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Out-of-distribution generalization of machine learning models remains challenging since the models are inherently bound to the training data distribution. This especially manifests, when the learned models rely on spurious correlations. Most of the existing approaches apply data manipulation, representation learning, or learning strategies to achieve generalizable models. Unfortunately, these approaches usually require multiple training domains, group labels, specialized augmentation, or pre-processing to reach generalizable models. We propose a novel approach that addresses these limitations by providing a technique to guide the neural network through the training phase. We first establish input pairs, representing the spurious attribute and describing the invariance, a characteristic that should not affect the outcome of the model. Based on these pairs, we form a corrective gradient complementing the traditional gradient descent approach. We further make this correction mechanism adaptive based on a predefined invariance condition. Experiments on ColoredMNIST, Waterbird-100, and CelebA datasets demonstrate the effectiveness of our approach and the robustness to group shifts.

In order to bolster the next generation of wireless networks, there has been a great deal of interest in non-terrestrial networks (NTN), including satellites, high altitude platform stations (HAPS), and uncrewed aerial vehicles (UAV). To unlock their full potential, these platforms can integrate advanced technologies such as reconfigurable intelligent surfaces~(RIS) and next-generation multiple access (NGMA). However, in practical applications, transceivers often suffer from radio frequency (RF) impairments, which limit system performance. In this regard, this paper explores the potential of multi-layer NTN architecture to mitigate path propagation loss and improve network performance under hardware impairment limitations. First, we present current research activities in the NTN framework, including RIS, multiple access technologies, and hardware impairments. Next, we introduce a multi-layer NTN architecture with hardware limitations. This architecture includes HAPS super-macro base stations (HAPS-SMBS), UAVs--equipped with passive or active transmissive RIS--, and NGMA techniques, like non-orthogonal multiple access (NOMA), as the multiple access techniques to serve terrestrial devices. Additionally, we present and discuss potential use cases of the proposed multi-layer architecture considering hardware impairments. The multi-layer NTN architecture combined with advanced technologies, such as RIS and NGMA, demonstrates promising results; however, the performance degradation is attributed to RF impairments. Finally, we identify future research directions, including RF impairment mitigation, UAV power management, and antenna designs., Comment: Accepted for IEEE Internet of Things Magazine

In this work, we use gas phase metallicities calculated from the Sloan Digital Sky Survey (SDSS) Mapping Nearby Galaxies at Apache Point (MaNGA) Data Release 17 (DR17) to assess the extent of potential biases in spaxels which are spatially adjacent to spaxels identified as non-star forming (non-SF) on a BPT diagram. We identify a sample of $\sim21,000$ such spaxels with calculable metallicities from the full metallicity catalogue ($\sim$1.57 million), representing a small fraction ($\sim1.3$ per cent) of the full metallicity sample. $\sim$23 per cent of all galaxies with at least one spaxel with a calculable metallicity also contain at least one spaxel with a calculated metallicity adjacent to a non-SF spaxel, with a typical galaxy hosting 9 non-SF-adjacent spaxels. From our suite of 6 different metallicity calibrations, we find that only the metallicity calibrations based entirely on the [NII]$_{6584}$/H$\alpha$ ratio are affected, showing systematic offsets to higher metallicities by up to $\sim$0.04 dex if they are located adjacent to a non-SF flagged spaxel, relative to a radially matched control sample. The inclusion of additional diagnostic diagrams (based on [OI]$_{6300}$~\&/or [SII]$_{6717+6731}$) is insufficient to remove the observed offset in the [NII]$_{6584}$/H$\alpha$ based calibrations. Using a stricter diagnostic line on the BPT diagram removes $\sim$94 per cent of identified bordering spaxels with metallicities for all metallicity calibrations, and removes the residual offset to higher metallicity values seen in [NII]$_{6584}$/H$\alpha$ calibrations. If science cases demand an exceptionally clean metallicity sample, we recommend either a stricter BPT cut, and/or a non-[NII]$_{6584}$/H$\alpha$ based metallicity calibration., Comment: MNRAS accepted. 21 pages, 10 figures, 3 tables, plus 3 appendix tables & 3 appendix figures

This study compares Term Frequency-Inverse Document Frequency (TF-IDF) features with Sentence Transformers for detecting writers' stances--favorable, opposing, or neutral--towards three significant topics: COVID-19 vaccine, digital transformation, and women empowerment. Through empirical evaluation, we demonstrate that Sentence Transformers outperform TF-IDF features across various experimental setups. Our team, dzStance, participated in a stance detection competition, achieving the 13th position (74.91%) among 15 teams in Women Empowerment, 10th (73.43%) in COVID Vaccine, and 12th (66.97%) in Digital Transformation. Overall, our team's performance ranked 13th (71.77%) among all participants. Notably, our approach achieved promising F1-scores, highlighting its effectiveness in identifying writers' stances on diverse topics. These results underscore the potential of Sentence Transformers to enhance stance detection models for addressing critical societal issues., Comment: Accepted for publication in the conference proceedings of ArabicNLP 2024

