Search Results (95)

The rapid expansion in unmanned aerial vehicles (UAVs) across various sectors, such as surveillance, agriculture, disaster management, and infrastructure inspection, highlights the growing need for robust navigation systems. However, this growth also exposes critical vulnerabilities, particularly in UAV package delivery operations, where intentional electromagnetic interference (IEMI) poses significant security and safety threats. This paper addresses IEMI attacks targeting inertial measurement units (IMUs) in UAVs, focusing on their susceptibility to medium-power electromagnetic interference. Our approach combines a comprehensive literature review and QuickField simulation with experimental validation using a commercially available 6-degree-of-freedom (DOF) IMU sensor. We propose a hardware-based electromagnetic shielding solution using mu-metal to mitigate IEMI’s impact on sensor performance. The study combines experimental testing with simulations to evaluate the shielding effectiveness under controlled conditions. The results of the measurements showed that medium-power IEMI significantly distorted IMU sensor readings, but our proposed shielding method effectively reduces the impact, improving sensor reliability. We demonstrate the mechanisms by which medium-power IEMI disrupts sensor operation, offering insights for future research directions. These findings also highlight the importance of integrating hardware-based shielding solutions to safeguard UAV systems against electromagnetic threats. Full article

Precise trajectory planning is crucial in terms of enabling unmanned aerial vehicles (UAVs) to execute interference avoidance and target capture actions in unknown environments and when facing intermittent target loss. To address the trajectory planning problem of UAVs in such conditions, this paper proposes a UAV trajectory planning system that includes a predictor and a planner. Specifically, the system employs a bidirectional Temporal Convolutional Network (TCN) and Gated Recurrent Unit (GRU) network algorithm with an adaptive attention mechanism (BITCN-BIGRU-AAM) to train a model that incorporates the historical motion trajectory features of the target and motion intention the inferred by a Dynamic Bayesian Network (DBN). The resulting predictions of the maneuvering target are used as terminal inputs for the planner. An improved Radial Basis Function (RBF) network is utilized in combination with an offline–online trajectory planning method for real-time obstacle avoidance trajectory planning. Additionally, considering future practical applications, the predictor and planner adopt a parallel optimization and correction algorithm structure to ensure planning accuracy and computational efficiency. Simulation results indicate that the proposed method can accurately avoid dynamic interference and precisely capture the target during tasks involving dynamic interference in unknown environments and when facing intermittent target loss, while also meeting system computational capacity requirements. Full article

Generally, various technologies, including waveguide below cutoff (WBC), gasket sealing, and bonding, are employed in metallic enclosures to achieve the high electromagnetic shielding performance required for EMP protection and EMC countermeasures in shielding structures or facilities. While the shielding structure or facility is properly constructed and maintained according to design specifications, its electromagnetic shielding performance can remain at the required level, effectively protecting internal electrical and electronic equipment from external electromagnetic interference. However, unintended apertures often occur during the construction or maintenance of shielding facilities, compromising their shielding performance. Therefore, it is crucial to develop technologies that prevent shielding effectiveness degradation caused by both intentional and unintentional apertures. This paper proposes a structure incorporating a composite absorber (made of dielectric and magnetic absorber) within a double metal panel of enclosure featuring an aperture, aimed at maintaining and improving the facility’s shielding performance. The effectiveness of the proposed structure was validated through numerical simulation. Full article

