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7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Rashid Hujijo, Hayder S. Ilyas, Muhammad Qasim, Abdullah Ali Ullah, Ubaid Dept. of Electrical and Computer Engineering Altinbas University Istanbul Turkey Dept. of Computer Engineering Altinbas University Istanbul Turkey Dept. of Tech. Communications Engineering Al-Furat Al-Awsat Technical University Najaf Iraq Network and Communication Engineering Al Ain University Abu Dhabi United Arab Emirates

ISBN: (纸本)9781665464086

Filtered-OFDM scheme recently considers a promising element for Visible Light Communication (VLC) systems. Converting the F-OFDM bipolar signal to a nonnegative signal and being compatible with the Intensity Modulation and Direct Detection (IM/DD) is a crucial issue for researchers. To achieve a unipolar signal, many techniques have been proposed. In this paper, a Direct Current-bias (DC-bias) technique is employed to acquire a signal unipolarity and evaluate the efficiency of the F-OFDM system. The simulation findings offer that when the DC bias increased, the peak-to-average-power ratio (PAPR) increased even when using different modulation orders. In contrast, comparing different modulation orders, F-OFDM shows better bit error rate (BER) performance, especially in low-order modulation schemes. © 2023 IEEE.

关键词： Quadrature amplitude modulation

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A Precise Positioning Method with Integration of GNSS and Doppler Shift Based Positioning using LEO Satellite 14

A Precise Positioning Method with Integration of GNSS and Do...

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Kabir, M. Humayun Hasan, Md. Ali Shin, Wonjae Ajou University Electrical and Computer Engineering Suwon Korea Republic of Ajou University Dept. of Ai Convergence Network Suwon Korea Republic of

ISBN: (纸本)9798350313277

Global Navigation Satellite System (GNSS) utilizes medium earth orbit (MEO) and geostationary earth orbit (GEO) satellites with time difference of arrival (TDOA) based multilateration technique to determine position. Due to the long orbital altitude of GNSS satellites from the earth surface, the signal strength is very low. This low signal is also remarkably attenuated and reflected by nature (tall trees) and buildings that induces large errors in pseudorange measurements. In contrast, the closer earth orbit of LEO provides strong signal power and high Doppler frequency shift range (±40kHz). This is advantageous to develop Doppler shift-based positioning algorithm. However, using the iterative method of Doppler shift positioning the initial receiver position plays a vital role in ensuring convergence. To face this challenge, we have utilized the positioning outcome of GNSS as an initial receiver position and then utilized the Doppler shift-based algorithm to estimate the more precise position. Experimental results show that the proposed approach reduces positioning error significantly compared to the individual GNSS method. © 2023 IEEE.

关键词： Doppler-Shift GNSS Multilateration TDOA

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Comparison of User Pairing Methods for NOMA in Beamforming Training within 802.11ad WLANs 15

Comparison of User Pairing Methods for NOMA in Beamforming T...

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Choi, Seonjoo Baek, Hoki Lim, Jaesung Ajou University Dept. of Ai Convergence Network Suwon Korea Republic of School of Computer Science and Engineering Kyungpook National University Daegu Korea Republic of Ajou University Dept. of Military Digital Convergence Suwon Korea Republic of

ISBN: (纸本)9798350364637

Beamforming training (BFT) is crucial for communication performance in the mmWave environment. A suitable multiple access technique is essential for enabling multiple users to perform BFT simultaneously. Therefore, non-orthogonal multiple access (NOMA) is a potential candidate for enabling multiple users to perform BFT. A user pairing method is necessary for performing BFT simultaneously with NOMA. We assessed the user pairing probability when applying various user pairing methods and identified the most appropriate user pairing strategy based on the network environment. © 2024 IEEE.

关键词： Beamforming

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Damping Control for Heaving Wave Energy Converters Using Maximum Power Point Tracking Methods 5

Damping Control for Heaving Wave Energy Converters Using Max...

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5th International Conference on Control, Communication and Computing, ICCC 2023

作者： Mon, Bisni Fahad Wahyudie, Addy Errouissi, Rachid Hashfi, Tuanku Badzlin UAE University Computer & Network Engineering Al Ain United Arab Emirates UAE University Dept. of Electrical Engineering Al Ain United Arab Emirates

ISBN: (纸本)9798350334128

The purpose of this study was to evaluate damping control utilizing various maximum power point tracking (MPPT) approaches for heaving wave energy converters (WEC). A DC-DC boost converter was used to implement damping control. A perturb and observe approach was used to find the duty cycle for the MPPT. The optimal performance index for the MPPT is determined by this assessment study, along with the appropriate position for the observation parameters. The observing parameters were assessed and evaluated in three locations (electrical variables at the load, electrical variables between the source and the load, and mechanical variables near the source). According to the findings, the MPPT strategy performs the best when considering the characteristics between the source and load, and using power maximization as the performance metric. © 2023 IEEE.

