Communication Applications Research Articles

Development of methods for monitoring and optimization of underground drainage systems using wireless sensor networks and ultra-wideband antennas

This research focuses on optimizing ultra-wideband (UWB) antennas, which are critical in modern communication systems due to their wide frequency range (3.1–10.6 GHz) and high data transmission capabilities. The study addresses the challenge of optimizing key antenna parameters – such as return loss, peak gain, and radiation efficiency – while also ensuring energy efficiency and network longevity. Traditional optimization methods, such as LEACH-C, often fail to balance these factors, leading to suboptimal performance. To solve this problem, the researchers developed the Generalized Position-based Optimization Neural Network (GPON) for UWB antenna optimization. They also evaluated the Position-based Hybrid Neural Network (PAN) method, comparing its performance with existing algorithms including LEACH-C, Firefly Algorithm (FA), HFAPSO, FA-ANN, and HWOABCA. The GPON model reduced return loss to 25.5 dB at 3.5 GHz and improved peak gain to 4.2 dB i, while maintaining 92 % radiation efficiency. In contrast, PAN demonstrated a 15–25 % improvement in residual energy and extended network lifetime by 20 % compared to LEACH-C. These improvements were due to the integration of advanced neural network techniques in GPON and the effective use of positional data in PAN, enabling more precise and adaptive optimization. The ability to balance multiple performance metrics simultaneously – a challenge previous models struggled with – is a key feature. This balance is crucial for UWB antennas in communication systems where both performance and energy efficiency are vital. The findings are especially relevant for practical applications in wireless sensor networks, mobile communications, and radar systems, requiring long-term network reliability and optimal antenna performance

Design and Implementation of a Partially-Grounded Dual-Band Compact Patch Antenna with Enhanced Selectivity for Multiservice Wireless Communication Applications

Design and Implementation of a Partially-Grounded Dual-Band Compact Patch Antenna with Enhanced Selectivity for Multiservice Wireless Communication Applications

Tunable phonon-photon coupling induces double MMIT and enhances slow light in an atom-opto-magnomechanics

Abstract In this paper, we theoretically investigate the magnomechanically induced transparency phenomenon, Fano resonance, and the slow/fast light effect in the situation where an atomic ensemble is placed inside the hybrid cavity of an opto-magnomechanical system. The system is driven by dual optical and phononic drives. We show double magnomechanically induced transparency (MMIT) in the probe output spectrum by exploiting the phonon-photon coupling strength. Then, we study the effects of the decay rate of the cavity and the atomic ensemble on magnomechanically induced transparency. In addition, we demonstrate that effective detuning of the cavity field frequency changes the transparency window from a symmetrical to an asymmetrical profile, resembling Fano resonances. Further, the fast and slow light effects in the system are explored. Besides, we show that the slow light profile is enhanced by adjusting the phonon-photon coupling strength. This result may have potential applications in quantum information processing and communication.

Coherent control of dressing interaction of sequential-doubly-dressed four-wave mixing

Abstract We investigate the coherent control of dressing interaction in four-wave mixing (FWM) in a Y-type four-level atomic system based on the dressed states theory. We study the density matrix equation acted by two dressing fields simultaneously governing FWM signal intensity and the eigenvalues under the dressed state formalism. It is shown that the peak position and intensity of Autler–Townes splitting both originate from the dressing interaction as the detuning of the probe field is scanned. Moreover, it is observed that the interaction could be controlled by the dressing fields. Such flexibly controlled nonlinear signal has potential applications in optical communication and quantum information processing.

Perspectives on virtual intercultural communication in the Irish-based technology sector

Abstract This mixed-methods study investigates English-medium oral online intercultural communication within the Irish-based international technology sector. The initial phase of the research consisted of a survey investigating participants’ (N = 113) experiences of virtual communication. Following the survey, to linguistically investigate such interactions, the International Virtual Team Corpus (IVT Corpus) was created. This corpus consists of approximately 80,000 words of transcribed speech gathered from 30 web-based recordings of meetings, which include both Irish and international colleagues speaking in English. This paper reports on some of the relevant quantitative and qualitative survey results, uncovering both preconceptions and embodied experiences of international virtual meetings. Following this, it presents corpus-based results of significant frequent and keyword clusters that provide a window into the discourse patterns of international virtual team meetings in this sector. Some tentative implications and applications for work-based virtual communication are explored in the closing discussion.