Background and Objectives: To evaluate the effectiveness of an integral HAMMAM experience, a 4-week therapeutic program that combined hydrotherapy and Swedish massage, applied in a multisensorial immersive environment, on pain, well-being and quality of life (QoL) in women with endometriosis-related chronic pelvic pain that is unresponsive to conventional treatment. Materials and Methods: This randomized controlled trial included 44 women with endometriosis. They were randomly allocated to either the ‘HAMMAM’ group (n = 21) or to a control group (n = 23). The primary outcome, pain intensity, was evaluated using numeric rating scales (NRSs). The secondary outcomes were pain interference, pain-related catastrophic thoughts, pressure pain thresholds (PPTs), subjective well-being, functional capacity and QoL, which were evaluated using the brief pain inventory (BPI), the pain catastrophizing scale (PCS), algometry, the subjective well-being scale-20 (EBS-20), the Patient-Reported Outcomes Measurement Information System-29 (PROMIS-29) and the Endometriosis Health Profile-30 Questionnaire (EHP-30), respectively. The primary and secondary outcomes were measured at the baseline and after the intervention. The statistical (between-group analyses of covariance) and clinical effects were analyzed by the intention to treat. Results: The adherence rate was 100.0% and the mean (± standard deviation) satisfaction was 9.71 ± 0.46 out of 10. No remarkable health problems were reported during the trial. The ‘HAMMAM’ intervention improved dysmenorrhea and dyspareunia after the intervention with large and moderate effect sizes, respectively. Improvements in pain interference during sleep and PPTs in the pelvic region were also observed in women allocated to the ‘HAMMAM’ group. No effects were observed in catastrophizing thoughts, well-being nor QoL, except for the sleep subscale. Conclusions: A 4-week program of an integral ‘HAMMAM’ experience combining hydrotherapy and massage in a multisensorial immersive environment is a feasible and effective intervention to alleviate pain during menstruation and sexual intercourse as well as pain interference with sleep in women with endometriosis. Full article

Background: Developed countries report specific issues regarding the declining midwifery workforce, and their shortage could have serious consequences for women’s sexual and reproductive health. The aim was to understand the perception of autonomy among midwives working in Spain, as well as factors related to their intention to leave the profession and their work environment. Method: A descriptive and cross-sectional study using an online questionnaire. Population: midwives working in Spain in any field (clinical, research, teaching, or management). Results: A sample of 1060 midwives was obtained. Of these, 53.7% (n = 569) feel autonomous in their work, 92.4% (n = 978) perceive that their profession frequently suffers from external interference, 46.6% (n = 494) have experienced sexist behaviors at work, and 53% (n = 561) have considered leaving the profession in the last year. Midwives with less than 10 years of experience (57.7%), those aged 31–45 years (59.8%), those with temporary contracts (38.3%), and those working in hospital care (71.9%) show a higher rate of considering leaving the profession (p < 0.001). Conclusions: Considering the current midwifery workforce crisis in Spain, it seems urgent to improve the working conditions of midwives to ensure the continuity and quality of women’s sexual and reproductive healthcare. Full article

The rapid evolution of drone technology has introduced unprecedented challenges in security, particularly concerning the threat of unconventional drone and swarm attacks. In order to deal with threats, drones need to be classified by intercepting their Radio Frequency (RF) signals. With the arrival of Sixth Generation (6G) networks, it is required to develop sophisticated methods to properly categorize drone signals in order to achieve optimal resource sharing, high-security levels, and mobility management. However, deep ensemble learning has not been investigated properly in the case of 6G. It is anticipated that it will incorporate drone-based BTS and cellular networks that, in one way or another, may be subjected to jamming, intentional interferences, or other dangers from unauthorized UAVs. Thus, this study is conducted based on Radio Frequency Fingerprinting (RFF) of drones identified to detect unauthorized ones so that proper actions can be taken to protect the network’s security and integrity. This paper proposes a novel method—a Composite Ensemble Learning (CEL)-based neural network—for drone signal classification. The proposed method integrates wavelet-based denoising and combines automatic and manual feature extraction techniques to foster feature diversity, robustness, and performance enhancement. Through extensive experiments conducted on open-source benchmark datasets of drones, our approach demonstrates superior classification accuracies compared to recent benchmark deep learning techniques across various Signal-to-Noise Ratios (SNRs). This novel approach holds promise for enhancing communication efficiency, security, and safety in 6G networks amidst the proliferation of drone-based applications. Full article