关键词： Permanent magnets

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MIRROR: MiRNA regulation-level differential network to study sex and ethnic disparities in cancer 46

MIRROR: MiRNA regulation-level differential network to study...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Alfano, Caterina Filetti, Marco Farina, Lorenzo Petti, Manuela Sapienza University of Rome Dept. of Experimental Medicine Rome Italy Fondazione Policlinico Universitario A. Gemelli Irccs Phase 1 Unit Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering PhD Program in Network Oncology and Precision Medicine Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350371499

Cancer disparities are adverse differences in cancer measures that exist among certain population groups. Given that the role they play not only in the disease prognosis but also in therapy response, there is an urgent need to understand what causes them. Most studies investigate these disparities by analyzing transcriptomic data and in particular miRNAs for their regulatory role, but only focusing on expression levels. To face this challenge we propose MIRROR, a new method which analyzes a differential co-expression network of miRNAs between patients' cohorts, to study the role they play at the target genes' level. Doing so, we can study the altered molecular mechanism that are linked to cancer disparities. The application of MIRROR to two different cases of cancer disparities has demonstrated its efficacy in identifying molecular players involved in the considered disparity, presenting itself as a viable option to approach this challenge. © 2024 IEEE.

关键词： differential network modeling disparities in cancer graph theory miRNA-target association transcriptomics

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Investigating Online Searching Behavior Based on Google Trends in MENA Region Before and After COVID-19 53

Investigating Online Searching Behavior Based on Google Tren...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Belkacem, Abdelkader Nasreddine Jamil, Nuraini Alrabaee, Saed College of It Uae University Dept. of Computer and Network Engineering Al Ain United Arab Emirates College of It Uae University Dept. of Computer Science and Software Engineering Al Ain United Arab Emirates College of It Uae University Dept. of Information Systems and Security Al Ain United Arab Emirates

ISBN: (纸本)9798350336429

The outbreak of the coronavirus disease (COVID-19) has had a profound impact on education worldwide. The rise of remote learning is one of the most significant changes in this regard, as many schools and universities were forced to close down by regional health authorities. This has also caused people to become more conservative in trade-offs between healthcare and education. Google Trends is the most common tool for analyzing online search behaviors. It is a free resource that provides information on the trends and changes in users' online interests over time based on certain terms and subjects. The online search queries on Google can be used to assess users' behaviors concerning online learning to forecast their choices regarding online education. This paper examines the frequency of users' web searches for online communication tools, courses, and learning terms. We statistically compared users in the Middle East and North Africa regions by using the volumes of searches recorded on Google Trends from January 2016 to August 2022. Moreover, we used machine learning techniques to identify differences among the keywords used. The findings statistically show that COVID-19 has led to an increase in the extent of students' attention to and interest in online learning. © 2023 IEEE.

关键词： COVID-19 Google Trends MENA Online learning Remote learning Web Behavior

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Chasing puppies on orthogonal straight-line plane graphs

arXiv

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arXiv 2025年

作者： Ockenfels, Johanna Okamoto, Yoshio Schnider, Patrick Dept. of Computer Science ETH Zürich Switzerland Dept. of Computer and Network Engineering The University of Electro-Communications Japan Dept. of Mathematics and Computer Science University of Basel Dept. of Computer Science ETH Zürich Switzerland

Assume that you have lost your puppy on an embedded graph. You can walk around on the graph and the puppy will run towards you at infinite speed, always locally minimizing the distance to your current position. Is it always possible for you to reunite with the puppy? We show that if the embedded graph is an orthogonal straight-line embedding the answer is yes. © 2025, CC BY.

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6-Port Rotationally Symmetric Antennas Supporting Orbital Angular Momentum Modes 2

6-Port Rotationally Symmetric Antennas Supporting Orbital An...

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2nd International Microwave and Antenna Symposium, IMAS 2024

作者： Alonso, R. Aldana Akazzim, Y. Jofre, M. Towfiq, Md. Asaduzzaman Cetiner, Bedri A. Blanch, S. Romeu, J. Jofre-Roca, L. Universitat Politècnica de Catalunya Dept. Signal Theory and Communications Barcelona Spain Universitat Politècnica de Catalunya Dept. Network Engineering Barcelona Spain i5 Technologies Inc. North LoganUT84341 United States Utah State University Dept. Electrical and Computer Engineering LoganUT84322 United States

ISBN: (纸本)9798350356359

The use of digital platforms with rapidly increasing users in the wireless domain leads communication systems to provide high data rates, reliability, and strong quality. In this context, Multiple-Input Multiple-Output (MIMO) antennas are getting more attention and play an essential part in the current generation of wireless technology. This work presents the performance of a 6-element rotationally symmetric MIMO antenna design based on a magnetoelectric (ME) dipole antenna approach to be used in advanced MIMO applications such as Orbital Angular Momentum (OAM) and high-capacity channels. Cognitive wireless technologies for vehicular communications, combined with OAM modes, aim to enhance Non-Line-Of-Sight (NLOS) short-distance communications for smart mobility. Antenna compatibility with the OAM mode is derived from specific spherical vector harmonic function momentum tensors synthesized from the dipoles. An optimized design is presented with good agreement between numerical and experimental results for the operating frequency band of 4.0 to 5.0 GHz. © 2024 IEEE.

