Radio Frequency - Science topic

Purpose: This paper explores the factors influencing bilateral trade between Egypt and BRICS by employing classic econometric techniques and machine learning methods, specifically Poisson Newton-Raphson, gradient boosting (GB), and random forest (RF). Design/methodology/: The investigation utilizes traditional econometric analysis (Poisson Newton-R...

One of the most common causes of road accidents is driver behavior. To reduce abnormal driver behavior, it must be detected early on. Previous research has demonstrated that behavioral and physiological indicators affect drivers' performance. The goal of this study is to consider the feasibility of classifying driver behavior as either aggressive (...

The demand for stable and tunable laser sources is steadily growing across a wide range of applications. Optical Frequency Combs (OFCs) have emerged as a powerful reference standard, offering stable frequency spacing between the comb tones or high optical frequency stability. To obtain low-cost tunable lasers with their carriers or relative frequen...

Synoptic weather patterns (SWPs) and human activities are significant driving factors of the canopy urban heat island effect (CUHI), and the CUHI phenomenon exhibits a pronounced diurnal cycle. However, to date, there has been a significant knowledge gap in understanding how the combination of SWPs and human activities modulates the diurnal cycle o...

Depression presents a significant challenge to global mental health, often intertwined with factors including oxidative stress. Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present an avenue for further investigation. This study employed advanced machine learning techniques to cl...

ChatGPT is a large language model built by OpeanAI. It is based on an architecture called the Generative pre-trained transformer (GPT). It can generate text that appears to be written by a human and understands natural languagequestions. We want to investigate whether we can distinguish between query results from web search and ChatGPT byutilizing...

This paper introduces the bitstream Photon Counting Chirped Amplitude Modulation (AM) Lidar (PC-CAML) with a Digital Logic Local Oscillator (DLLO) concept in various configurations. Rather than using a radio-frequency (RF) analog local oscillator (LO) applied electronically either in post-detection mixing or via opto-electronic mixing (OEM) at the...

Dynamic metasurface antennas (DMAs) are promising alternatives to fully digital (FD) architectures, enabling hybrid beamforming via low-cost reconfigurable metasurfaces. In DMAs, holographic beamforming is achieved through tunable elements by Lorentzian-constrained holography (LCH), significantly reducing the need for radio-frequency (RF) chains an...

Citation: Faiella, E.; D'amone, G.; Ragone, R.; Pileri, M.; Vergantino, E.; Zobel, B.B.; Grasso, R.F.; Santucci, D.

Objective. Local pulse wave velocity (PWV) plays a crucial role in assessing the regional arterial elasticity. Accurate estimation of local PWV is beneficial for the risk assessment and early diagnosis of cardiovascular diseases. In this study, a method involving incident waves based on coherent plane wave compounding ultrasound (IWCU) is proposed...

Predicting battery capacity is essential for enhancing battery management systems (BMSs), ensuring safety, and extending battery life. However, lithium-ion battery faces the challenge of performance degradation over the period due to electrochemical phenomena. It can be addressed with data-driven techniques to estimate the battery capacity and rema...

Magnonics is a promising platform for integrated radio frequency (rf) devices, leveraging its inherent non-reciprocity and reconfigurability. However, the efficiency of spin-wave transducers driven by rf-currents remains a major challenge. In this study, we systematically investigate a spin-wave transducer composed of micron-sized rf antennas on yt...

Superconducting circuits provide a versatile and controllable platform for studies of fundamental quantum phenomena as well as for quantum technology applications. A conventional technique to read out the state of a quantum circuit or to characterize its properties is based on RF measurement schemes. Here we demonstrate a simple DC measurement of a...

This paper shows a comprehensive analysis of three algorithms (Time Series, Random Forest (RF) and Deep Reinforcement Learning) into three inventory models (the Lost Sales, Dual-Sourcing and Multi-Echelon Inventory Model). These methodologies are applied in the supermarket context. The main purpose is to analyse efficient methods for the data-drive...