The Application of Near Field Communication (NFC) in Public Transportation: Current Practices, Challenges, and Future Prospects

In the field of public transportation, the introduction of NFC technology can realize contactless payment and automatic ticket checking functions, significantly improving system efficiency and passenger experience. The article first reviews the development history of the public transportation system and the basic principles of NFC technology, and then analyzes the technical architecture and working principle of the NFC payment system. Through the cases of public transportation systems in many cities around the world, the practical application and effect of NFC technology are demonstrated. This article also verifies the transaction speed, stability and user satisfaction of NFC technology in the public transportation system through a series of experimental evaluations. The results show that NFC technology has excellent performance in terms of processing speed, system stability and user satisfaction, especially during peak hours, its advantages are more obvious. At the same time, the research also pointed out the limitations of current NFC technology applications and the challenges faced in practical applications. In the future, NFC technology will become more complete and is expected to provide passengers with a more personalized and intelligent service experience.

5.B. Round table: Improving digital health literacy in the era of generative artificial intelligence

Abstract Improved access to generative Artificial Intelligence (AI) platforms and technologies has prompted greater awareness of their potential application in health communication. This workshop will examine this potential alongside the practical challenges and risks of using generative AI in health communication in the broader context of the European Union AI Act. The workshop will explore the implications for the concept of digital health literacy in ways that reduce or mitigate existing digital health inequities across and within Europe. Chatbots and conversational AI platforms such as ChatGPT have opened opportunities for people to find, understand and use health information in significantly different ways. Public health professionals are already using these technologies to simplify health and medical information and to make it available in different languages. AI assisted technologies are also being used to create interactive and engaging learning experiences that provide the public with real-time feedback and insights about their health as well as prompting and reinforcing actions they can take to improve health. These developments have fundamental implications for our understanding of digital health literacy and the methods we use to support people in optimising the potential benefits of AI. Different communities in Europe vary considerably in their - access to digital technology, - skills to discriminate the accuracy and reliability of information, and - trust and responsiveness to what digital technologies have to offer. Building these fundamental digital health literacy skills is a critical priority if we are to ensure that all people benefit equitably from the potential offered by AI. Those of us engaged in improving health literacy have an important role to play in influencing the future direction of AI in health communication, including and especially by engaging in research and development activities that build evidence of effectiveness and support the development of digital health literacy skills in parallel with the expansion of access to AI-assisted digital technologies. The workshop chairs will provide introductory and summary remarks, moderate the panel discussion, and facilitate audience participation in the workshop. The individual panel members will make 3-minute introductions to key issues from different perspectives on the emerging practical applications of generative AI in health communication as well as the implications for strategies to improve digital health literacy in different population groups. The panel is made up of individuals in different roles and at different career stages who can offer complementary perspectives on these issues. Following the presentations, the co-chair will present some follow-up questions to the Panel before engaging directly with the workshop attendees for an open but structured discussion scheduled to last for 30 minutes of the Workshop. Key messages • We will examine how generative artificial intelligence has opened new both new opportunities and risks in the ways people find, understand and use health information. • We will consider how we can optimise the benefits of generative AI in a way that is equitable through the development of digital health literacy within and between communities in Europe. Speakers/panelists Catherine Jenkins London South Bank University, London, UK Diane Levin-Zamir Tel Aviv University, Tel Aviv, Israel Christopher Le Inland Norway University of Applied Sciences, Innlandet, Norway Miguel Telo de Arriaga Direção-Geral da Saúde, Lisbon, Portugal

Extending radiowave frequency detection range with dressed states of solid-state spin ensembles

Quantum sensors using solid-state spin defects excel in the detection of radiofrequency (RF) fields, serving various applications in communication, ranging, and sensing. For this purpose, pulsed dynamical decoupling (PDD) protocols are typically applied, which enhance sensitivity to RF signals. However, these methods are limited to frequencies of a few megahertz, which poses a challenge for sensing higher frequencies. We introduce an alternative approach based on a continuous dynamical decoupling (CDD) scheme involving dressed states of nitrogen vacancy (NV) ensemble spins driven within a microwave resonator. We compare the CDD methods to established PDD protocols and demonstrate the detection of RF signals up to ~85 MHz, about ten times the current limit imposed by the PDD approach under identical conditions. Implementing the CDD method in a heterodyne/synchronized protocol combines the high-frequency detection with high spectral resolution. This advancement extends to various domains requiring detection in the high frequency (HF) and very high frequency (VHF) ranges of the RF spectrum, including spin sensor-based magnetic resonance spectroscopy at high magnetic fields.

