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2023 IEEE Symposium on computers and Informatics, ISCI 2023

作者： Momo, Mhd Adel Karim, Hezerul Abdul Sy, Michael Aaron Albunni, Ahmad Tan, Myles Joshua Toledo Aldahoul, Nouar Fleet Management Systems & Technologies Turkey Multimedia University Faculty of Engineering Cyberjaya Malaysia University of St. la Salle College of Engineering and Technology Bacolod6100 Philippines Istanbul Aydin University Istanbul Turkey New York University Computer Science Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350302363

Internet has become a main source of information for people in numerous areas. However, internet can be useful or harmful according to types of contents exposed. When the visual sexual and violent contents are available, the danger targets children and youths and causes a damage in their mental health. Consequently, content moderators are required to be employed in all websites and social media platforms. Several companies involve human to review, filter, and edit visual sexual and violent contents. However, manual reviewing and filtering is costly and tough. Therefore, big companies such as Amazon and Microsoft used machine learning based solutions to automate the content moderation process. This paper proposes a new solution for content moderation that targets sketch images specifically. Three state of the art models including EfficientNetB7 convolutional neural network (CNN), vision transformer, and convolution and attention (CoAtNet) have been employed for this task to detect nudity and pornography in sketch images. A novel benchmarking dataset including 4417 sketch images were used for training and testing. It was found that our proposed methods outperformed the cloud-based content moderation solutions such as AWS, and Microsoft Azure in terms of accuracy (97%) and F1-score (97%). © 2023 IEEE.

关键词： Convolution

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Ratiometric System based on an Ionic Liquid-Modified Colorimetric Dye for Enhanced Carbon Dioxide Sensing

Ratiometric System based on an Ionic Liquid-Modified Colorim...

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IEEE Sensors Applications Symposium, SAS

作者： Xavier Lopes Luis C. C. Coelho Pedro A. S. Jorge João P. Mendes FCUP - Faculty Of Sciences of University of Porto Porto Portugal Centre for Applied Photonics INESCTEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (数字)9798350369250

ISBN: (纸本)9798350369267

Carbon dioxide (CO2) holds paramount significance in nature, serving as a vital component in Earth's ecosystems. Its evaluation has become increasingly important across various sectors, spanning from environmental conservation to industrial operations. Therefore, this study investigates the viability of utilizing a $\mathbf{pH}$ colorimetric dye as a C02-sensitive material. The material's effectiveness relies on chemical modifications induced in the dye structure through the action of a phase transfer agent, which establishes a stable equilibrium with the dye, thereby promoting its receptivity to C02 molecules. As the resulting physicochemical changes primarily exhibit colorimetric alterations, an optical system was developed to assess the performance of this material upon exposure to C02. Employing a dual-wavelength method, the system also incorporates a ratio metric relationship between the two signals to provide the most precise information. The conducted experiments generated promising results when the dye was subjected to varying concentrations of C02, ranging from 0% to 4 %, in comparison to nitrogen (N2). The application of the ratiometric method emerged as a crucial factor in this system, enabling its potential use in environments characterized by instability. Finally, the dye-sensitive characteristics experienced enhancement through the integration of an ionic liquid within the membrane matrix.

关键词： Performance evaluation Sensitivity Carbon dioxide Distance measurement Real-time systems Optical sensors Time factors

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INVESTIGATION OF THE ACCELERATION INFLUENCE ON FRICTION IN BEARINGS IN DUAL-SPIN MISSILE 38

INVESTIGATION OF THE ACCELERATION INFLUENCE ON FRICTION IN B...

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38th Danubia-Adria Symposium on Advances in Experimental Mechanics, DAS 2022

作者： Todić, Ivana Kuzmanović, Vladimir University of Belgrade Faculty of Mechanical Engineering Weapon Systems Department Kraljice Marije 16 Belgrade11120 Serbia University of Belgrade Faculty of Mathematics Department for Computer Science and Informatics Studentski Trg 16 Belgrade11000 Serbia

