Channel Switching Research Articles

Frequency-selectable microwave generation based on on-chip switchable spectral shaping and wavelength-to-time mapping.

We propose and experimentally demonstrate a scheme for the photonic generation of pulsed microwave signals with selectable frequency based on spectral shaping and wavelength-to-time mapping (WTTM) technique. The frequency selectivity is realized by channel switching on an integrated silicon-on-insulator (SOI) spectral shaping chip. The incident signal is spectrally shaped by the asymmetric Mach-Zehnder interferometer (MZI) in the selected channel, and an optical spectrum with uniform free spectral range (FSR) can be generated in a broad bandwidth up to dozens of nanometers, implying large microwave signal duration after WTTM if a pulse light source with matched bandwidth is available. Microwave pulses of frequency from 3.6 GHz to 28.4 GHz with a fixed interval are experimentally generated respectively. The realization of eight microwave frequencies selectable with only one shared dispersive element (DE) required indicates high expansibility in the frequency cover range of our scheme by tuning the dispersion value in WTTM.

Arbitrary Ca2+ regulation for endothelial nitric oxide, NFAT and NF-κB activities by an optogenetic approach.

Modern western dietary habits and low physical activity cause metabolic abnormalities and abnormally elevated levels of metabolites such as low-density lipoprotein, which can lead to immune cell activation, and inflammatory reactions, and atherosclerosis. Appropriate stimulation of vascular endothelial cells can confer protective responses against inflammatory reactions and atherosclerotic conditions. This study aims to determine whether a designed optogenetic approach is capable of affecting functional changes in vascular endothelial cells and to evaluate its potential for therapeutic regulation of vascular inflammatory responses in vitro. We employed a genetically engineered, blue light-activated Ca2+ channel switch molecule that utilizes an endogenous store-operated calcium entry system and induces intracellular Ca2+ influx through blue light irradiation and observed an increase in intracellular Ca2+ in vascular endothelial cells. Ca2+-dependent activation of the nuclear factor of activated T cells and nitric oxide production were also detected. Microarray analysis of Ca2+-induced changes in vascular endothelial cells explored several genes involved in cellular contractility and inflammatory responses. Indeed, there was an increase in the gene expression of molecules related to anti-inflammatory and vasorelaxant effects. Thus, a combination of human blue light-activated Ca2+ channel switch 2 (hBACCS2) and blue light possibly attenuates TNFα-induced inflammatory NF-κB activity. We propose that extrinsic cellular Ca2+ regulation could be a novel approach against vascular inflammation.

Driving mechanism of consumer migration behavior under the COVID-19 pandemic.

China is now in the post-period of COVID-19 epidemic prevention and control. While facing normalized epidemic prevention and control, consumers behavioral intention and decision-making will still be influenced by the epidemic's development and the implementation of specific epidemic prevention measures in the medium to long term. With the impact of external epidemic prevention environment and measures, consumers' channel behavior has changed. How to better promote channel integration by adopting consumers' channel migration behavior is important for channel coordination strategies. This paper takes fresh product retailing under normal epidemic prevention and control as an example and examines the change in channel migration behavior. Based on the value-based adoption model (VAM), this paper discusses the influence of channel characteristics and channel switching costs on channel migration intention, the mediating effect of perceived value between various influencing factors and channel migration intention, and the moderating effect of channel switching cost on perceived value and channel migration intention. Thus, an empirical study was carried out with 292 samples to verify the hypotheses. The results show that under normal epidemic prevention and control, the influencing factors in the VAM model have a significant impact on channel migration intention; perceived value plays a mediating role between various influencing factors and channel migration intention. The COVID-19 pandemic has had a significant effect on daily life and purchasing behavior. In the context of this pandemic, we have confirmed that consumers will probably change to other retailers when the usefulness, entertainment, and cost meet their expectation for purchasing fresh products. Channel characteristics have versatile features, such as channel structure and supply chain mode, which affect consumer behaviors in different ways. The perceived value comes from expectations and experience. Retailers should try to keep their products fresh and provide consumers with a high-level shopping experience during sale.

