Frequency Band Research Articles

Brain Responses to Real and Imagined Interpretation of Tonal Versus Atonal Music

Professional musicians have been teaching/learning/interpreting Western classical tonal music for longer than atonal music. This may be reflected in their brain plasticity and playing efficiency. To test this idea, EEG connectivity networks (EEG-CNs) of expert cellists at rest and during real and imagined musical interpretation of tonal and atonal excerpts were analyzed. Graphs and connectomes were constructed as models of EEG-CNs, using functional connectivity measurements of EEG phase synchronization in different frequency bands. Tonal and atonal interpretation resulted in a global desynchronization/dysconnectivity versus resting—irrespective of frequency bands—particularly during imagined-interpretation. During the latter, the normalized local information-transfer efficiency (NLE) of graph-EEG-CN’s small-world structure at rest increased significantly during both tonal and atonal interpretation, and more significantly during atonal-interpretation. Regional results from the graphs/connectomes supported previous findings, but only certain EEG frequency bands. During imagined-interpretation, the number of disconnected regions and subnetworks, as well as regions with higher NLE, were greater in atonal-interpretation than in tonal-interpretation for delta/theta/gamma-EEG-CNs. The opposite was true during real-interpretation, specifically limited to alpha-EEG-CN. Our EEG-CN experimental paradigm revealed perceptual differences in musicians’ brains during tonal and atonal interpretations, particularly during imagined-interpretation, potentially due to differences in cognitive roots and brain plasticity for tonal and atonal music, which may affect the musicians’ interpretation.

Compact dual-band antenna design for sub-6 GHz 5G application

A design of a compact dual-band antenna for 5G application is presented in this research article. The dual-band operation includes the 3.6 GHz and 5.4 GHz frequency bands of the sub-6 GHz frequency band for 5G technology. The proposed antenna offers a compact design with satisfactory antenna performance parameters. Moreover, the dual-band antenna showcases the independent tuning ability for both frequency bands. The prototype of the dual-band antenna is manufactured and when tested for various antenna performance parameters shows a good agreement between the simulated and measured results. The proposed dual-band antenna has compact dimensions along with a peak gain of 2.2 dB and antenna efficiency of more than 90%.The antenna performance parameters are also compared with various dual-band antenna designs from the literature. The proposed dual-band antenna offers a compact design with satisfactory performance parameters and outperforms its counterparts.

Dynamic base station allocation for 6G wireless networks through narrow neural network

The 6G wireless communication system will utilize the terahertz (THz) frequency band (0.1-10 THz) to meet customer demand for increased data rates and ultra-high-speed communication in future applications. The exponential surge in data traffic, which is supported by dynamic resource allocation. To mitigate this challenge, the use of artificial intelligence-based methods, such as narrow neural network (NNN), can help to smooth the performance of the network. In this paper, an NNN-based approach for dynamic base station allocation for 6G wireless networks is proposed 14 different 6G parameters used to train the NNN model, initially achieving an accuracy of 89.5% and an F1 score of 0.72 for 200 users. Results demonstrate the efficacy of the proposed NNN approach for dynamic decision-making in 6G networks and its potential for application in other domains where similar problems exist. Moreover, the proposed narrow neural network model shows improved results with an increase in number of users and decrease in fully connected layers and regularization strength (lambda). The validation accuracy received is 98.9% and 99.6% for thousand users with single fully connected layer, none (linear) activation function and regularization strength lambda values of 0.01 and 0.001.

Error-based Implicit Learning in Language: The Effect of Sentence Context and Constraint in a Repetition Paradigm.

Prediction errors drive implicit learning in language, but the specific mechanisms underlying these effects remain debated. This issue was addressed in an EEG study manipulating the context of a repeated unpredictable word (repetition of the complete sentence or repetition of the word in a new sentence context) and sentence constraint. For the manipulation of sentence constraint, unexpected words were presented either in high-constraint (eliciting a precise prediction) or low-constraint sentences (not eliciting any specific prediction). Repetition-induced reduction of N400 amplitudes and of power in the alpha/beta frequency band was larger for words repeated with their sentence context as compared with words repeated in a new low-constraint context, suggesting that implicit learning happens not only at the level of individual items but additionally improves sentence-based predictions. These processing benefits for repeated sentences did not differ between constraint conditions, suggesting that sentence-based prediction update might be proportional to the amount of unpredicted semantic information, rather than to the precision of the prediction that was violated. In addition, the consequences of high-constraint prediction violations, as reflected in a frontal positivity and increased theta band power, were reduced with repetition. Overall, our findings suggest a powerful and specific adaptation mechanism that allows the language system to quickly adapt its predictions when unexpected semantic information is processed, irrespective of sentence constraint, and to reduce potential costs of strong predictions that were violated.

