Article
Engineering, Electrical & Electronic
Liangbo Zhao, Qingjun Zhang, Yan Li, Yalin Qi, Xinzhe Yuan, Jie Liu, Hangliang Li
Summary: The GF-3 satellite is China's first civilian quad-polarized C-band imaging microwave satellite that provides high-resolution marine and land observations, with a design life of eight years. Despite facing numerous challenges during development, significant advancements in technological innovation were achieved.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Davide Giudici, Pietro Guccione, Marco Manzoni, Andrea Monti Guarnieri, Fabio Rocca
Summary: In this paper, we discuss a coherent synthetic aperture radar formation where identical sensors transmit at the same time, providing diversity through receiver phase centers to mitigate interference and achieve large swath coverage.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Enzhe Tao, Nannan Guo, Kexin Xu, Bin Wang, Xuhua Zhou
Summary: The study conducted SLR validation on precise orbits of eight Galileo satellites provided by multiple analysis centers, showing significant improvements in SLR residuals after updating solar radiation pressure (SRP) models. The updated SRP descriptions led to reduced standard deviation and systematic bias of residuals, as well as decreased variability in orbital products. The study also demonstrated the effectiveness of perturbation models, such as SRP, in providing better orbit modeling for Galileo satellites.
Article
Computer Science, Information Systems
Ilaria Nasso, Fabrizio Santi, Debora Pastina
Summary: This paper presents a new method to estimate ship target velocity by utilizing a Taylor-series approach with the bistatic Doppler-rates estimated in GNSS-based multistatic radar configurations. Leveraging on long integration times significantly increases the accuracy of estimated ship velocity.
Article
Computer Science, Information Systems
Anargyros J. Roumeliotis, Christos N. Efrem, Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos
Summary: This article focuses on studying the one-to-many suboptimal assignments in high-throughput multibeam satellite systems under the smart gateway diversity concept. It proposes a two-step heuristic approach to approach the optimal solutions and introduces new metrics for investigation.
IEEE SYSTEMS JOURNAL
(2022)
Article
Geochemistry & Geophysics
Fernando Nino, Clement Coggiola, Denis Blumstein, Lea Lasson, Stephane Calmant
Summary: In this article, deep convolutional neural networks are used to convert radar measurements into water levels of inland waterbodies. The method is validated and shown to be highly accurate and robust compared to traditional methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Aerospace
Alessandro Golkar, Giuseppe Cataldo, Ksenia Osipova
Summary: This paper introduces a trade space exploration model to identify designs for space-borne satellite synthetic aperture radars and demonstrates its utility through two case studies focusing on radar instruments on small satellite platforms and 3U CubeSat platforms. The analysis narrows down feasible radar designs to optimal ones, elicits feasibility conditions, and discusses technical constraints on associated requirements for such innovative miniaturized radars.
Article
Computer Science, Information Systems
Marko Hoyhtya, Sandrine Boumard, Anastasia Yastrebova, Pertti Jarvensivu, Markku Kiviranta, Antti Anttonen
Summary: In the New Space era, small countries are emerging as important players in the space business. Sustainability is crucial for preserving satellite services for future generations, but has been overlooked in existing surveys on space technologies. This survey paper discusses multi-layer networking approaches in the 6G era from a sustainability perspective and addresses important space safety paradigms and advancements towards a planned European connectivity constellation.
Article
Engineering, Electrical & Electronic
Yanhao Liu, Yibiao Wang, Jue Wang, Li You, Wenjin Wang, Xiqi Gao
Summary: This paper investigates the design of precoder for LEO satellite downlinks with imperfect AoD-based CSI. The angle deviations of each user are treated as random variables and integrated to enhance the robustness of the precoder. A per-antenna power constraint is adopted instead of a sum-power constraint, and an iterative algorithm and deep learning techniques are used to reduce computational complexity. Simulation results demonstrate the effectiveness of the proposed precoding approach.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Miaona Huang, Jun Chen, Suili Feng
Summary: The integration of satellite and terrestrial cellular networks using OFDM technology is promising, but faces challenges in synchronization due to higher Doppler shifts in the satellite system. New methods for carrier frequency offset estimation in OFDM-based satellite systems are proposed to address this issue with compatibility with LTE and NR standards and lower computational complexity.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Geochemistry & Geophysics
S. R. Cloude, R. Ossikovski, E. Garcia-Caurel
Summary: This letter introduces a new algorithm for polarimetric calibration of spaceborne imaging radar systems, combining distortion matrix estimation and polar decomposition techniques to achieve fully calibrated data on arbitrary Faraday rotation.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2021)
Article
Environmental Sciences
Luisa Bastos, Peter Buist, Raffaela Cefalo, Jose Alberto Goncalves, Antonia Ivan, Americo Magalhaes, Alexandru Pandele, Marco Porretta, Alina Radutu, Tatiana Sluga, Paolo Snider
Summary: The European Commission (EC) declared the provision of Galileo Initial Services (IS), marking a historical milestone in the program's progress towards Full Operational Capability. The European Union Agency for the Space Programme (EUSPA) is the Galileo Service Provider, responsible for monitoring and evaluating the performance of Galileo services and other GNSS. This paper presents numerical results from dynamic campaigns comparing navigation performance across different GNSS.