Dual-channel structured illumination super-resolution quantitative fluorescence resonance energy transfer imaging

The Structured illumination (SI)-based super resolution fluorescence resonance energy transfer (SR-FRET) imaging technique, known as SISR-FRET, enables the investigation of molecular structures and functions in cellular organelles by resolving sub-diffraction FRET signals within living cells. The FRET microscopy offers unique advantages for quantitatively detecting dynamic interactions and spatial distribution of biomolecules within living cells. The spatial resolution of conventional FRET microscopy is limited by the diffraction limit, and it can only capture the average behavior of these events within the resolution limits of conventional fluorescence microscopy. The SISR-FRET performs sequential linear reconstruction of the three-channel SIM images followed by FRET quantitative analysis by using a common localization mask-based filtering approach. This two-step process ensures the fidelity of the reconstructed SR-FRET signals while effectively removing false-positive FRET signals caused by SIM artifacts. However, the slow imaging speed resulting from the switching of excitation-emission channels in SISR-FRET imaging limits its application in fast imaging scenarios. To address this issue, this study proposes a dual-channel structured illumination super-resolution quantitative FRET imaging system and method. By incorporating an FRET dual-channel imaging and registration module into the imaging pathway, the spatial switching and channel multiplexing of the SISR-FRET excitation-emission channels are achieved. Combining the image reconstruction algorithm with channel sub-pixel registration correction, the dual-channel SISR-FRET technique enhances the temporal resolution by 3.5 times while preserving the quantitative super-resolution FRET analysis. Experimental results are obtained by using a multi-color SIM system to perform super-resolution imaging of living cells expressing mitochondria outer membrane FRET standard plasmids. These experiments validate the improved spatial and temporal resolution of dual-channel SISR-FRET and the fidelity of FRET quantification analysis. In summary, this research presents a novel dual-channel structured illumination super-resolution FRET imaging system and method. It overcomes the limitations of slow imaging speed in SISR-FRET by realizing the spatial switching and channel multiplexing of excitation-emission channels. The proposed technique enhances the temporal resolution while maintaining quantitative analysis of super-resolution FRET. Experimental validation demonstrates the increased spatial and temporal resolution of dual-channel SISR-FRET and the accuracy of FRET quantification analysis. This advancement contributes to the study of molecular structures and functions in cellular organelles, providing valuable insights into the intricate mechanisms of living cells.

OPTIMIZATION OF INFORMATION COMMUNICATION NETWORK MANAGEMENT PROCESS PARAMETERS

The classical theory of control systems focused mainly on control objects, which are characterized by a certain determinism, stationarity, relative simplicity, fixity of coordinates, sufficiently studied characteristics, and the possibility of building regular mathematical models. These characteristics were fully met by telecommunication networks with channel switching, including mathematical network models for calculating resources by means of mass service theory. Over time, new problems arise that require new solutions and, accordingly, new approaches to managing information communications, which is considered in this study. The research analyzed trends in the construction of fifth generation 5G networks. The relevance of the study of new approaches to the management of information communications is shown. The main stages of the evolution of telecommunications as an object of management are indicated. Problems corresponding to this evolution and approaches to their solution are outlined. Forecasts of the development and complications of telecommunications in the 2020s and 2030s are offered. Self-organization and multi-agent systems are considered within the framework of the analysis of telecommunications management as a scientific discipline. The concept of the correctness of the management strategy at certain moments of time and always, that is, at all moments of time of the considered period, is formalized. A new probabilistic-parametric concept of three-level management of 5G information and communication networks is substantiated. Approaches to mathematical modeling of telecommunications management within the framework of this concept are proposed. The relevance of the development of new methods for calculating probabilistic-temporal characteristics of management of fifth generation communication networks in real time has been proven. Ways to develop research on software-configured networks and virtualization of the functionality of post-NGN networks are proposed.