High-Performance Ultra-Broadband Photodetector Based on Fe3O4/CrSiTe3 Heterostructures.

Photodetectors based on advanced materials with a broad spectral photoresponse, high sensitivity, huge integration ability, room-temperature operation, and stable environmental stability are highly desired for diversified applications of imaging, sensing, and communication. Herein, a high-performance ultra-broadband photodetector based on an ultrathin two-dimensional (2D) Fe3O4 nanoflake heterostructure with high sensitivity was designed. The photodetector response light was from visible 405 nm to long-wave infrared (LWIR) 10.6 μm in ambient air. The competitive performances, including a high photoresponsivity (R) of 182.8 A W-1, fast speed with the rise time τr = 8.8 μs, and decay time τd = 4.1 μs, were demonstrated in the visible range. Notably, the device exhibits an excellent uncooled LWIR detection ability, with a high R of 1.4 A W-1 realized at a 1.5 V bias. In the full spectral range, the noise equivalent power is lower than 0.79 pW Hz-1/2, and specific detectivity (D*) is higher than 4.9 × 108 cm Hz1/2 W-1 in ambient air. This work provides alternative ultrathin 2D materials for future infrared optoelectronic devices.

Reverse-Engineered Exact Control of Population Transfer in Lossy Nonlinear Three-State Systems

We introduce a reverse-engineered scheme for achieving the precise control of population transfer in nonlinear quantum systems characterized by a 1:2 resonance. This scheme involves the use of two resonant laser pulses that transition from initial and final states to an intermediate level exhibiting irreversible losses. In comparison to alternative techniques, our approach offers computational efficiency advantages. Notably, the analytically defined form of the pump pulse enables tailored control strategies, enhancing robustness against decoherence and imperfections. This flexibility extends to choosing dump pulses and designing time evolution scenarios. These features open doors for practical implementation and scalability in quantum technologies, with potential applications in quantum information processing, quantum computing, and quantum communication.

Resonance scattering generated by rotating bodies

Abstract The scattering of rotating bodies to a polarized plane wave, including the dielectric cylinder and sphere, is studied. The resonance caused by rotation is emphasized. Numerical results prove that the resonance scattering caused by rotation can be realized in the optical range. It is sensitive to the rotation dimensionless parameter γ. The internal Mie mode corresponding to the electromagnetic field intensity changes with γ, and the resonant mode appears when the particle rotates at a specific speed. Moreover, the resonant mode changes with γ. It causes resonance scattering to appear in the same particle at different speeds. Inside particles, resonant rings are composed of a series of array points and are determined by γ. Under resonance conditions, the energy near the rotating cylinder is consistent with its rotation direction. In contrast, the direction of energy flow in the rotating sphere model is opposite to the direction of particle rotation. This work provides a novel idea for the design of ultra-sensitive sensors and resonators. It has promising applications in optical communication, optical microscopy, and optical signal processing.

Personalized movie recommendation in IoT-enhanced systems using graph convolutional network and multi-layer perceptron

Exploring the optimization of communication strategies for animation films in the context of cross-cultural communication, this research integrates the Internet of Things (IoT) and convolutional networks. The research constructs a collaborative filtering (CF) movie recommendation model based on a graph convolutional neural network (GCN) and investigates its application in cross-cultural communication. The fusion of IoT and convolutional networks in movie communication is also analyzed, and the effectiveness of the proposed GCN-CF model is validated through comparative experiments. The results indicate that, compared to other models, the GCN-CF model achieves the lowest Root Mean Square Error (RMSE) on the MovieLens 100 K and MovieLens 1 M datasets, with values of 0.8762 and 0.8275, respectively. Compared to traditional models, the GCN-CF model exhibits significantly superior performance in terms of RMSE, with reductions ranging from 0.6 to 5.2%, highlighting its heightened detection accuracy and overall performance. Moreover, the performance of the GCN-CF model is enhanced after introducing attention mechanisms and auxiliary information on both datasets, showing an improvement of 0.4% compared to the scenario without these additions. This data demonstrates the effectiveness of attention mechanisms and auxiliary information. Finally, the research presents an animation film communication strategy based on IoT and convolutional networks, offering novel insights for film production and communication, along with positive implications for cultural exchange and the advancement of the global media industry.