ISBN: (纸本)9786188627802

Rockets and missiles fired from a tube usually have aerodynamic surfaces that are packed when the rocket is in the tube. One of the common fins folding solutions is the wrap-around fins. The wrap-around fins are usually separated from the rocket's body by a bearing;thus the characteristics and the type of bearings used will have an effect on roll stabilization and the performance of roll stabilization autopilot. Also, during the flight, many forces act upon the missile thus affecting its exposed components. In turn, this may also affect the performance of the bearings that allow the wrap-around fins to rotate independently around the missile's body. This dual-spin concept increases roll stabilization efficiency and reduces induced roll from lateral control. For this design to be effective and achieve the desired performance, it is critical to analyze how the movements of the missile affect the bearing separating the body from the wrap-around fins. Since the sections are separated by the bearing, various imperfections of the joint such as friction, misalignment, etc. combined with the acceleration of the missile may have a transitional influence on the performance of the wrap-around fins and thus roll stabilization. In this paper, we will first identify and explain the problem of acceleration influence on friction in bearings. Next, the laboratory equipment and experimental procedures for examining friction in bearings will be described in detail. We will then present and analyze the results obtained from the experiments. Finally, we will draw conclusions and present the design modification this investigation has led to as well as the improved roll autopilot performance achieved by using the appropriate bearing. © 2023 Elsevier Ltd. All rights reserved.

关键词： acceleration-induced dual-spin fins friction missile wrap-around

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Development of a Model for Discriminating Electroencephalograms of Patients with Mild Cognitive Impairment and Healthy Individuals Using a Support Vector Machine 13

Development of a Model for Discriminating Electroencephalogr...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Tanabe, Akifumi Nakatani, Kyosuke Harachi, Kento Yamamoto, Yusuke Muramatsu, Ayumi Nagahara, Hajime Takemura, Noriko Shimojo, Shinji Furihata, Daisuke Mizuno-Matsumoto, Yuko Kamae-Shigenobu, Kazue Shinosaki, Kazuhiro Graduate School of Information Science University of Hyogo Kobe Japan School of Life Science and Technology Tokyo Institute of Technology Yokohama Japan Aino University Department of Medical Engineering Ibaraki Japan Institute for Datability Science Osaka University Suita Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Aomori University Faculty of Software and Information Technology Aomori Japan Osaka University Cyber Media Center Suita Japan Asakayama General Hospital Sakai Japan

ISBN: (纸本)9798350373332

We performed machine learning using spectrum analysis and power spectra of electroencephalograms (EEGs) of patients with mild cognitive impairment (MCI). Spectrum analysis was performed on the EEGs of MCI patients and healthy individuals, and the power spectrum values of the two groups were calculated and compared. Based on the power spectrum values of the theta and alpha bands, models for discriminating MCI patients were created using a support vector machine (SVM), and their accuracies were compared. In the spectrum analysis, the theta band showed significantly higher power spectrum values in the MCI group. In the comparison of the accuracies of SVM models, the model using the theta band showed higher values in parameters, such as accuracy rate. These results suggested that the power spectrum values of the theta band are useful for discriminating MCI patients. © 2024 IEEE.

关键词： Electroencephalography

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Hook Point Estimation for System Call Detection by Virtual Machine Monitor

Hook Point Estimation for System Call Detection by Virtual M...

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International Symposium on Computing and Networking Workshops (CANDARW)

作者： Masaya Sato Taku Omori Toshihiro Yamauchi Hideo Taniguchi Faculty of Computer Science and Systems Engineering Graduate School of Computer Science and Systems Engineering Okayama Prefectural University Soja Okayama Japan Faculty of Natural Science and Technology Okayama University Okayama Japan

Virtual machine monitors (VMMs) are used to monitor the behavior of virtual machine (VM) programs. System call detection is frequently used to monitor behavior. To monitor the system calls, the VMM inserts a breakpoint, called a hook point, into the memory of the monitored VM. Researchers have determined hook points based on experimental knowledge or reading the source code of operating systems (OSes). However, reading the source codes of OS requires specialized knowledge. In addition, the appropriate hook point differs among OS versions. Therefore, analyzing the source code in each OS update is impractical. We propose a method for estimating the hook point using a memory analysis technique. The proposed method acquires the memory of the monitored VM and then searches for an appropriate instruction appropriate to hook. The search instructions depend on the processor architecture. Therefore, the proposed method does not require knowledge of OS versions or reading the source code of OSes. The experimental results showed that the proposed method precisely estimates the hook point. In addition, the overhead of the proposed method is small, considering the boot time of the monitored VM.

关键词： Performance evaluation Virtual machine monitors Codes Source coding Operating systems Linux computer architecture

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Wireless control of a D.C. Motor Used for Driving a Conveyor Belt

Wireless control of a D.C. Motor Used for Driving a Conveyor...