Design of higher gain linearly polarized 2×2 microstrip patch array antenna for wireless communication

The fifth-generation technology is popular and best as far as data rates are concerned for wireless applications. To meet the increased demand of the modern world for faithful communication, this research work is carried out. In this approach, a single patch, 1×2 array, and 2×2 array are designed using a low-cost FR4 dielectric substrate ( =4.4) covering the 3.3–3.8 GHz frequency band. Due to the lack of gain from arrays in the present research, an attempt is made to achieve excellent gain from arrays with a minimum number of patches. First, the gain of a single inset-fed antenna is compared with another normal single patch of the same thickness but with an additional air dielectric medium. Next, the second single patch is extended to obtain a rectangular 1×2 array and a 2×2 array antenna. A second single patch measuring 50×32.5×0.8 mm is designed assuming an infinite ground plane. It has 3mm air gap between the patch strip and the ground. Air acts as a second dielectric layer that reduces power loss. This allows a maximum gain of 15.2 dB with a return loss of -22 dB. Also, antenna efficiency and bandwidth are 91% and 267.69 MHz, respectively.

Multimodal planar monopole filtenna for 5G applications

This paper presents a novel planar filtering antenna (filtenna) with simple layout based on tightly-coupled different-length monopoles. Its design methodology is based on an even-mode/odd-mode decomposition of the monopole currents, and the combination of both modes in a multimodal circuit model that facilitates the design and tuning of the antenna and the accompanying feeding network, since most of the process is performed using fast circuit simulations. The circuit model casts light into the interaction between conducting and radiating modes in the bulk of the antenna, and on how this interaction can be used to propose feedback loops that increase and define the radiation band. Using these modal tools, a filtenna was designed and fabricated to fully cover the new 5G frequency bands (n77, n78 and n79) from 3 to 5 GHz that are currently being adopted by many countries for high-capacity data transmission. It features a 62.9% FWB, dipole-like radiation patterns, good out-of-band rejection up to 10 GHz, and a very good trade-off between design/structural-simplicity and bandwidth.

Experimental analysis for comparison of wireless transmission technologies: Wi-Fi, Bluetooth, ZigBee and LoRa for mobile multi-robot in hostile sites

This research paper conducts a thorough comparison of four prominent transmission technologies suitable for mobile robots operating in challenging environments. Emphasizing key factors such as signal strength, noise resistance, and data transfer efficiency, the study aims to identify the optimal communication solution in hostile conditions. The exploration delves into the intricacies of received signal strength indication (RSSI) and signal-to-noise ratio (SNR), revealing distinctive traits and trade-offs among the technologies. Navigating through the complexities of frequency bands, modulation types, and communication topologies, the paper examines the impact of obstacles, energy consumption dynamics, and potential real-world applications. Beyond contributing to the fields of robotics and communication, the study offers practical insights for stakeholders seeking resilient and efficient transmission methods for mobile robotic applications. Advocating for long range (LoRa) as the preferred transmission technology in hostile environments, the paper highlights its unmatched immunity to noise, stability, and minimal energy consumption. These findings provide valuable guidance for technology choices in collaborative mobile robot operations under challenging conditions. This research sets the stage for future developments in robotic communication, underscoring the crucial role of selecting the right transmission means for mission-critical applications in hostile environments.

Study of the characteristics of broadband matching antennas for fifth-generation mobile communications based on new composite materials

The presented research aims to analyze in detail the characteristics of broadband matching antennas specifically designed for 5G mobile communications applications, with an emphasis on innovative composite materials. The study focuses on a compact planar loop antenna designed for use on smartphones, covering the LTE/WWAN frequency bands 824 to 960 MHz, 1,710 to 2,690 MHz, and 3,300 to 3,600 MHz for full coverage of modern 5G networks. Experimental and numerical methods are used to broadly analyze the frequency range associated with 5G networks. The features of the use of composite materials in the implementation of antenna devices in 5G technologies are noted. A broadband matching circuit (BMC) with elements with lumped parameters and a reduced sensitivity invariant has been synthesized. A 3D model of the adaptive selective surface controller (SSC) was developed using CST Studio. The study results highlight the benefits of new composite materials in improving the performance of 5G antennas. This research makes a significant contribution to the development of 5G technologies by optimizing antenna design for efficient data transmission in modern mobile networks and can be a valuable resource for engineers and designers working in this field.