ISAR Imaging of Precession Target Based on Joint Constraints of Low Rank and Sparsity of Tensor

Precession is a typical form of micro-motion that can bring about complex and time-varying Doppler modulation. The range instantaneous Doppler (RID) method, which uses time-frequency analysis instead of the Fourier transform to describe the time-varying Doppler, is typically used to obtain the high-resolution inverse synthetic aperture radar (ISAR) image of a precession target. However, the observation time of a specific target is often non-uniform due to various interference and channel switching among multi-channel radars, which will lead to a sparse aperture. Sparse aperture can cause sidelobe interference in the ISAR image obtained by the RID method, making it difficult to focus well. To solve the problem whereby the RID method fails to image a precession target with sparse aperture, this paper proposes a new method based on the joint constraints of low-rank and sparsity of tensor, and uses the alternating direction method of multipliers to solve the problem. The low-rank can constrain the correlation among consecutive ISAR images, and sparsity can remove the impact of sparse aperture. This effectively eliminates the micro-Doppler interference and sidelobe interference in ISAR image, and enables the reconstruction of precession target in a sequence of ISAR images with sparse aperture. Experimental results under both simulations and darkroom measurements verify that the proposed method performs well on ISAR images of conic precession target with sparse aperture.

Economic Analysis and Evaluation of the Effectiveness of Network Retail and Sales of Goods

The study is devoted to the peculiarities of the activities of network retailers (retail trade networks). It was determined what retailers in general and network retailers in particular are. The focus is on identifying how companies such as retailers and consumer goods manufacturers operate during and after the pandemic crisis and how they stimulate demand for their products with an additional focus on the Ukrainian market. The analysis carried out is based on general business and analytical secondary data available in the public domain. The methodology of the article is compatible with the general academic approach to research, such as analysis and synthesis, abstraction, induction. Prior to the main analysis, key challenges during the volatile industry were identified. Various sources of business literature are analyzed to outline strategies that companies can use to encourage customers to maintain their usual level of demand. Attention was drawn to a specific business case of a British retailer. In order to compare the strategies proposed by international players with local ones, the retail market in Ukraine was analyzed. Key information points were strategy switching, physical growth and development of digital channels. The authors found differences in the general approach to stimulating demand and the approach used by local players. Unlike its Western competitors, the Ukrainian market grew significantly during the pandemic crisis, but in a new format. Analysis of digital channels focused on consumer preferences. The results show that the Ukrainian market still prefers physical stores over digital channels in the food category, while in the cosmetics category the leadership of physical stores is being lost. In order for companies to better adapt to market conditions and limit the negative financial impact during the recovery phase, management must clearly understand the path to recovery of key categories.

Switching Strategy for Connected Vehicles Under Variant Harsh Weather Conditions

With the development of 5G networks and advanced communication technologies, connected vehicles (CV) are becoming an increasingly important aspect of the future of transportation. The connected vehicles will usually generate a large amount of data that require fast and reliable communication channels with low latency. 5G millimeter-wave (mmWave) is crucial for the next generation of vehicle-to-vehicle (V2V) communications in CV scenarios. However, harsh weather conditions such as rain, snow, dust, and sand can significantly impact the performance of 5G mmWave channels for V2V communications. Maintaining seamless connections for connected vehicles during harsh weather conditions is a significant challenge that researchers must address. In this paper, we propose a two-stage strategy enabling connected vehicles to operate effectively under moderate and severe weather conditions. Our proposed approach involves a prediction step, which uses machine learning techniques to forecast weather patterns and determine the optimal communication strategy, followed by a switching step, which seamlessly chooses between frequency or channel switch based on the prediction. By incorporating these two steps, we aim to provide a robust and efficient communication system that can adapt to different weather conditions. The NS3 simulation results show that our switching strategy is effective and can benefit the field of connected vehicle technology.

ЗАБЕЗПЕЧЕННЯ УПРАВЛІННЯ РОЗГОРТАННЯМ МОБІЛЬНОЇ КОМПОНЕНТИ СИСТЕМИ ЗВ’ЯЗКУ З’ЄДНАНЬ ТА ЧАСТИН НАЦІОНАЛЬНОЇ ГВАРДІЇ УКРАЇНИ ЦИФРОВИМИ РАДІОЗАСОБАМИ