This paper presents a novel approach to simultaneous transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RIS) for energy harvesting from both radio frequency (RF) signals and vibrations. STAR-RIS technology aims to enhance wireless communication networks by integrating communication and energy harvesting capabilities into a sing...

A helical resonator with a certain resonant frequency and a high-quality factor (Q-factor) is critical for an ion trap system, which results in a larger trap depth, longer trap time, and lower radiofrequency (RF) noise. Here, we propose a new method for driving amplitude-adjustable multiple RF ion trap electrodes. By dividing the output of the heli...

Predictive Maintenance (PdM) plays an integral role in modern manufacturing by minimizing downtime, enhancing efficiency, and reducing costs. However, many existing approaches struggle with noisy data, limited interpretability, and inadequate scalability. This research introduces a hybrid Artificial Intelligence (AI) model for analyzing multivariat...

We address the radio frequency (RF) cavity experiment for probing dark photons, which is a modification of the light-shining-through-thin-wall (LSthinW) setup with a relatively thin conducting barrier between a cylindrical emitter and a hollow receiver. The experimental facility allows for the effective probing of dark photons even in the off-shell...

Coverage analysis in heterogeneous networks (HetNets) remains insufficient, especially under user mobility and diverse association strategies. To address this, this paper proposes a contact probability and coverage approximation based on association strategy (CPCA-AS) to analyze the coverage probability (CPr) in visible light communication (VLC) an...

Introduction: Imbalanced datasets cause significant issues in classification tasks that might have a negative impact on the model's performance. It frequently results in minority classes having worse predictive accuracy. This leads to lower accuracy for minority classes. This issue affects model performance and risks missing crucial insights that i...

Beamforming provides transmission/reception directivity gains that compensate for the high propagation loss encountered at millimeter-wave (mmWave) and sub-THz bands. However, narrow beams introduce significant beam misalignment challenges. Providing fast and efficient beam tracking is vital for maintaining communications and minimizing service dis...

This study examines the effect of gate recess depth on the electrical and RF performance of AlGaN/GaN high electron mobility transistors (HEMTs) before and after die‐attach. Devices with greater recess depths exhibited notably larger improvements in transconductance and RF metrics (ft, fmax) due to mechanical and thermal stresses induced by packagi...

O objetivo deste estudo foi avaliar o uso de bandas de imagens de satélite para mapear áreas agrícolas em Petrolina-PE, utilizando séries temporais e algoritmos de machine learning. Foram comparados os modelos Random Forest (RF) e Temporal Convolutional Neural Network (TempCNN) na identificação de classes de uso e cobertura da terra com ênfase em c...

Purpose: Validation of quantitative MRI (qMRI) parameters with histology is often done with ex vivo fixed tissue samples. Freezing is another common form of tissue preservation, but the effects of freezing and thawing tissue on myelin-sensitive quantitative MRI parameters and their correlation with histology require further analysis. Methods: Myeli...

We investigate the relativistic jet of the powerful radio-emitting blazar J1429+5406 at redshift z=3.015. Our understanding of jet kinematics in z>3 quasars is still rather limited, based on a sample of less than about 50 objects. The blazar J1429+5406 was observed at a high angular resolution using the method of very long baseline interferometry o...

AR Scorpii, the so called white dwarf pulsar, contains a rapidly rotating magnetic white dwarf (WD; Pspin = 117.0564 s) interacting with a cool, red dwarf (RD) companion in a 3.56 hour orbit. It is a strong radio source with an inverted spectral index between 1-200 GHz that is indicative of synchrotron emission. This paper presents the first submil...

The conventional receiver-initiated MAC (RI-MAC) protocol employed in energy-harvesting wireless sensor networks (WSNs) mandates a specific listening duration to identify communication partners, which consequently increases power consumption and impedes the development of ultralow-energy WSNs. To address these limitations, the novel zero excess nod...