Multi-Buoy Deployment Method Based on an Improved Tuna Swarm Optimizer Enhanced with Fractional-Order Calculus Method for Marine Observation

Ocean buoys play a critical role in marine hydrological, water quality, and meteorological monitoring, with applications in navigation, environmental observation, and communication. However, accurately modeling and deploying a multi-buoy system in the complex marine environment presents significant challenges. To address these challenges, this study proposes an enhanced deployment strategy using the tuna swarm optimizer enhanced with the fractional-order calculus method for marine observation. The proposed method first introduces a detailed observation model that precisely captures the performance of buoys in terms of coverage and communication efficiency. By integrating the observation coverage ratio and communication energy consumption, we establish an optimal multi-buoy deployment model. The proposed method leverages tent chaotic mapping to improve the diversity of initial solution generation and incorporates fractional-order calculus to strengthen its search capabilities. Simulation experiments and statistical analysis verify the effectiveness of the proposed deployment model, with the proposed method achieving the best performance in deploying the multi-buoy system, reaching a final fitness value of 0.190052 at iteration 449, outperforming TSA, PSO, GWO, and WOA. These results highlight the potential of the proposed method in optimizing multi-buoy system deployment in marine observation.

New Constructions of One-Coincidence Sequence Sets over Integer Rings

In this paper, we introduce new constructions of one-coincidence frequency-hopping sequence (OC-FHS) sets over integer rings. These OC-FHSs are designed to minimize interference in frequency-hopping multiple access (FHMA) systems, which are widely used in various communication applications. By leveraging the properties of primitive elements in integer ring Zpn, we develop OC-FHS sets with lengths mpn−1 for m dividing (p−1), along with constructions with composite lengths based on linear functions. The proposed OC-FHS sets include parameters not previously addressed in the literature and encompass some known cases as special cases.

On optimal upper bound for the settling time of fixed-time stable systems and its application in secure communication

On optimal upper bound for the settling time of fixed-time stable systems and its application in secure communication

Application Research of Power Measurement Data Exchange Based on Uninterruptible Power Supply

With the maturity of the smart meter embedded system integration mode, the power consumption information can be fed back to the management center by the intelligent terminal through the power Internet of Things. The smart terminal adopts the narrowband data communication mode. However, the narrowband channel interval is hindered by interference signals, resulting in serious data packet loss. Therefore, a stable and efficient acquisition scheme is needed to ensure its smooth interaction. Based on the application of smart meter data communication, we analyze the power consumption optimization and carrier transmission optimization of the power Internet of Things and propose a data analysis method based on self-learning and external characteristics, which is used to calculate the offline execution strategy of smart meters when they encounter factors such as power outage or intrusion. A production task-driving rule is designed. The external characteristics of deep learning data of the power Internet of Things are collected. The accuracy of data classification is judged according to the parallel Internet of Things of a convolutional neural network and a long-term and short-term memory deep neural network. When dealing with high-dimensional original data, the data network is graded to reduce the work of feature selection and the difficulty of training. Moreover, we improve the autonomous execution ability of an embedded terminal device in an offline state. We also strengthen the ability of abnormal data detection and judgment learning to meet the requirements of efficient and stable operation of the power grid. Simulation results verify that compared with the current mainstream schemes, the performance of the proposed scheme is improved by more than 17%. Besides, the fault tolerance rate is enhanced by 29%, and the power consumption after optimization is reduced by 26.3% and 42.8%. These effects highlight the role of data processing in embedded systems. It solves the problem of abnormal data and energy loss affecting the accuracy of error estimation of electric energy meters, opens up a new way for data acquisition and processing of large-scale smart meters, and further improves the service level of information management of power systems.