Background/Objectives: The most important prognostic factors in curatively treated prostate cancer are T and N stage, histology, grade group and initial PSA. A recent study found that men with blood calcium levels at the high end of the normal range are over two-and-a-half times more likely to develop fatal prostate cancer than those with lower calcium levels. However, there is limited evidence regarding the prognostic value of calcium levels at the time of prostate cancer diagnosis. We aimed to determine whether a calcium level in the upper range of normal values has any prognostic value in curatively treated prostate cancer. Methods: We conducted a retrospective analysis of 84 consecutive patients with prostate cancer who underwent curative-intent radiotherapy—either as primary treatment or adjuvant therapy—using external beam radiotherapy with or without brachytherapy. We analyzed all pertinent prognostic factors that could potentially impact disease-free survival. Results: The study revealed that calcium levels at diagnosis significantly predict disease-free survival, whereas the initial PSA level did not hold prognostic significance—likely due to interference from benign prostatic hyperplasia. Conclusions: If our findings are validated, calcium levels at the time of prostate cancer diagnosis could be incorporated into future predictive and prognostic models. Full article

Intentional electromagnetic interference attacks (e.g., jamming) against wireless connected devices such as the Internet of Things (IoT) remain a serious challenge, especially as such attacks evolve in complexity. Similarly, eavesdropping on wireless communication channels persists as an inherent vulnerability that is often exploited by adversaries. This article investigates a novel approach to enhancing information security for IoT systems via collaborative strategies that can effectively mitigate attacks targeting availability via interference and confidentiality via eavesdropping. We examine the proposed approach for two use cases. First, we consider an IoT device that experiences an interference attack, causing wireless channel outages and hindering access to transmitted IoT data. A physical-layer-based security (PLS) transmission strategy is proposed in this article to maintain target levels of information availability for devices targeted by adversarial interference. In the proposed strategy, select IoT devices leverage a cooperative transmission approach to mitigate the IoT signal outages under active interference attacks. Second, we consider the case of information confidentiality for IoT devices as they communicate over wireless channels with possible eavesdroppers. In this case, we propose a collaborative transmission strategy where IoT devices create a signal outage for the eavesdropper, preventing it from decoding the signal of the targeted devices. The analytical and numerical results of this article illustrate the effectiveness of the proposed transmission strategy in achieving desired IoT security levels with respect to availability and confidentiality for both use cases. Full article

Session-based recommendations which aim to predict subsequent user–item interactions based on historical user behaviour during anonymous sessions can be challenging to carry out. Two main challenges need to be addressed and improved: (1) how does one analyze these sessions to accurately and completely capture users’ preferences, and (2) how does one identify and eliminate any interference caused by noisy behavior? Existing methods have not adequately addressed these issues since they either neglect the valuable insights that can be gained from analyzing consecutive groups of items or fail to take these noisy data in sessions seriously and handle them properly, which can jointly impede recommendation systems from capturing users’ real intentions. To address these two problems, we designed a multi-order semantic denoising (MSD) model for session-based recommendations. Specifically, we grouped items of different lengths into varying multi-order semantic units to mine the user’s primary intentions from multiple dimensions. Meanwhile, a novel denoising network was designed to alleviate the interference of noisy behavior and provide a more precise session representation. The results of extensive experiments on three real-world datasets demonstrated that the proposed MSD model exhibited improved performance compared with existing state-of-the-art methods in session-based recommendations. Full article