This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital mortality, using machine learning models and SHapley Additive exPlanations (SHAP) analysis. Data were collected from a national Stroke Registry from January 2014 to July 2022. Various predictive factors were considered, such as stroke severity at pres...

Random Forest (RF) is a flexible machine learning algorithm that does not rely on linearity. The use of the RF method for spatial analysis is referred to as Geographically Random Forest (GRF), which can capture the effects of spatial heterogeneity. Therefore, GRF is well-suited for modeling rainfall, which exhibits spatial heterogeneity characteris...

This study aims to assess the effectiveness of various Machine learning based models in predicting the Air Quality Index (AQI) for Gurugram City, India. The Air Quality Index (AQI) pertains to many Sustainable Development Goals (SDGs), mainly those associated with health, sustainable urban development, and climate action. This analysis utilize tree...

Background In many countries, patients with headache disorders such as migraine remain under-recognized and under-diagnosed. Patients affected by these disorders are often unaware of the seriousness of their conditions, as headaches are neither fatal nor contagious. In many cases, patients with migraine are often misdiagnosed as regular headaches....

The study of mutations is fundamental to understanding evolution, domestication, and genetics. Characterizing mutations has the potential to accelerate breeding programs through selection and purging of deleterious mutations (DelMut). Here, we investigated how predicting DelMut in breeding populations can improve genomic prediction (GP) and inform...

The ability to accurately predict and analyze student performance in online education, both at the outset and throughout the semester, is vital. Most of the published studies focus on binary classification (Fail or Pass) but there is still a significant research shortcoming in predicting performance of students across multiple categories. This stud...

INTRODUCTION Medical conditions including obesity, diabetes, hyperlipidemia, and depression significantly increased risk of Alzheimer's disease (AD). However, effect of their duration, influenced by non‐modifiable factors like chromosomal sex and apolipoprotein E (APOE) genotype, remains unclear. METHODS Data from 5644 UKBiobank participants were...

We present new, high frequency radio observations of the merging galaxy clusters PLCK G287.0+32.9, Abell 2744, and Bullet. These clusters are known to host $\sim$Mpc scale sources, known as radio halos, which are formed by the acceleration of cosmic rays by turbulence injected into the intracluster medium during cluster mergers. Our new images reve...

Most of the research studies are focused on detecting dynamic changes in non-linear time series with the entropy-based methods and intensifying the fault diagnostic performance in rotational machines. However, the investigations in multi-signal fusion and multi-component fault detection with reduced computation complexity are still unexplored with...

Radio Frequency signal modulation classification is essential for spectrum monitoring systems but remains challenging in low Signal-to-Noise Ratio (SNR) environments. While state-of-the-art (SOTA) methods achieve only 30-35% accuracy at-20 dB SNR, we introduce RF-DDPM, a Denoising Diffusion Probabilistic Model architecture specifically designed for...

Providing efficient and reliable content delivery in rural areas remains a significant challenge due to the lack of communication infrastructure. To bridge the digital divide, this paper investigates the potential of leveraging multiple high-altitude platforms (HAPs) for energy-efficient content delivery in wide rural regions. Each caching-enabled...

Topographical and geological conditions are typically regarded as the primary causes of landslides. However, accurately estimating landslide volumes on rock slopes using empirical equations remains challenging. In contrast, data science approaches, such as machine learning, leverage advanced data integration and processing capabilities, significant...

Neural operators have demonstrated promise in modeling and controlling systems governed by Partial Differential Equations (PDEs). Beyond PDEs, Stochastic Partial Differential Equations (SPDEs) play a critical role in modeling systems influenced by randomness, with applications in finance, physics, and beyond. However, controlling SPDE-governed syst...

Thermoelectric generators (TEGs) leveraging commercially available thermal super-insulating materials offer a promising pathway for large-scale ambient waste heat recovery, adding economic and environmental value to industrial insulation systems. Achieving this requires optimizing thermoelectric (TE) properties through electrical functionalization...