Spectral analysis of seismic data based on a combined generalized S transform

The S transform is widely used to delineate seismic spectral anomalies associated with hydrocarbons during reservoir characterization. To overcome the relatively poor time-frequency resolution due to the fixed varying pattern of the window used in the S transform, we present a combined generalized S transform (CGST) for the spectral analysis of seismic data. First, the CGST decomposes the signal into a series of intrinsic mode functions (IMFs) using a complete ensemble empirical mode decomposition (CEEMD). An objective function is defined to quantitatively determine the spectral energy concentration criteria for optimal parameter selection of the improved Gaussian windows. Then, the time-frequency spectra for all the IMFs within narrower frequency bands are calculated using the respective Gaussian windows with normalized energy and individual optimal controlling parameters. We applied the CGST to spectral analyses of both synthetic signals and seismic field data. The results indicate that the CGST exhibits good performance with a higher time-frequency resolution. Field examples illustrate that the CGST can be used to characterize the spectral behavior of thin beds and indicate low-frequency shadows associated with hydrocarbon reservoirs.

Design of a novel compact low specific absorption rate multiple input multiple output antenna for 5G sub-6 GHz terminals

This investigation presents a new design and analysis of a fourteen elements massive multiple input multiple output (MIMO) compact low specific absorption rate (SAR) antenna system for 5G and beyond terminals. The MIMO antennas are realized for sub-6 GHz LTE-band 46 (5.1-5.8 GHz) long-term evolution 5G wireless communication services. The proposed antenna system is designed on an FR-4 dielectric constant 4.3 substrate consisting of the main board and four sideboards. The radiating elements are developed on the sideboards consisting of a monopole antenna and two metamaterial unit cells, as well as the feed line is designed on the principal board. The overall volume of the proposed structure is 150×80×7.5 mm. Through the use of the metamaterial unit cells, the proposed antennas have been arranged in close proximity without developing a strong mutual coupling. The results obtained were very important in terms of impedance matching, isolation among the antennas, and good gain. Even, the SAR analysis at the operating frequency band of 5.5 GHz proves that the proposed MIMO antenna system satisfies safety standards set for human exposure at the international level. Therefore, the proposed massive MIMO antenna structure is a potential solution for future communication applications.

A novel slotted antenna design for future Terahertz applications

A slotted patch antenna operating at 118 GHz is proposed to address challenges in the terahertz (THz) frequency band for wireless communication systems. The antenna design, utilizing a Rogers RO3003 substrate, which has a dielectric constant of 3 and tan 0.001, strategically incorporates slots to enhance key performance parameters. Copper is employed for the ground and radiating patch, and a microstrip feeding method powers the antenna. High frequency structure simulator (HFSS) software is used for design and simulation, revealing resonance at 0.118 THz with a reflection coefficient of -42.41 dB and an impedance bandwidth of 4.42 GHz (115.84–120.26 GHz). At the operating frequency, the antenna exhibits a gain of 7.36 dB, maximum directivity of 7.38 dB, the voltage standing wave ratio (VSWR) of 1.01, and 99.75% radiation efficiency, all within a compact size of 1.5×1.3×0.1 mm³. The suggested antenna outperforms recent counterparts, making it suitable for applications like security screening and wireless communication systems (5G). Future efforts will target bandwidth expansion, gain enhancement, and further size reduction to enhance overall performance.

Design of Compact Size Tri-Band Stacked Patch Antenna for GPS and IRNSS

Abstract: This paper introduces a low-profile, compact tri-band microstrip patch antenna designed for GPS and IRNSS applications. The proposed antenna operates at frequencies of 1.57 GHz, 1.22 GHz, and 1.77 GHz. The antenna configuration consists of a patch antenna with a slip slot or manderline to generate three frequency bands while maintaining an acceptable radiation pattern. The focus of the study is to enhance the antenna's gain across all three frequency bands. This design aims to offer a versatile solution for navigation systems, leveraging the tri-band capability to accommodate different satellite signals and improve overall performance in GPS and IRNSS applications.