Article
Engineering, Electrical & Electronic
Gihan C. Hamza
Summary: The use of GNSS receivers in the field of telecommunications for timing and synchronization is essential. Multiple GNSSs, including GPS, Galileo, BeiDou, and GLONASS, are used for time transfer and calculation of UTC.
IEEE COMMUNICATIONS MAGAZINE
(2022)
Article
Geochemistry & Geophysics
P. Steigenberger, O. Montenbruck
Summary: Information on satellite antenna phase center offsets (PCOs) is crucial for high-precision applications of global navigation satellite systems. Pre-flight manufacturer calibrations of the PCOs are available for all individual Galileo satellites and each frequency. The consistency of the PCO values for different frequencies becomes increasingly important due to the growing number of E5b and E6-capable receivers and upcoming multi-frequency applications.
JOURNAL OF GEODESY
(2023)
Article
Engineering, Electrical & Electronic
Guanming Zeng, Yafeng Zhan, Haoran Xie, Chunxiao Jiang
Summary: In this paper, a networked telemetry system is designed to meet the monitoring requirements of mega constellations in the upcoming 6G communication era. Data is transmitted through the inter-satellite-links of LEO and MEO satellites. The resource allocation problem is decomposed using the block coordinate descent method and effectively increases the transmitted data amount of the system.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
G. Ignisha Rajathi, R. Ramesh Kumar, D. Ravikumar, T. Joel, Seifedine Kadry, Chang-Won Jeong, Yunyoung Nam
Summary: Recently, the Internet of Medical Things (IoMT) has received significant attention for its potential to improve healthcare services. In this paper, a novel IoMT and cloud-enabled brain tumor diagnosis model, IoMTC-HDBT, is proposed. The model utilizes deep learning techniques to automate the diagnosis process using magnetic resonance imaging (MRI) brain images captured by IoMT devices. The cloud server executes a disease diagnosis model based on the sparrow search algorithm (SSA) with GoogleNet (SSA-GN) model. The proposed model, which includes adaptive window filtering and functional link neural network (FLNN), achieves high accuracy in detecting and classifying abnormal MRI brain images.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
V. R. Kavitha, K. Nimala, A. Beno, K. C. Ramya, Seifedine Kadry, Byeong-Gwon Kang, Yunyoung Nam
Summary: Image Captioning is a research topic in AI that combines Computer Vision and Natural Language Processing to generate image descriptions. This paper introduces an OHHODLIC technique that utilizes an oppositional Harris Hawks optimization and deep learning for image captioning. The technique involves pre-processing, feature extraction, caption generation, and hyperparameter tuning, resulting in better performance compared to recent approaches.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
R. Bhaskaran, S. Saravanan, M. Kavitha, C. Jeyalakshmi, Seifedine Kadry, Hafiz Tayyab Rauf, Reem Alkhammash
Summary: Sentiment Analysis, a subfield of Natural Language Processing, focuses on identifying and extracting opinions from text. This research proposes a novel machine learning model that effectively handles unstructured text and achieves improved sentiment classification.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Mathematics, Applied
Atiqe Ur Rahman, Muhammad Saeed, Mazin Abed Mohammed, Alaa S. Al-Waisy, Seifedine Kadry, Jungeun Kim
Summary: This study aims to address the dam site selection problem by proposing a novel evaluation method that takes into account essential features such as fuzzy parameterized grades, hypersoft setting, complex setting, and single-valued neutrosophic setting. By integrating fuzzy parameterization, decision-makers' opinions, and classical matrix theory, the method calculates score values for evaluating alternative sites. These computed scores are then used to evaluate suitable locations for dam construction. The proposed algorithm has been found to be precise and consistent through comparison with existing approaches.
Article
Biochemistry & Molecular Biology
Priscilla Pushparani Victor, Radhakrishnan Narayanaswamy, Seifedine Kadry, Baskar Gurunathan
Summary: Kidney stone is a global problem, and research on nonsurgical treatment using biological compounds is important. Citric acid is traditionally used to dissolve kidney stones. The study evaluated the activity of Citrus sinensis peel extract against phosphoethanolamine cytidylyltransferase (PCYT) for treating kidney stones. The compounds in the extract showed good binding affinities against PCYT and have potential for pharmaceutical drug development.
BIOTECHNOLOGY AND APPLIED BIOCHEMISTRY
(2023)
Article
Medicine, General & Internal
Sudhakar Tummala, Seifedine Kadry, Ahmed Nadeem, Hafiz Tayyab Rauf, Nadia Gul
Summary: Lung and colon cancers are major causes of death and illness. Early diagnosis methods include radiography, ultrasound, MRI, and CT scans, as well as blood tumor markers. However, histopathology remains the most accurate diagnostic method, despite being time-consuming and requiring high-end equipment. Deep learning has shown promise in the medical field, enabling earlier diagnosis and treatment.