Rationale and objectives Neoadjuvant chemotherapy (NAC) is a promising therapeutic strategy for managing locally advanced gastric cancer (LAGC), aiming to reduce tumor burden, enhance resection rates, and improve clinical outcomes. Due to variability in patient responses, the objective of this study was to enhance the prediction of NAC tumor regres...

This study investigates the use of gas jet injection to mitigate both radio frequency blackouts and aerodynamic heating experienced by spacecraft during atmospheric reentry. The key concept behind this approach is that the injected gas forms a thin air film layer around the spacecraft. This air film acts as an insulating layer, reducing heat transf...

Inductive plasma sources: Transmission Lene Plasma Sources Lambda-Resonator Plasma Source Gamma-Resonator Plasmqa Source Industrial plasma sources RF standing wave discharges High Density Plasma Radical Plasma Sources High-power remote plasma source Capacitive problem of inductive plasma sources (ICP) Capacitively balanced plasma source concept Vin...

Modern industry heavily relies on inductively coupled plasmas for the generation of energetic ions. In electric propulsion, these ions generate thrust. In the semiconductor industry, they are used to etch high aspect ratio features. In materials science, they are crucial in the deposition and modification of thin films, which are essential for deve...

This study evaluates the performance of binary classifications of burned areas using satellite imagery time series provided by the WFI sensors on board the CBERS-4A and AMAZONIA-1 satellites. Five machine learning algorithms were applied for supervised classification: Support Vector Machine (SVM), Random Forest (RF), XGBoost, Simple Recurrent Neura...

Accurate slope stability prediction is crucial for mitigating slope failures, but conventional methods are challenging due to their complexity and high data requirements. To overcome these limitations, researchers have used machine learning (ML) techniques enabled by advances in data science. This paper presents an innovative ML approach, which com...

Historians rightfully insist on learning from history. Indeed, history tends to repeat itself - just as mankind stubbornly tends to ignore that fact. Bruce Cumings’ historical take on the succession issue in the DPRK is thus an important and welcome addition to the many different voices that have tried to make sense of what is happening and to prov...

This study employs Particle-In-Cell/Monte Carlo Collision simulations to examine the magnetized radio frequency sheath resonance heating mechanism in a voltage-driven discharge using a dual-frequency source. The effects of low-frequency (LF) voltage, high-frequency (HF) voltage, and pressure on the resonance heating mechanism are well examined. Inc...

Radio frequency capacitively coupled plasmas (RF CCPs) operated in Ar/O ² gas mixtures which are widely adopted in microelectronics, display and photovoltaic industry, are investigated based on an equivalent circuit model coupled with a global model. This study focuses on the effects of singlet metastable molecule O 2 ( b ¹ Σ g ⁺ ), highly excited...

Air discharge originates from the interaction between electric field (EF) and the meteorological environment, and the dielectric strength of a long air gap is affected by both EF distribution and atmospheric parameters. A regularization‐logistic regression (R‐LR) model is proposed for the accurate calculation of long air gap discharge voltage at hi...

The accurate prediction of river discharge is essential in water resource management, particularly under variability due to climate change. Traditional hydrological models commonly struggle to capture the complex, nonlinear relationships between climate variables and river discharge, leading to uncertainties in long-term projections. To mitigate th...

The present investigation elucidates the prediction of crack length (a) and fatigue crack growth rate (FCGR), in the TP316L stainless steel pipe during four-point bending, using different approaches— ridge regression (RR), random forest (RF), and polynomial regression (Poly.) machine learning (ML) modelling. The FGCR i.e., da/dN, in the radial dire...

This work demonstrated a passive mode-locked ytterbium-doped fiber laser operating at a 1-micron region. The saturable absorber incorporated was a Ti3C2Tx/MoO3 deposited on a D-shaped fiber, generating stable dissipative soliton in all normal dispersion regimes. The all-fiber ring cavity laser configuration generates mode-locked pulses with a repet...