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2024 International Conference on Circuit, systems and Communication, ICCSC 2024

作者： Livint, Petru Banu, Ioan-Viorel Culea, George Manale, Bouderbala Majout, Btissam Dusa, Alexandru University 'Vasile Alecsandri' of Bacau Department of Energetics and Science Computer Romania Sidi Mohammed Ben Abdellah University Fez Limas Laboratory Faculty of Sciences Dhar El Mahraz Morocco Sidi Mohammed Ben Abdellah University Fez Laboratory of Engineering Modellingand Systems Analysis Morocco 'Dunarea de Jos' University of Galati Department of Automatic and Electrical Engineering Romania

ISBN: (纸本)9798350365306

This article presents an experimental stand for the remote control of a D.C. motor used to drive a conveyor belt. This is based on two development boards Arduino Uno and two shields NRF24L01. The D. C. motor is supplied from a D.C. voltage source by means of the H type bridge. The emitter circuit sends the control signal generated through a potentiometer to the receptor circuit by means of radio waves at a frequency of 2.4 GHz. The receptor circuit receives the analogue signal emitted by the emitting circuit, transforms it into a PWM (pulse width modulation) signal and uses it for controlling the transistors of the H-bridge. For implementing and validating the remote control system of the D.C. motor two programs have been issued in the programming environment Arduino IDE for the two circuits. emitter and receptor. The remote control system of the D.C. motor has been running in the same way as the direct control of this. The remote control is used in the case of the electric actuation systems made with D.C. motors continuous used in spaces inaccessible to the human operator. © 2024 IEEE.

关键词： Belts

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PSO Optimization Algorithm for QoS Enhancement in IoT-Enabled WSNs

PSO Optimization Algorithm for QoS Enhancement in IoT-Enable...

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International Conference on Artificial Intelligence and Smart Environment, ICAISE 2022

作者： Benelhouri, Abdelkader Idrissi-Saba, Hafida Antari, Jilali Laboratory of Metrology and Information Processing Faculty of Science Ibn Zohr University B.P. 8106 Agadir Morocco Laboratory of Computer Systems Engineering Mathematics and Applications Ibn Zohr University Polydisciplinary FacultyB.P. 271 Taroudant83000 Morocco

ISBN: (纸本)9783031262531

Through the recent progress in the field of microelectronics and the emergence of wireless communication technologies, wireless sensor networks (WSNs) have seen the light of day. However, one of the major problems of this type of networks is the energy efficiency. The overage is also a key problem as it determines the ability of a set of sensors to monitor a geographic area efficiently. In order to improve network deployment and throughput, this paper proposes a PSO-based approach to deploy nodes and select cluster heads efficiently. The suggested work has undergone significant QoS experimentation in a variety of scenarios. The results of this algorithm are investigated by implementing the Mod-LEACH algorithm in the data routing process. It is concluded that the PSO based clustering algorithm enhances the network throughput by improving nodes emplacement. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Microelectronics

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Improving Motor Imagery Classification in BCI systems Using EMD and Multi-Layer CNNs

Improving Motor Imagery Classification in BCI Systems Using ...

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International eConference on computer and Knowledge engineering (ICCKE)

作者： Reza Arghand Ali Chaibakhsh Moein Radman Intelligent Systems and Advanced Control Lab Faculty of Mechanical Engineering University of Guilan Rasht Guilan Iran Brain-Computer Interfacing and Neural Engineering Laboratory University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom

ISBN: (数字)9798331511272

ISBN: (纸本)9798331511289

Brain-computer Interface (BCI) systems are relatively new technologies that could play a significant role in aiding the recovery of impaired activities resulting from neuromuscular disabilities in affected individuals. Accurate recognition and classification of motor imagery in BCI systems present a challenge, leading to extensive research in recent years aimed at improving the accuracy of these systems. In this study, a combination of the Empirical Mode Decomposition (EMD) method and a multi-layer Convolutional Neural Network (CNN) is employed. Initially, the signal is decomposed into Intrinsic Mode Functions (IMFs) using EMD, and all IMFs across all trials are analyzed to select the best ones, which are then fed into the CNN as inputs. Additionally, the study incorporates the fusion of three CNN networks, each corresponding to a different IMF. The features extracted from these networks are combined and used to train an SVM classifier. The proposed method achieved an accuracy of 86.1% on the BCI-2a 2008 dataset, outperforming other state-of-the-art approaches.