Article
Medicine, General & Internal
Manoj Diwakar, Prabhishek Singh, Ravinder Singh, Dilip Sisodia, Vijendra Singh, Ankur Maurya, Seifedine Kadry, Lukas Sevcik
Summary: This study aims to incorporate a novel multimodality medical image fusion technique into the shearlet domain. The proposed method uses the non-subsampled shearlet transform (NSST) to extract both low- and high-frequency image components and applies a modified sum-modified Laplacian (MSML)-based clustered dictionary learning technique to fuse low-frequency components. High-frequency coefficients are fused using directed contrast in the NSST domain. The proposed method outperforms existing methods in terms of edge preservation.
Article
Mathematics
Chandrakala Arya, Manoj Diwakar, Prabhishek Singh, Vijendra Singh, Seifedine Kadry, Jungeun Kim
Summary: Significant advances have been made in the field of text summarization, with a focus on news summarization. To create summaries of various news articles in the context of erroneous online data, it is essential to develop a synthesis approach that can extract, compare, and rank sentences. It is also necessary for the news summarization system to handle multi-document summaries due to content redundancy. This paper proposes a method for summarizing multi-document news web pages using similarity models and sentence ranking, which outperforms other recent methods in summarizing news articles according to experimental results.
Article
Computer Science, Artificial Intelligence
Sujatha Krishnamoorthy, Weifeng Yu, Jin Luo, Seifedine Kadry
Summary: This paper proposes a novel GO-DBNWKELM technique based on Gannet optimization, deep belief network, and wavelet kernel extreme learning machine for detecting and assessing the progression of diabetic retinopathy. The classifier achieves high accuracy and performance in detecting DR.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Ahmad Almadhor, Rizwana Irfan, Jiechao Gao, Nasir Saleem, Hafiz Tayyab Rauf, Seifedine Kadry
Summary: Dysarthria is a speech disability caused by weak muscles and organs involved in articulation, affecting speech intelligibility. This paper proposes a visual dysarthric ASR system using SCNN and MHAT to overcome speech challenges. The DASR system outperformed other systems, improving recognition accuracy for the UA-Speech database by 20.72%, with the largest improvements seen in very-low (25.75%) and low intelligibility (33.67%) cases.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Theory & Methods
Muhammad Attique Khan, Asif Mehmood, Seifedine Kadry, Nouf Abdullah Almujally, Majed Alhaisoni, Jamel Balili, Abdullah Al Hejaili, Abed Alanazi, Shtwai Alsubai, Abdullah Alqatani
Summary: Industrial advancements and financial stakes drive the aims of smart cities, which focus on increasing efficiency and citizens' quality of life. Human Gait Recognition (HGR) is an important application that utilizes walking styles for individual recognition. This paper proposes a deep learning method for HGR using a large gait database and transfer learning, achieving high accuracy by addressing constraints such as poor lighting and varying angles. The proposed technique combines improved BAT algorithm, entropy selection, and canonical correlation analysis to extract and fuse features for final gait recognition using a softmax classifier.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Multidisciplinary Sciences
Shahid Rashid, Mudassar Raza, Muhammad Sharif, Faisal Azam, Seifedine Kadry, Jungeun Kim
Summary: White blood cells are categorized using a transform learning model and a virtual hexagonal trellis structure feature extraction method. The features extracted by CNN and VHT are optimized using ant colony optimization and classified using support vector machine variants. The proposed method achieves an accuracy of 99.9%, outperforming existing methods.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Information Systems
Ilyos Abdullaev, Natalia Prodanova, K. Aruna Bhaskar, E. Laxmi Lydia, Seifedine Kadry, Jungeun Kim
Summary: A new Task Offloading and Resource Allocation method based on IoT-based Mobile Edge Computing (MEC) using Deep Learning with Seagull Optimization (TORA-DLSGO) algorithm is proposed in this study. It addresses the resource management issue and enables an optimum offloading decision to minimize system cost. The proposed method outperforms existing models in reducing client overhead in MEC systems.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Multidisciplinary Sciences
Muhammad Attique Khan, Yu-Dong Zhang, Majed Alhusseni, Seifedine Kadry, Shui-Hua Wang, Tanzila Saba, Tassawar Iqbal
Summary: In this paper, a method for action recognition based on the fusion of shape and deep learning features is proposed. The method consists of two steps: human extraction and action recognition. By combining entropy-controlled feature selection and parallel conditional entropy approach, the features are fused and classified, achieving a high accuracy rate.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Muhammad Attique Khan, Seifedine Kadry, Pritee Parwekar, Robertas Damasevicius, Asif Mehmood, Junaid Ali Khan, Syed Rameez Naqvi
Summary: Human gait analysis is an important topic in computer vision with various applications. However, the variability in patients' clothes, viewing angle, and carrying conditions can affect system performance. To enhance accuracy, this study proposes a deep learning feature aggregation method applied in gait recognition. The results demonstrate that the proposed method achieves accuracy beyond 96% and outperforms other classifiers.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