Synthetic-aperture radar (SAR) can work in all weather conditions and at all times, and satellite-borne radar has the characteristics of short revisiting period and large imaging width. Therefore, satellite-borne synthetic-aperture radar has been widely deployed, and the SAR images have been widely used in geographic mapping, radar interpretation, ship detection, and other fields. Satellite-borne synthetic-aperture radar is also susceptible to various types of intentional or unintentional interference during the imaging process, and because the interference is a direct wave, its power is much stronger than the wave reflected by targets. As a common interference pattern, radio-frequency interference widely exists in various satellite-borne synthetic-aperture radars, which seriously deteriorates SAR image quality. In order to solve the above problems, this paper proposes a feature decomposition network to suppress interference based on regularization optimization. The contributions of this work are as follows: 1. By analyzing the performance limitations of the existing methods, this work proposes a novel regularization method for radio-frequency interference suppression tasks. From the perspective of data distribution histograms and residual components, the proposed method eliminates the variable components introduced by common regularization, greatly reduces the difficulty of data mapping, and significantly improves its robustness and performance. 2. This work proposes a feature decomposition network, where the feature decomposition module contains two parts; one part only represents the interference signal, and the other part only represents the radar signal. The neurons representing the interference signal are discarded, and the neurons representing the radar signal are used as input for the subsequent network. A cosine similarity constraint is used to separate the interference from the network as much as possible. Finally, this method is validated on the MiniSAR dataset and Sentinel-1A dataset. Full article

Complete surgical resection in the context of a multimodal approach has been associated with excellent long-term survival in children diagnosed with pancreatoblastoma (PB). Traditionally, curative intent surgery for PB implies standard pancreatic resections such as pancreaticoduodenectomies and distal pancreatectomies with splenectomies, surgical procedures that may lead to significant long-term pancreatic functional deficiencies. Postoperative pancreatic functional deficiencies are particularly interesting to children because they may interfere with their development, considering their long life expectancy and the significant role of pancreatic functions in their nutritional status and growth. Thus, organ-sparing pancreatectomies, such as spleen-preserving distal pancreatectomies and central pancreatectomies, are emerging in specific tumoral pathologies in children. However, data about organ-sparing pancreatectomies’ potential role in curative-intent PB surgery in children are scarce. Based on the literature data, the current review aims to present the early and late outcomes of pancreatectomies in children (including long-term deficiencies and their potential impact on the development and quality of life), particularly for PB, and further explore the potential role of organ-sparing pancreatectomies for PB. Organ-sparing pancreatectomies are associated with better long-term pancreatic functional outcomes, particularly central pancreatectomies, and have a reduced impact on children’s development and quality of life without jeopardizing their oncological safety. The long-term preservation of pancreatic functions should not be disregarded when performing pancreatectomies for PB in children. A subset of patients with PB might benefit from organ-sparing pancreatectomies, particularly from central pancreatectomies, with the same oncological results as standard pancreatectomies but with significantly less impact on long-term functional outcomes. Full article

Since the integration of electronic devices and intelligent electronic devices into the power grid, power quality (PQ) has consistently remained a significant concern for system operators and experts. Maintaining high standards of power quality is crucial to preventing malfunctions and faults in electric assets and connected loads. Recently, PQ studies have shifted their focus to a specific frequency range, previously not considered problematic—the supraharmonic 2 kHz to 150 kHz range. This range is not populated by easily recognizable harmonic components of the 50 Hz to 60 Hz mains fundamental, but by a combination of intentional emissions, switching non-linearities and byproducts, and various types of resonances. This paper aims to provide a detailed analysis of the impact of supraharmonics (SHs) on power network operation and assets, focusing on the most relevant documented negative effects, namely power loss and the heating of grid elements, aging of dielectric materials, failure of medium voltage (MV) cable terminations, and interference with equipment and power line communication (PLC) technology in particular. Under some shareable assumptions, limits are derived and compared to existing ones for harmonic phenomena, providing a clear identification of the primary issues associated with supraharmonics and suggestions for the standardization process. Strictly related is the problem of grid monitoring and assessment of SH distortion, discussing the suitability of normative requirements for instrument transformers (ITs) with a specific focus on their accuracy. Full article