The capabilities of modern Harris RF-7800S-TR digital radios for managing communication units are considered. A comparative analysis of the capabilities of the Motorola DP4800 and Harris RF-7800S-TR radio stations was carried out in providing control over the deployment of the mobile communication center of the auxiliary control point of the territorial control of the National Guard of Ukraine. Proposed recommendations for the implementation of the topology of the Harris RF-7800S-TR radio station programming file for the management of the process of deploying a field communication node on one operating frequency with the separation of all radio networks and ensuring their simultaneous operation independently of each other and with access only to the appropriate management levels. The research results make it possible to develop an innovative frequency plan for the deployment control system of the auxiliary control point field communication node. At the same time, all radio stations operate on the same frequency, using different positions of the radio station channel switch. Separation of radio networks is temporary, and access to radio networks is carried out using various tangents, the functions of which are programmed in advance. Thus, the modern Harris RF-7800S-TR digital radio station, which is in service with NSU units, allows for reliable management of the deployment of a field communication node with the fulfillment of all requirements for security, communication security, and with minimal expenditure of material resources, and the conducted class on the implementation of the topology of the radio station programming file will provide the most effective training of communication specialists for positions in the military.

State estimation of reaction-diffusion inertial neural networks with Markovian switching channels via conjunct measurement

This paper addresses the state estimation of reaction-diffusion inertial neural networks (RDINNs) with Markovian switching channels based on conjunct measurement method. First, a suitable variable substitution is employed to transform the original second-order differential system into a first-order one, and a time-space sampled-data measurement strategy is adopted to replace the traditional continuous measurement method. As single-channel transmission may suffer from various communication deficiencies, a multi-channel switching scheme is considered in this paper to improve transmission efficiency. Then, by constructing Lyapunov-Krasovskii functional with relaxed conditions, sufficient conditions are derived to ensure that the error system is asymptotically stable. Finally, the feasibility of the proposed method is further validated by simulation results.

Barform deposits of the Carolyn Shoemaker formation, Gale crater, Mars

ABSTRACT The early environmental history of Mars is encoded in the planet's record of sedimentary rocks. Since 2012, the Curiosity rover has been ascending Mount Sharp, Gale crater's central mound, making detailed observations of sedimentary strata exposed there. The primary depositional setting represented by the rocks examined thus far has been a perennial lake, represented by the mudstones and sandstone lenses of the Murray formation. Here, we report on the sedimentology of outcrops examined in the Carolyn Shoemaker formation, which sits stratigraphically above the Murray formation. We interpret strata exposed in the Glasgow and Mercou members of the Carolyn Shoemaker formation to represent river bars in ancient alluvial and shoreline settings based on sedimentary structures, stratal geometries measured from photogrammetric data, and erosional morphology. The transition from a lacustrine to a fluvial depositional setting records the aggradation and progradation of coastal rivers into what was previously the extent of the Gale lake system. This may have occurred due to the shrinking of the lake over time due to climate-driven changes in the basin water balance, or local three-dimensionality in shoreline evolution, such as the formation of a new sedimentary lobe following a channel switch.

Network Lifetime Optimization in Multi-hop Industrial Cognitive Radio Sensor Networks

Industrial cognitive radio sensor networks (ICRSNs) extend channel resources by occupying the vacant licensed channels in the absence of licensed users. In ICRSNs, industrial devices should switch to a common available channel to set up a communication link. However, channel switching leads to severe energy consumption. As the energy resources of battery-powered industrial devices are limited, it is crucial to carefully allocate channels to prolong the network lifetime of multi-hop ICRSNs. This paper is the first work that studies the channel allocation problem to optimize the network lifetime by considering the channel-switching (CS) energy consumption and the time-critical requirements of industrial applications. The problem is formulated to maximize the minimum residual energy at each round of data transmission, which is linearized as integer linear programming. As the channel allocation results will affect the residual energy at subsequent rounds, we propose a switching distance-optimized channel allocation (SDOCA) scheme that shortens the CS distances to improve the residual energy of each device. Moreover, we analyze the characteristics of SDOCA, i.e., convergent CS distance and guaranteed end-to-end delay. Extensive simulation results show that SDOCA can adaptively allocate channels according to the end-to-end delay requirement and significantly prolong the network lifetime.