Colossal room-temperature non-reciprocal Hall effect.

Non-reciprocal charge transport has gained significant attention due to its potential in exploring quantum symmetry and its promising applications. Traditionally, non-reciprocal transport has been observed in the longitudinal direction, with non-reciprocal resistance being a small fraction of the ohmic resistance. Here we report a transverse non-reciprocal transport phenomenon featuring a quadratic current-voltage characteristic and divergent non-reciprocity, termed the non-reciprocal Hall effect. This effect is observed in microscale Hall devices fabricated from platinum (Pt) deposited by a focused ion beam on silicon substrates. The transverse non-reciprocal Hall effect arises from the geometrically asymmetric scattering of textured Pt nanoparticles within the focused-ion-beam-deposited Pt structures. Notably, the non-reciprocal Hall effect generated in focused-ion-beam-deposited Pt electrodes can propagate to adjacent conductors such as Au and NbP through Hall current injection. Additionally, this pronounced non-reciprocal Hall effect facilitates broadband frequency mixing. These findings not only validate the non-reciprocal Hall effect concept but also open avenues for its application in terahertz communication, imaging and energy harvesting.

Generation of partially coherent full Poincaré beam arrays and their Stokes scintillations in turbulent media

A type of vector beam arrays, called partially coherent full Poincaré (PCFP) beam arrays, is introduced and experimentally synthesized using modal-vector-decomposition method. Our experimental system involves a digital micro-mirror device, which can generate such beam arrays with controllable spatial coherence and array structure in almost real-time, enabling to test the impact of atmospheric turbulence on them. Furthermore, we experimentally examine the scintillations of four Stokes parameters (denoted as S0, S1, S2, and S3) of PCFP beam arrays propagating through lab-simulated turbulence. The results indicate that the Stokes scintillations decrease as the number of beamlets increase or spatial coherence decreases. In contrast to S0 scintillation (intensity scintillation), S1, S2, or S3 scintillation is less affected by the turbulence under the same conditions. Our experimental results show that S2 and S3 scintillations could reduce by 67.2% and 52.4% compared to the intensity scintillation in strong turbulence. Our findings have potential applications in free-space optical communication when the Stokes parameter S2 or S3 is served as an information carrier.

Minimal lateral damage fabrication of high-temperature superconducting nanowires via focused helium ion beam irradiation

Abstract The low temperature superconducting nanowire single-photon detectors have become a key infrared photon counting technology in communication and astronomy applications. However, the constrained physical space of devices demands for high-performance superconducting detectors capable of operation at higher temperature. To date, the fabrication of high temperature superconductor nanowires is still facing seriously uneven lateral damage during ion etching process. In this work, we report a promising fabricating method for high-temperature superconducting YBa2Cu3O7−x (YBCO) nanowires, using a focused helium ion beam to minimize the lateral damage of the cut. Based on the simulation, we designed tangent circles and adjacent isosceles triangles to replace lines in cutting nanowires for reducing the superimposed damage of He+ ions. The lateral damage of single helium ion cut has been reduced with a superimposed damage width decrease from 58.8 nm to 29.7 nm. This work provides a platform for boosting the YBCO nanowires to achieve single photon detection.

A Review of the Physical, Optical and Photoluminescence Properties of Rare Earth Ions Doped Glasses

Doping glasses with rare-earth ions have garnered significant attention among researchers worldwide. This interest stems from the widespread utilization of rare-earth ions to enhance the optical characteristics of host glasses and exploit the unique spectroscopic properties arising from their optical transitions in the intra-4f shell. Thus, this study reviewed the exceptional potential of rare-earth ion-doped glasses (REIs) in various applications such as solid-state lasers, photonic devices, communication optical fibers, and white light emission. Various methods for the fabrication of glass such as direct melt quenching, sol-gel, ion exchange, sputtering and co-doping techniques were reviewed extensively. The Specific focus was on the physical, optical and photoluminescence properties of glasses produced from glass formers co-doped with rare earth ions. The investigation centers on the comprehensive current applicability of REI-doped glasses. The review concludes based on the physical, optical and photoluminescence properties of rare earth ion-doped glasses that they are extremely useful in photonics, lasers, biomedical and optical communication applications.