This paper put forward a hybrid energy harvester for collecting RF and solar energy in quad-band (GSM-900/1800, ISM-2400 and WiMAX-3500). By introducing diverse parasitic structures, good impedance matching with unidirectional radiation is achieved in the multi-band. Below the solar antenna, a low-power rectifier circuit is employed to achieve broa...

Rotating saddle potentials provide a compelling visual demonstration of dynamic stability, widely used in undergraduate physics as mechanical analogs to the RF Paul trap. Traditional demonstrations typically rely on rolling ball bearings, whose frictional effects and internal rotation obscure fundamental particle dynamics. We introduce a simple yet...

Accurate tunnel deformation prediction is critical for mitigating construction risks and ensuring tunnel stability. This study introduces a novel hybrid model integrating long short-term memory (LSTM) networks and random forest (RF) to enhance the precision of tunnel deformation predictions during construction. Bayesian optimization was utilized to...

With the huge financial transfers taking place over the Internet, it is necessary to provide precise mechanisms to ensure that financial fraud does not occur. In this study, a new framework was proposed that combines deep learning and Ensemble techniques using the stacking mechanism to detect financial fraud. The Random Forest (RF) and Multilayer P...

Human thoughts, feelings, and ideas are expressed through speech. Stuttering, also referred to as stammering, is an impediment to speech that affects millions of people across the globe. Stuttering speech recognition is a good deal of research within the realm of speech signal processing. Classification of eight different types of stuttering includ...

We show a distributed Bragg reflector laser operating at 1875 nm, using a hybrid silicon nitride photonic chip coated with thulium-doped tellurite glass. The passive laser cavity consists of nominally 50 nm wide sidewall Bragg gratings directly patterned in a 1.2 µm wide, 0.2 µm thick, and 22 mm long silicon nitride waveguide on a thermally-oxidize...

Optical frequency combs are increasingly used in applications such as optical communications, radio signal processing, and dual-comb spectroscopy. Many of these applications require a broad, flat spectrum with tunable center wavelength and tone spacing, while maintaining a consistent spectral profile. However, most existing OFC generators either la...

Antifragility of communication systems is defined as measure of benefits gained from the adverse events and variability of its environment. In this paper, we introduce the notion of antifragility in Reconfigurable Intelligent Surface (RIS) assisted communication systems affected by a jamming attack. We analyzed the antifragility of the two hop syst...

This paper presents a novel drain-engineered (DE) double-gate (DG) graphene nanoribbon (GNR) tunnel field-effect transistor (TFET) designed to address the limitations of conventional DG GNR-TFETs. The proposed device introduces a p⁺-n–n configuration, replacing the conventional p⁺-i-n⁺ structure by incorporating uniform n-type doping (Ncd) in both...

In this study, first, we improved an existing variant of the Nearest Centroid algorithm. In this new version, the predictive power of features and within-class variances are used as weights in distance calculation. This version is called the Enhanced Nearest Centroid (ENC). Second, we proposed a new model tree algorithm for binary classification. I...

Study Design: Anatomical study. Background: While radiofrequency ablation (RFA) is a well-established and effective treatment for lumbar facet joint syndrome (FJS), some studies have reported that pain relief in certain patients is limited, with symptoms potentially recurring within 1-2 years following medial branch RFA. A deeper understanding of t...

The performance of fans and pumps is pivotal to the efficiency and responsiveness of the engine cooling system. In this study, a joint simulation model incorporating a detailed engine cooling system was developed and calibrated using vehicle road cycle tests, and the predictive capabilities of four different machine learning models for water pump a...

Three-way integrated filtering power divider (FPD) is presented. The proposed FPD unevenly distributes an input power signal into three unequal output signals. The design incorporates unbalanced power division and filtering functionality for the removal of unwanted frequency elements and aims at enhancing signal quality and efficiency in RF front-e...

