Enhance Transmission Efficiency Research Articles

A secure and effective image encryption scheme by combining parallel compressed sensing with secret sharing scheme

In the complex network environment, it is becoming more and more significant to protect the security of information during transmission. A secure and effective image encryption scheme by combining parallel compressed sensing with secret sharing scheme is presented in this paper. Firstly, an image is measured by parallel compressed sensing, which not only realizes compression and encryption in the meantime, but also reduces computational complexity and storage space, and enhances transmission efficiency. Secondly, a block Arnold transformation is applied to process the measurement value image, and the obtained image is called a secret image, so as to achieve the effects of scrambling and encryption. Then, the secret image is partitioned into n shadow images by Shamir’s (t,n)-threshold secret sharing scheme, at least any t of n shadows images are able to recover the secret image, so the size of shadow images can be adjusted according to different application scenarios, which is flexible. This method realizes the encryption effect, and enhances the security of the secret image. Finally, to ensure the security of shadow images, the Zigzag confusion is introduced to process n shadow images and realizes the encryption effect. Experimental results manifest that our scheme realizes security and availability of the network system under the condition of limited resources.

Novel event-triggered protocol to sliding mode control for singular semi-Markov jump systems

This study presents a memory-based sliding mode control for singular semi-Markov jump systems using a novel dynamic-memory event-triggered protocol. Based on the average dwell-time strategy, a deterministic switching signal was developed to adjust the variation of the semi-Markov chains. Randomly occurring deception attacks are considered owing to the existence of an adversary. Furthermore, to enhance transmission efficiency and achieve better control performance, a novel dynamic-memory triggering condition is proposed, in which both historical transmitted data and two auxiliary dynamic variables are implemented. Based on the proposed protocol and Lyapunov theory, some parameter-dependent sufficient criteria are established to guarantee mean-square exponential stability and strictly dissipative performance, and the desired memory-based sliding mode controller is designed. Finally, two simulation examples were presented to verify the effectiveness of the proposed methodology.

Enhancing Transmission Efficiency of Mega-Constellation LEO Satellite Networks

Mega-constellation Low Earth Orbit (LEO) Satellite Networks (LSNs) have become an ongoing projection to realize the ubiquitous large-capacity wireless communication. With the rapid growth of satellite scale, the transmission efficiency of Mega-constellation LSNs is substantially decreased as the Average Shortest Path Length (ASPL) is dramatically increased, which not only encumbers the high-speed data transmission, but results in more processing delay, cost of satellite energy, rerouting probability and loss rate of packets. To this end, this paper proposes the structural optimization methods of Two-Layered Satellite Networks (TLSNs) to enhance the transmission efficiency of Mega-constellation LSNs. Differing from the traditional TLSNs, the proposed TLSNs emphasize on the highly integration between the different layers. The evaluated results confirm that the proposed methods not only effectively enhance the transmission efficiency of mega-constellation LSNs, but significantly increase the duration time of Inter-Layer Links (ILLs) and reduce the topological dynamics of TLSNs deriving from the switching of ILLs.

Machine Learning based Frame Size Optimization in WLAN Downlink MU-MIMO Channel with the Least Cost of Delay

The key enhancement in the medium access control (MAC) layer is frame aggregation introduced by the IEEE 802.11n/ac standard to accommodate the growing traffic demand in the WLAN by allowing multiple packets aggregated per transmission. Frame aggregation efficiently reduces control overhead in the MAC layer, such as the MAC header and thus it helps to enhance transmission efficiency and throughput performance of WLAN. However, heterogeneous traffic demand among streams in the WLAN downlink MU-MIMO channel creates a challenge to efficiently utilize the benefits of frame aggregation. Transmission efficiency is also compromised during frame size setting determination because when a frame size is larger, the impact of the overhead frame can be lower, but they are also more vulnerable to transmission errors. Thus, this trade-off between maximizing frame size and minimizing overhead frames should be addressed by employing an adaptive frame aggregation technique to derive the optimal frame size that would maximize the throughput in WLAN downlink MU-MIMO channel. Moreover, when frame aggregation approach is employed, more frames must wait before transmission in a buffer which causes a delay in the performance of WLAN. Thus, analysing the trade-off between maximizing throughput and minimizing delay is a critical issue that should also be addressed to enhance the performance of WLAN. However, the majority of the existing adaptive aggregation algorithms in the WLAN downlink MU-MIMO channel are focused to maximize the throughput or minimize the delay. The main contribution of this paper is to propose a machine learning-based frame size optimization algorithm by extending our earlier approach in considering the cost of delay to maximize the system throughput of WLAN. The effectiveness of the proposed scheme is evaluated over the FIFO Baseline Approach and earlier conventional approaches under the effects of various traffic patterns, channel conditions, and the number of STAs.