Exploring the Impact of Split Ring Resonator Metamaterial Structure Integration on 4X4 MIMO Antenna Performance in Sub-6GHz Bands for 5G Applications

This research delves into the realm of antenna engineering, with a specific focus on examining the performance of 4x4 MIMO antennas with and without integration of split ring resonator metamaterial structure. The objective is to comprehend the influence of split ring resonator metamaterials on antenna characteristics within the 6 GHz frequency range. Employing CST Studio Suite software, comprehensive simulations are conducted to evaluate various parameters including gain, directivity, radiation efficiency, S-parameters, power distribution, VSWR, and total efficiency. In the frequency band up to 6GHz, observed gain values were 24.62dB without split ring resonator metamaterial integration and ranging from 6dB to 27dB with integration. Through a systematic comparison, the study aims to delineate the precise effects of split ring resonator metamaterials on antenna performance, thereby offering valuable insights into their potential for enhancing MIMO antenna systems.

A Case Study on Image Co-Registration of Hyper Spectral and Dual (L & S) Band SAR Data and Ore Findings Over Zewar Mines, India

The technique of superimposing two or more photographs in a way that ensures that for each image, the same pixel corresponds to the same location of the target scene is known as image coregistration It is a crucial stage in the picture enhancement process for satellite images. Different frequency bands store feature. Image fusion makes it possible to superimpose co-registered pictures taken by several sensors to get a superior image incorporating elements from both sources. On many match patches that are evenly dispersed over the two scenes, we estimate pixel offsets between possibly coherent picture pairings as image coregistration allows a more detailed single image to be obtained than many photos with distinct attributes. This study presents existing various fusion methods for ASAR (Airborne Synthetic Aperture Radar) images in the S-band and L-band to interpret urban, forestry, and agricultural areas. AVIRIS hyper spectral data also shows mining possibilities on ore of region. Hence, the seeking of ore region, and coregistration using fusion facilitates the remote sensing architecture next to drones.

A data recovery method for extra-long-span railway bridge health monitoring based on TVFEMD and CNN-GRU

Structure health monitoring systems play a crucial role in understanding the condition of structures. However, owing to various uncertain factors, sensor data may be missing, which poses a great challenge to capture the real-time dynamic characteristics of the bridge. To address this problem, this paper proposes a model that integrates time varying filtering based empirical mode decomposition (TVFEMD), convolutional neural network (CNN), and gated recurrent unit (GRU) to forecast and fill in the missing data. The proposed model initially employs TVFEMD to decompose the signal into several intrinsic mode functions (IMFs) of different frequency bands. Subsequently, CNN is utilized to extract data features for each IMF, followed by prediction through GRU. The model linearly combines the prediction results obtained from each IMF to obtain the actual prediction result. Simulation data and measured data from the large railway bridge are utilized in this research to validate the model’s efficacy. The analysis results demonstrate a significant improvement in prediction performance compared to traditional models, showcasing strong generalization ability and robustness. In conclusion, the model proposed in this paper has a high utilization value in health monitoring data recovery.

Relationships between Electroencephalogram and Thermal Perception of Passenger in Winter Vehicle Compartments

The development of electric vehicles (EVs) has prompted a critical examination of the trade-off between range and human thermal comfort. Therefore, an accurate, real-time assessment of human thermal perception inside vehicles is important. This study investigates an electroencephalogram- (EEG-) based method for evaluating human thermal comfort in the vehicle passenger compartment. Under transient winter heating conditions, the study experimentally investigates the correlation between objective physiological parameters (skin temperature and electroencephalogram) and subjective human thermal perception. The results reveal distinct patterns in EEG signals corresponding to changes in thermal perception. Specifically, the δ rhythm exhibits a U-shape variation with increasing thermal perception, while the θ, α, β, and γ rhythms display an inverted U-shape variation. Differences in each frequency band across thermal comfort states in humans are greater than differences in the frequency band across thermal sensation states. Furthermore, the relative power of the θ rhythm emerges as the most effective in discerning the thermal perception state of the human body. The EEG signal characteristics of the T7 and T8 channels align more closely with human thermal sensation, whereas the AF4 channel excels at discriminating the state of human thermal comfort. The insights gained from this study serve as a foundation for evaluating human thermal perception in vehicles, enhancing human-vehicle interaction, and addressing challenges related to human thermal comfort and vehicle range.