Additive manufacturing is currently regarded as one of the enabling technologies for Space Economy since it allows for the reduction of lead time and costs of payloads and platforms. Typically, metal-based additive manufacturing technologies are considered for the development of microwave components for Space applications since they exhibit the bes...

Driven by the exponential growth in data traffic and the limitations of Radio Frequency (RF) networks, Optical Wireless Communication (OWC) has emerged as a promising solution for high data rate communication. However, the inherently dynamic nature of OWC environments resulting from user mobility, and time-varying user demands poses significant cha...

El proyecto AutoForCes (MCI-21-PID2020-112839RB-I00), financiado por la Agencia Estatal de Investigación (AEI) del Ministerio de Ciencia, Innovación y Universidades (MCIN/AEI/10.13039/501100011033), es una iniciativa para la estimación automática de recursos forestales y la productividad en el norte de España (Galicia, Asturias, Cantabria y País Va...

Memes have become one of the main mediums for expressing ideas, humor, and opinions through visual-textual content on social media. The same medium has been used to propagate harmful ideologies, such as misogyny, that undermine gender equality and perpetuate harmful stereotypes. Identifying misogynistic memes is particularly challenging in low-reso...

High-speed trains with broadband service is rapidly growing as more people commute from their homes to work and vice versa, where the current available radio frequency (RF) technology could not meet. An alternative technique defined as free space optics (FSO) that could possibly overcome the bandwidth constraint problem might be easily implemented...

Ambient backscatter communication (ABC) enables low-cost and energy-efficient connectivity for Internet of Things (IoT) devices by leveraging ambient radio-frequency (RF) signals. However, the passive nature and open wireless medium of ABC systems make them vulnerable to detection by unauthorized receivers (wardens). To mitigate this risk, covert c...

Background This study aimed to develop a nomogram to predict peritoneal dialysis (PD) adequacy in incident PD patients and identify those at high risk for low Kt/Vurea PD function. Methods We retrospectively analyzed 141 incident PD patients from January 2021 to January 2024. Baseline characteristics, including BMI, hemoglobin levels, and high tra...

This study explores the optimization methods of agricultural resource allocation and their impacts on ecological and economic benefits through big data and machine learning techniques. By combining Random Forest (RF) and Genetic Algorithm (GA), the study analyzes the effects of different agricultural resource allocation schemes on ecological and ec...

The step-bunching instability in (100) β-Ga2O3 films grown via metalorganic vapor phase epitaxy was investigated using a machine learning approach based on Random Forest (RF). This study reveals the interplay of Ga supersaturation (O2/Ga) and impurity effects as coexisting mechanisms driving the morphological transition (from step-flow growth to st...

This paper presents the integration of memristors into N-path filter architectures to develop reconfigurable N-path filters with a tuneable bandwidth. Two different memristor-based N-path filter designs are proposed and systematically compared. One of the architectures was experimentally validated by interfacing it with a memristor package in a lab...

Wireless signals are integral to modern society, enabling both communication and increasingly, environmental sensing. While various propagation models exist, ranging from empirical methods to full-wave simulations, the phenomenon of electromagnetic diffraction is often treated as a secondary effect or a correction factor. This paper positions diffr...

Integrating renewable energy sources with new technologies such as artificial intelligence (AI) is important to balance energy supply and demand. The predictability of variable energy sources, such as solar energy, plays an important role in maintaining the stability and efficiency of power grids. This study examines the use of various algorithms i...

Kebutuhan akan rumah sebagai tempat tinggal utama semakin meningkat di Indonesia akibat pertumbuhan penduduk yang pesat. Selain sebagai kebutuhan dasar, rumah juga dipandang sebagai investasi berharga dengan nilai yang dapat berubah seiring waktu. Keragaman informasi harga perumahan seringkali membingungkan masyarakat dalam memilih rumah yang sesua...