacana Christian University Jakarta11470 Indonesia Information System Department Krida Wacana Christian University Jakarta11470 Indonesia Management Department Faculty of Economics and Business Krida Wacana Christian University Jakarta11470 Indonesia Informatics Faculty of Engineering and Computer Science Krida Wacana Christian University Jakarta11470 Indonesia

ISBN: (纸本)9781665405447

Higher education is one of the fields that is affected by the COVID-19 pandemic. One of the regulations in Indonesian higher education is Merdeka Learning-Independent Campus (MB-KM). In this research article we are aiming to do an analysis of the sentiment using Twitter as the dataset in order to find out the sentiment of university students towards the program. The analysis was being done using RoBERTa Base IndoLEM Sentiment Classifier Model. With the total number of more than 30 thousand positive sentiments and almost 20 thousand negative sentiments found. The result of the model shows that it achieved an accuracy of 91.73%, with a precision of 83.33%, recall 89.74%, and a harmonic mean of the two (F1 score) of 86.42%. Based on the analysis, it also shows the distribution of the sentiment is 63.0% of positive sentiment and 37.0% of negative sentiments. This paper shows that there are more positive sentiments than the negative one. © 2022 IEEE.

关键词： Sentiment analysis

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