Background: Vasomotor symptoms (VMSs) associated with menopause represent a significant challenge for many patients after cancer treatment, particularly if conventional menopausal hormone therapy (MHT) is contraindicated. Methods: The Menopause after Cancer (MAC) Study (NCT04766229) was a single-arm phase II trial examining the impact of a composite intervention consisting of (1) the use of non-hormonal pharmacotherapy to manage VMS, (2) digital cognitive behavioral therapy for insomnia (dCBT-I) using Sleepio (Big Health), (3) self-management strategies for VMS delivered via the myPatientSpace mobile application and (4) nomination of an additional support person/partner on quality of life (QoL) in women with moderate-to-severe VMS after cancer. The primary outcome was a change in cancer-specific global QoL assessed by the EORTC QLC C-30 v3 at 6 months. Secondary outcomes included the frequency of VMS, the bother/interference of VMS and insomnia symptoms. Results: In total, 204 women (82% previous breast cancer) with a median age of 49 years (range 28–66) were recruited. A total of 120 women completed the protocol. Global QoL scores increased from 62.2 (95%CI 58.6–65.4) to 70.4 (95%CI 67.1–73.8) at 6 months (p < 0.001) in the intention to treatment (ITT) cohort (n = 204) and from 62 (95%CI 58.6–65.4) to 70.4 (95%CI 67.1–73.8) at 6 months (p < 0.001) in the per-protocol (PP) cohort (n = 120). At least 50% reductions were noticed in the frequency of VMS as well as the degree of bother/interference of VMS at six months. The prevalence of insomnia reduced from 93.1% at the baseline to 45.2% at 6 months (p < 0.001). The Sleep Condition Indicator increased from 8.5 (SEM 0.4) to 17.3 (SEM 0.5) (p < 0.0005) in the ITT cohort and 7.9 (SEM 0.4) to 17.3 (SEM 0.5) (p < 0.001) in the PP cohort. Conclusions: A targeted composite intervention improves the quality of life for cancer patients with frequent and bothersome vasomotor symptoms with additional benefits on frequency, the bother/interference of VMS and insomnia symptoms. Full article

An electromagnetic cloaking approach is employed with the intention to curb the destructive effects of mutual interference for rectangular and circularly shaped patch antennas situated in a tight spacing. Primarily, we show that by coating the top surface of each patch with an appropriately designed metasurface, the mutual coupling is considerably reduced between the antennas. Furthermore, the cloak construct is extended to a tightly spaced, interleaved linear patch antenna array configuration and it is shown that the coated metasurfaces successfully enhance the performance of each array in terms of their matching characteristics, total efficiencies and far-field realized gain patterns for a broad range of beam-scan angles. For rectangular patches, the cloaked Array I and II achieve corresponding peak total efficiencies of 93% and 90%, in contrast to the total efficiencies of 57% and 21% for uncloaked Array I and II, respectively, at their operating frequencies. Moreover, cloaked rectangular Array I and II exhibit main lobe gains of 13.2 dB and 13.8 dB, whereas uncloaked Array I and II only accomplish main lobe gains of 10 dB and 5.5 dB, respectively. Likewise, for the cloaked circular patches, corresponding total efficiencies of 91% and 89% are recorded for Array I and II, at their operating frequencies (uncloaked Array I and II show peak efficiencies of 71% and 55%, respectively). The main lobe gain for each cloaked circular patch array is approximately 14.2 dB, whereas the uncloaked Array I and II only achieve maximum gains of 10.5 dB and 7.5 dB, respectively. Full article

The past decade has shown a growing awareness of the dangers of intentional interference (especially jamming and spoofing) with GNSS signals. The Antiference project uses reconfigurable digital signal processing methods in the detection, classification, and mitigation of interference by employing machine learning techniques. The ML-based jamming classifier uses distinctive features of spectrograms for the differentiation of various jamming attacks. A residual neural net is used to map the spectrograms to the different jamming types. It relies on a fingerprinting architecture. Fingerprints summarize the characteristics of all the incoming signals, which are stored in and matched to a database of previously encountered interference types. To validate the implemented functionalities, a developed test-bed runs test scenarios and benchmarks the results against two state-of-the-art COTS receivers with interference mitigation capabilities. Full article