关键词： Antenna Magneto electric Microwave Orbital Angular Momentum Radiation Vehicular Communications

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Classification of Functional and Nonfunctional Hand Movement Using Deep Learning and First-Person View Video

Classification of Functional and Nonfunctional Hand Movement...

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Tran, Tan Chang, Lin-Ching Lum, Peter S. Dept. of Electrical Engineering and Computer Science The Catholic University of America WashingtonDC20064 United States The Catholic University of America Dept. of Biomedical Engineering WashingtonDC20064 United States MedStar National Rehabilitation Network WashingtonDC20064 United States

ISBN: (纸本)9798350327595

Upper extremity (UE) rehabilitation of motor function is needed post-stroke. Although UE rehabilitation is widely used in practice, it is difficult to evaluate the effectiveness of UE treatments. There are various approaches to evaluate UE motor function such as performing tasks in the clinician's office, patient's self-report, or wearable devices equipped with accelerometer/gyro sensors to analyze the data captured from stroke survivors. Our previous study reported that using a Random Forest machine learning algorithm with accelerometry sensor data obtained by single wrist-worn sensor, it is possible to differentiate between functional and non-functional UE movements in stroke survivors with good accuracy. However, to build the model, a third-person view video was captured and manually annotated by experts to provide ground truth labels for training. This task is very time-consuming and subjective. In this study, we propose a framework that uses deep learning (DL) to classify functional and non-functional hand movement in videos captured from a wearable camera (i.e., first-person view videos). The proposed system is fully automated and consists of two DL networks. The first DL network performs hand pose estimation from a 2-second sequence of frames which extract pre-defined key points on the hands. The second DL network then takes these key points as input and classifies the sequence of frames to either functional or non-functional movement. The proposed system has two major impacts on rehabilitation. First, it can provide initial annotations on the frames of videos that can significantly reduce the time required for human annotations. Second, analyzing the effectiveness of UE rehabilitation using the first-person view videos enables us to measure the outcomes of UE treatments in stroke survivors' homes. In addition, the system can deliver timely feedback to stroke survivors that has the potential to increase the use of the affected UE in the community. © 2023 IEEE

关键词： deep learning - Regular Research Paper rehabilitation stroke upper extremity

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Comparative Evaluation of Machine Learning-Based Controller Area network Intrusion Detection Systems 14

Comparative Evaluation of Machine Learning-Based Controller ...

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14th International Conference on Information and Communication Systems, ICICS 2023

作者： Al-Jarrah, Omar Y. Ramadan, Omar A. Alsaify, Baha Alkhushayni, Suboh Jordan University of Science and Technology Faculty of Computer and Information Technology Dept. Network Engineering and Security P.O. Box 3030 Irbid22110 Jordan Jordan University of Science and Technology Faculty of Engineering Dept. Mechanical Engineering P.O. Box 3030 Irbid22110 Jordan Yarmouk University Dept. Information Systems Irbid Jordan

ISBN: (纸本)9798350307870

The controller area network (CAN) protocol is widely used in vehicle networks. However, it lacks essential security features like confidentiality and authentication. To enhance vehicle security, researchers have proposed and developed various methods, including intrusion detection systems (IDSs). These IDSs play a key role in early detection of potential cyberattacks, safeguarding vehicles, passengers, and road users. Machine learning (ML) algorithms are increasingly employed in CAN IDSs but they face challenges due to diverse experimental settings, datasets, and metrics used for evaluation, impeding progress and comparison of different approaches in this field. This study aims to benchmark well-recognized ML algorithms, including gaussianNB, k-nearest neighbors (KNN), decision trees (DT), random forest (RF), long short-term memory (LSTM), and convolutional neural networks (CNN), for intrusion detection in CAN. We evaluate the performance of these algorithms using seven evaluation metrics on the real ORNL automotive dynamometer (ROAD) dataset, a state-of-the-art benchmark in this field. Experimental results demonstrate that KNN, DT, RF, LSTM, and CNN can detect various types of attacks (e.g., Fuzzing, targeted ID, and masquerade attacks) with high accuracy. However, the computational and time efficiency of tree-based classifiers, namely DT and RF, makes them a potentially appealing choice for real-time intrusion detection tasks in CAN. © 2023 IEEE.

关键词： Intrusion detection

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