Ad-hoc networks are specifically designed to facilitate communication in environments where establishing a dedicated network infrastructure is exceedingly complex or impractical. The integration of clustering concepts into various ad-hoc network scenarios, including Wireless Sensor Networks (WSN), Mobile Ad-hoc Networks (MANET), Vehicular Ad-hoc Networks (VANET), Delay-Tolerant Networks (DTN), Wireless Ad-hoc Networks (WANET), Underwater Wireless Sensor Networks (UWSN), Unmanned Aerial Vehicle Networks (UAV), commonly known as "drones," Space Networks (SN), and Satellite Networks (TN), presents abundant opportunities for refining strategies in event tracking and area monitoring across both deterministic and uncertain environments. This paper conducts a comparative analysis of diverse proposed strategies leveraging clustering concepts to address coverage challenges within deterministic and uncertain environments. As a result, it addresses current and future challenges inherent in clustering-based WANET, elucidating the merits, shortcomings, and weaknesses of clustering models. Lastly, it identifies potential avenues for addressing coverage issues in existing and emerging technologies., Comment: 12 pages, 5 figures, conference

Uncrewed aerial vehicles (UAVs) have attracted recent attention for sixth-generation (6G) networks due to their low cost and flexible deployment. In order to maximize the ever-increasing data rates, spectral efficiency, and wider coverage, technologies such as reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) are adapted with UAVs (UAV-RIS NOMA). However, the error performance of UAV-RIS NOMA has not been considered, yet. In this letter, we investigate the error probability of UAV-RIS NOMA systems. We also consider the practical constraints of hardware impairments (HWI) at the transceivers, inter-cell interference (ICI), and imperfect successive interference cancellation (SIC). The analytical derivations are validated by Monte-Carlo simulations. Our results demonstrate that our proposed system achieves higher performance gain (more than 5 dB with increasing the number of RIS elements) with less error probability compared to UAVs without RIS. Moreover, it is found that the HWI, ICI, and imperfect SIC have shown a negative impact on the system performance.

In order to bolster future wireless networks, there has been a great deal of interest in non-terrestrial networks, especially aerial platforms including high-altitude platform stations (HAPS) and uncrewed aerial vehicles (UAVs). These platforms can integrate advanced technologies such as reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA). In this regard, this paper proposes a multi-layer network architecture consisting of HAPS and UAV, where the former acts as a HAPS super macro base station (HAPS-SMBS), while the latter serves as a relay node for the ground Internet of Things (IoT) devices. The UAV is equipped with active transmissive RIS, which is a novel technology with promising benefits. We also utilize multiple-input single-output (MISO) technology, i.e., multiple antennas at the HAPS-SMBS and a single antenna at the IoT devices. Additionally, we consider NOMA as the multiple access technology as well as the existence of hardware impairments as a practical limitation. We compare the proposed system model with various scenarios, all involving the HAPS-SMBS and RIS-equipped UAV relay combination, but with different types of RIS, antenna configurations, and access technologies. Sum rate and energy efficiency are used as performance metrics, and the findings demonstrate that, in comparison to all benchmarks, the proposed system yields significant performance gains. Moreover, hardware impairment limits the system performance at high transmit power levels., Comment: IEEE Wireless Communications and Networking Conference (WCNC) 2025, Milan, Italy

Non-orthogonal multiple access (NOMA) has been a strong candidate to support massive connectivity in future wireless networks. In this regard, its implementation into cooperative relaying, named cooperative-NOMA (CNOMA), has received tremendous attention by researchers. However, most of the existing CNOMA studies have failed to address practical constraints since they assume ideal conditions. Particularly, error performance of CNOMA schemes with imperfections has not been investigated, yet. In this letter, we provide an analytical framework for error performance of CNOMA schemes under practical assumptions where we take into account imperfect successive interference canceler (SIC), imperfect channel estimation (ICSI), and hardware impairments (HWI) at the transceivers. We derive bit error rate (BER) expressions in CNOMA schemes whether the direct links between source and users exist or not which is, to the best of the authors' knowledge, the first study in the open literature. For comparisons, we also provide BER expression for downlink NOMA with practical constraints which has also not been given in literature, yet. The theoretical BER expressions are validated with computer simulations where the perfect-match is observed. Finally, we discuss the effects of the system parameters (e.g., power allocation, HWI level) on the performance of CNOMA schemes to reveal fruitful insights for the society., Comment: submitted to IEEE

Cooperative non-orthogonal multiple access (CNOMA) has recently been adapted with energy harvesting (EH) to increase energy efficiency and extend the lifetime of energy-constrained wireless networks. This paper proposes a hybrid EH protocol-assisted CNOMA, which is a combination of the two main existing EH protocols (power splitting (PS) and time switching (TS)). The end-to-end bit error rate (BER) expressions of users in the proposed scheme are obtained over Nakagami-$m$ fading channels. The proposed hybrid EH (HEH) protocol is compared with the benchmark schemes (i.e., existing EH protocols and no EH). Based on the extensive simulations, we reveal that the analytical results match perfectly with simulations which proves the correctness of the derivations. Numerical results also show that the HEH-CNOMA outperforms the benchmarks significantly. In addition, we discuss the optimum value of EH factors to minimize the error probability in HEH-CNOMA and show that an optimum value can be obtained according to channel parameters., Comment: submitted to IEEE