Interspectral Error Tracking and Compensation of DSDT in Satellite Internet of Things

With the rapid growth of satellite Internet of Things (SIoT) services, existing frequency band resources are insufficient to meet future business demands. To effectively address this issue, it is necessary to enhance the utilization of existing frequency resources. However, idle frequency resources are typically scattered across multiple bands and vary in bandwidth size. Direct Spectrum Division Transmission (DSDT), dividing a complete signal into sub-spectrum signals for transmission in idle frequency bands, can take the use of fragmented spectrum resources for satellite communication. Nevertheless, the performance of DSDT depends heavily on accurate synchronization toward multiple sub-spectrums. In this paper, an algorithm for error synchronization tracking and compensation is proposed by utilizing the focusing nature of constellation. All sub-spectrums are weighed by the minimum Euclidean distance of the constellation to compensate for amplitude–frequency–phase errors simultaneously. Simulations and experimental verification demonstrate synchronization performance and feasibility of proposed method in a multi-radio frequency channels environment.

Simulated dynamical transitions in a heterogeneous marmoset pFC cluster

Network analysis of the marmoset cortical connectivity data indicates a significant 3D cluster in and around the pre-frontal cortex. A multi-node, heterogeneous neural mass model of this six-node cluster was constructed. Its parameters were informed by available experimental and simulation data so that each neural mass oscillated in a characteristic frequency band. Nodes were connected with directed, weighted links derived from the marmoset structural connectivity data. Heterogeneity arose from the different link weights and model parameters for each node. Stimulation of the cluster with an incident pulse train modulated in the standard frequency bands induced a variety of dynamical state transitions that lasted in the range of 5–10 s, suggestive of timescales relevant to short-term memory. A short gamma burst rapidly reset the beta-induced transition. The theta-induced transition state showed a spontaneous, delayed reset to the resting state. An additional, continuous gamma wave stimulus induced a new beating oscillatory state. Longer or repeated gamma bursts were phase-aligned with the beta oscillation, delivering increasing energy input and causing shorter transition times. The relevance of these results to working memory is yet to be established, but they suggest interesting opportunities.

SEISMONOISY: A Quasi-Real-Time Seismic Noise Network Monitoring System

This paper introduces SEISMONOISY, an application designed for monitoring the spatiotemporal characteristic and variability of the seismic noise of an entire seismic network with a quasi-real-time monitoring approach. Actually, we have applied the developed system to monitor 12 seismic networks distributed throughout the Italian territory. These networks include the Rete Sismica Nazionale (RSN) as well as other regional networks with smaller coverage areas. Our noise monitoring system uses the methods of Spectral Power Density (PSD) and Probability Density Function (PDF) applied to 12 h long seismic traces in a 24 h cycle for each station, enabling the extrapolation of noise characteristics at seismic stations after a Seismic Noise Level Index (SNLI), which takes into account the global seismic noise model, is derived. The SNLI value can be used for different applications, including network performance evaluation, the identification of operational problems, site selection for new installations, and for scientific research applications (e.g., volcano monitoring, identification of active seismic sequences, etc.). Additionally, it aids in studying the main noise sources across different frequency bands and changes in the characteristics of background seismic noise over time.

Absorption‐Dominant Electromagnetic Interference (EMI) Shielding across Multiple mmWave Bands Using Conductive Patterned Magnetic Composite and Double‐Walled Carbon Nanotube Film

AbstractThe revolution of millimeter‐wave (mmWave) technologies is prompting a need for absorption‐dominant EMI shielding materials. While conventional shielding materials struggle in the mmWave spectrum due to their reflective nature, this study introduces a novel EMI shielding film with ultralow reflection (<0.05 dB or 1.5%), ultrahigh absorption (>70 dB or 98.5%), and superior shielding (>70 dB or 99.99999%) across triple mmWave frequency bands with a thickness of 400 µm. By integrating a magnetic composite layer (MCL), a conductive patterned grid (CPG), and a double‐walled carbon nanotube film (DWCNTF), specific resonant frequencies of electromagnetic waves are transmitted into the film with minimized reflection, and trapped and dissipated between the CPG and the DWCNTF. The design factors for resonant frequencies, such as the CPG geometry and the MCL refractive index, are systematically investigated based on electromagnetic wave propagation theories. This innovative approach presents a promising solution for effective mmWave EMI shielding materials, with implications for mobile communication, radar systems, and wireless gigabit communication.