Microwave imaging for watermelon maturity determination

Microwave imaging technology is a useful method often applied in medical diagnosis and can be used by the food industry to ensure food safety and quality. For fruit, ripeness is the primary characteristic which determines quality for the consumer. This paper proposes a novel microwave imaging system to determine the ripeness of watermelon as a proof of concept. The design employs a circular array with 10 Coplanar Vivaldi antennas offering wide bandwidth, high gain, and high efficiency. S-parameters between antennas are collected quickly via automated channel switching for fast image generation. Eight different watermelon samples of varying ripeness, type, dimensions, and origin are scanned and imaged. Comparisons with sample cross-sections show distinct differences in image characteristics based on watermelon maturity. Sugar concentration of unripe and ripe watermelon is also measured and plotted for further validation of the imaging technique.

Energy efficient two-stage capacity allocation scheme for WBAN healthcare applications

Co-channel interference occurs in coexisting Wireless Body Area Networks (WBANs) and has an impact on the capacity allocation of the networks. The proposed Two Stage Capacity Allocation (TSCA) mitigates interference and maximizes the capacity of poor channel quality WBANs with high priority data. It uses traditional interference mitigation schemes such as transmission power level control, channel switching and relay-aided transmission in each instant of pause time. The proposed work introduces a metric called Emergency Residual Index (ER-Index) and chooses any one of the mitigation schemes. The ER Index value provides a trade-off between residual energy, emergency factor and channel metrics. Further, TSCA executes a two-stage capacity allocation method. The TSCA scheme is a combination of the Nash bargaining solution and the Min-Max algorithm. The mitigated interference is 45% compared to Dynamic link quality-based Sub Channel Allocation (DSCA) and 60% compared to Traffic Aware Medium Access Control (TA-MAC). The average energy consumption is decreased up to 37.82% compared to TA-MAC and 25.59% compared to the DSCA algorithm.

Heterogeneous Strain Distribution Based Programmable Gated Microchannel for Ultrasensitive and Stable Strain Sensing.

Developing highly sensitive strain sensors requires conduction pathways capable of rapidly switching between disconnection and reconnection in response to strain. Ion channels in living organisms exactly control the channel switch through protein-composed gates, achieving changeable ion currents. Herein, inspired by the gating characteristics of the ion channels, a programmable fluidic strain sensor enhanced by gating ion pathways through heterogeneous strain distribution of discrete micropillars is proposed. During stretching, the contraction and closure of the widthwise gaps between discrete micropillars greatly weaken or even nearly cut off the conduction pathway, resulting in orders of magnitude increase in resistance and thus ultrahigh sensitivity. By adjusting the combination form and structural parameters of the discrete micropillars in the fluidic channel, the sensitivity and strain range can be customized. Thus, a gauge factorof up to 45300and a stretch range of 590% are obtained. Benefiting from the fluidic gating mechanism, no mechanical mismatch can be observed at the interface, breaking through the sensing stability issue of flexible sensors. The proposed sensor can be used to detect the full range of human motion, and integrated into a data glove to achieve human-machine interaction.

Switch Matrix System for Automatic Test Path Finding Algorithm

This paper introduces a switch matrix system that uses a configurable switch matrix to realize test channel switching. Through this configurable switch matrix system, N channels to be tested can be connected to N channels to be tested according to user requirements. Since the design of each node of the switch matrix is similar, it is convenient to expand and reduce horizontally and vertically according to the requirements. Switch Matrix adopts a double-layer design, which can obtain the optimal connection path between the tested channel and the tested channel with a path search algorithm.

High-throughput and energy-efficient data gathering in heterogeneous multi-channel wireless sensor networks using genetic algorithm

The need for high throughput in Wireless Sensor Networks (WSNs) necessitates the use of the Multi-Channel (MC) scheme. Existing multi-channel approaches used single or multi-radio sensors to exploit channel resources. The former scheme yields low throughput as well as considerable overhead for channel switching. On the other hand, the latter is costly due to installing multiple radios per node. This study applies the MC scheme to heterogeneous WSNs to bridge this gap. It assumes some super nodes that are equipped with multiple radios. These nodes are used as Cluster Heads (CHs) and are responsible for delivering the gathered data from normal sensors to the Base Station (BS). A high-throughput and energy-efficient algorithm is proposed to perform clustering, routing, and channel assignment in the heterogeneous setting. The proposed method decouples the original problem into two phases and solves them using genetic algorithm. The first phase is devoted to constructing a spanning tree over super nodes and assigning proper channels to their radios. A novel multi-objective cost function is proposed which prolongs network lifetime considerably compared to existing tree construction approaches. It also increases throughput by balancing the observed interference throughout the network. In the second phase of the proposed algorithm, the proper CH and channel per normal node are determined. The extensive simulations demonstrate that the proposed algorithm obtains high throughput using multiple channels. Additionally, it improves total energy consumption and energy exhaustion per delivered bit to the BS by 21.6% and 48.3% compared to the previous schemes.