关键词： Support vector machines Knowledge engineering Accuracy Image recognition Empirical mode decomposition Neuromuscular Motors Feature extraction Brain-computer interfaces Convolutional neural networks

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Novel vision transformer and data augmentation technique for efficient detection of monkeypox disease

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Multimedia Tools and Applications 2024年 1-19页

作者： Alarfaj, Aisha Ahmed Ahmad, Salman Hakeem, Abeer M. Alabdulqader, Ebtisam Abdullah PERO, Chiara Alsubai, Shtwai Innab, Nisreen Ashraf, Imran Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Post Graduate Resident Department of Urology Allama Iqbal Teaching Hospital Dera Ghazi Khan Pakistan Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Department of Information Technology College of Computer and Information Sciences King Saud University P. O. Box 800 Riyadh11421 Saudi Arabia Department of Management & amp Innovation Systems University of Salerno Via Giovanni Paolo II 132 Fisciano Salerno Italy Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University P.O. Box 151 Al-Kharj11942 Saudi Arabia Department of Computer Science and Information Systems College of Applied Sciences AlMaarefa University Diriyah Riyadh13713 Saudi Arabia Department of Information and Communication Engineering Yeungnam University Gyeongsan Korea Republic of

Recent technological advancements have paved the way for the optimization of medical processes, particularly automated disease detection. Moreover, the adoption of machine learning (ML) has greatly helped in automating disease detection. Such approaches can detect various diseases early, enabling timely treatment to save countless lives. Early and accurate diagnosis is very important for diseases like monkeypox, to curb its spread. Monkeypox is a viral disease caused by double-stranded DNA and can be transmitted through close contact with infected humans or animals. It’s early identification and accurate lesion diagnosis are critical to contain the disease. This study proposes an automated approach to optimize the diagnosis of monkeypox disease using a novel vision transformer, which is utilized due to its effectiveness for feature extraction. The Proposed approach’s efficiency and accuracy are tested on a public benchmark dataset comprising a variety of skin lesions of different ages and genders. In addition, data augmentation involves rotation, scaling, and flipping thereby enhancing the density of the training data set for better generalization of ML models. Experiments involve binary, as well as, multi-class classification. For the binary class, the proposed model achieves an accuracy of 97.63%, outperforming traditional ML and deep learning (DL) techniques. In the case of multi-class classification with monkeypox, measles, normal, HFMD, cowpox, and chickenpox classes, the proposed model archives an accuracy of 90.61% while precision, recall, and F1 scores are 91.39%, 89.17%, and 90.28%, respectively. Furthermore, the proposed approach shows average accuracy, precision, recall, and F1 scores of 97.54%, 96.19%, 95.16%, and 95.67%, respectively for five-fold cross-validation. Experiments demonstrate that the combination of data augmentation techniques and the vision transformer model significantly optimizes diagnostic performance. In brief, advanced DL architectur

关键词： Medical image processing

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Investigations on Cyber Security Vulnerability using Distribution Analysis

Investigations on Cyber Security Vulnerability using Distrib...

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2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Andrews, Leo John Baptist Alagappan, Annamalai Sarathkumar, D. Fathima, M. Venkatachary, Sampath Kumar Rajeshkanna, R. Raj, Raymon Antony Botho University Faculty of Engineering and Technology Department of Information Technology Gaborone Botswana Botho University Faculty of Engineering and Technology Department of Network and Infrastructure Management Gaborone Botswana Kongu Engineering College Department of Electrical and Electronics Engineering Tamilnadu Erode District638 060 India Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India Grant Thornton Botswana Plot 50370 Acument Park Fair Grounds Gaborone Botswana Thamirabarani Engineering College Department of Eee Tamil Nadu Tirunelveli627 358 India

ISBN: (纸本)9798350348460

Internet communication is used as a mode of engagement by businesses, organizations, and even nations in a variety of contexts. As a result, both the quantity of data produced and the importance of the information that can be derived from it are growing. Multiple safeguards are required in order to ensure that the accessibility, integrity, and confidentiality of company information and assets are maintained. When it comes to protecting the privacy of a company and its reputation, adopting countermeasures and minimizing the damage caused by irreversible cyberattacks are both very crucial. It is possible to utilize both active and passive attack tactics, as well as social engineering tests, to evaluate the weaknesses of a corporation's cyber security. The identification and ranking of vulnerabilities both play an active part in the process of raising the level of corporate awareness, as well as closing shortfalls and enhancing measures. In this investigation, ethics committee reports and confidentiality agreements were followed in order to do a cyber security vulnerability assessment on seven separate organizations. These organizations represented the governmental sector, the corporate sector, and the civil society. In order to evaluate the effectiveness of the firms' cyber security infrastructures, security scans such as port, web, application-based system and network penetration tests, distributed denial of service attacks, and social engineering were carried out. The Common Vulnerability Scoring System (CVSS) was used in order to change the base score of each institution and to identify the vulnerabilities that were present. Enterprise Networks, Cyber Security Analysis, Cyber Attacks, Penetration, and Vulnerability are some of the Keywords that can be found in this article. © 2024 IEEE.

关键词： cyber analysis Introduction cyber security cyber-attacks vulnerabilities

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