Optimized channel prediction and auction‐based channel allocation for personal cognitive networks

SummaryCognitive networks are stands out as intelligent technology which evolved to enhance spectrum utilization. Secondary users are allowed to utilize the primary user's frequency bands on idling times. Identifying the idle licensed spectrum is achieved through spectrum sensing. The spectrum holes should be explored such that a suitable spectrum can be selected and allocated to the secondary users. Existing spectrum sensing and selection schemes have limitations due to interferences. Thus, an optimization algorithm based on bio‐inspired improved weed optimization was presented in this research work for enhanced channel utilization. The optimization model explores the channel characteristics and reduces the primary network interferences through its optimal solution. Further, Markov greedy‐based auction scheme was presented for channel allocation. Considering the channel capacity, delay, and switching rates the allocation is performed to enhance the overall system performance. Simulation analysis demonstrates the superior performance of the proposed model over existing techniques like particle swarm optimization and genetic algorithm.

Self‐powered virtual olfactory generation system based on bionic fibrous membrane and electrostatic field accelerated evaporation

AbstractOlfactory plays an important role in virtual reality technology. In this work, a bionic fibrous membrane (BFM) integrated with the function of electrostatic field accelerated evaporation (EFAE) is applied for realizing the virtual olfactory generation (VOG) system. The BFM is capable of self‐driven unidirectional liquid transmission and EFAE process is induced on BFM by using an ultrafast voltage‐elevation triboelectric nanogenerator (UVE‐TENG). The output voltage from UVE‐TENG can reach 8 kV within 40 ms, which is enough to maintain all of the functions of VOG system. Meanwhile, the output current from UVE‐TENG is smaller than 1 μA, leading to a safe and human compatible system. The flow rate of the volatile liquid spray from the system emitter can reach 0.1 μl/s, and the average evaporation rate of the BFM device with integrated EFAE function is 0.12 mg/s. Accordingly, the user of this VOG system can feel the generation of odor within 3 s, while the switching of different odor channels can be wirelessly controlled by a mobile phone. This VOG system enhances the user's immersive and interactive experience for virtual reality technology. The similar system composed of UVE‐TENG, reed switch, BFM and EFAE devices also has potential application value in assisted breathing treatment and nasal delivery.image

Priority based dynamic spectrum management using Virtual Utility Functions in Cognitive Radio enabled Internet of Things

Fast growth of wireless devices in IoT (Internet of Things), industry 5.0 and 6G cellular networks, is dealing with the challenge of spectrum scarcity and uneven utilization of available resources. To achieve Ambient Intelligence (AmI) in IoT communication network, dynamic utilization of available network resources, is a challenge faced by resource constraint IoT devices. Cognitive radio technology enables these devices to intelligently sense the free spectrum holes and smartly manage available channels opportunistically. To jointly deal with the challenge of spectrum scarcity and application specific network service provision, we propose a novel multi-attribute based two-tier framework called Cognitive Radio Efficient Spectrum Utilization (CR-ESU) which integrates the concept of Network Function Virtualization (NFV) as Virtual Utility Functions (VUFs) with cognitive radio enabled IoT devices to achieve the dynamic and flexible network services as well as spectral efficiency. The proposed framework is one of the pioneer works that incorporate the two ground breaking technologies, NFV and CRN to create a smart and flexible CR-enabled IoT network. CR-ESU also ensures the best channel selection using Dynamic Channel Reservation (DCR) scheme to decrease the channel switching rate. Continuous Time Markov Chain (CTMC) model is used for network modeling and mathematical expression formation. Promising results show the potential of CR-ESU framework to form a reconfigurable and efficient network.