Enhanced transmission efficiency of begomoviruses by a single whitefly (Bemisia tabaci) using a microcage technique

Enhanced transmission efficiency of begomoviruses by a single whitefly (Bemisia tabaci) using a microcage technique

Flexible THz Carrier‐Envelope Phase Shifter Based on Metamaterials

AbstractThe ability to manipulate terahertz (THz) waveform is important for its applications. Despite rapid progress in metamaterials (MMs), the carrier‐envelope phase (CEP) control for THz pulse is still challenging due to its broadband feature. THz scanning tunneling microscope (THz‐STM), as an emerging technique combining both high temporal and spatial resolution, imposes additional requirements. Here, an ultra‐thin and flexible THz CEP shifter with five groups of different MM arrays is proposed. The CEP shifter is based on a specified split‐ring resonator with a pair of cross‐oriented gratings to enhance transmission efficiency. Simulation and experimental results show that the CEP of the THz pulse is modulated by passing through different MM arrays in turn, which can be shifted as high as 2π. The CEP shifter has good tolerance to wide‐angle oblique incidence and structural bending, which is expected to be used as a key component for THz‐STM. The structure of the CEP shifter has many potential applications, including THz wave focusing, beam‐steering, spatial phase modulation, and structured light generation.

A So-Far Overlooked Secondary Conformation State in the Binding Mode of SARS-CoV-2 Spike Protein to Human ACE2 and Its Conversion Rate Are Crucial for Estimating Infectivity Efficacy of the Underlying Virus Variant.

ABSTRACTSince its outbreak in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread with high transmission efficiency across the world, putting health care as well as economic systems under pressure. During the course of the pandemic, the originally identified SARS-CoV-2 variant has been multiple times replaced by various mutant versions, which showed enhanced fitness due to increased infection and transmission rates. In order to find an explanation for why SARS-CoV-2 and its emerging mutated versions showed enhanced transmission efficiency compared with SARS-CoV (2002), an enhanced binding affinity of the spike protein to human angiotensin converting enzyme 2 (hACE2) has been proposed by crystal structure analysis and was identified in cell culture models. Kinetic analysis of the interaction of various spike protein constructs with hACE2 was considered to be best described by a Langmuir-based 1:1 stoichiometric interaction. However, we demonstrate in this report that the SARS-CoV-2 spike protein interaction with hACE2 is best described by a two-step interaction, which is defined by an initial binding event followed by a slower secondary rate transition that enhances the stability of the complex by a factor of ~190 (primary versus secondary state) with an overall equilibrium dissociation constant (KD) of 0.20 nM. In addition, we show that the secondary rate transition is not only present in SARS-CoV-2 wild type (“wt”; Wuhan strain) but also found in the B.1.1.7 variant, where its transition rate is 5-fold increased.IMPORTANCE The current SARS-CoV-2 pandemic is characterized by the high infectivity of SARS-CoV-2 and its derived variants of concern (VOCs). It has been widely assumed that the reason for its increased cell entry compared with SARS-CoV (2002) is due to alterations in the viral spike protein, where single amino acid residue substitutions can increase affinity for hACE2. So far, the interaction of a single unit of the CoV-2 spike protein has been described using the 1:1 Langmuir interaction kinetic. However, we demonstrate here that there is a secondary state binding step that may be essential for novel VOCs in order to further increase their infectivity. These findings are important for quantitatively understanding the infection process of SARS-CoV-2 and characterization of emerging SARS-CoV-2 variants of spike proteins. Thus, they provide a tool for predicting the potential infectivity of the respective viral variants based on secondary rate transition and secondary complex stability.

A Wireless Power Transfer System Based on Dual-Band Metamaterials

Wireless power transfer (WPT) received widespread research in various field, such as wireless power in consumer electronics and electric vehicles. Recent researches have shown that adding metamaterials to the WPT system was an effective method to enhance transmission efficiency and distance. In view of the fact that traditional metamaterial slab often had a single working frequency point and was not suitable for multifrequency WPT, this letter analyzed and discussed the mechanism of magnetic negative metamaterial enhancing WPT efficiency. Moreover, two kinds of metamaterials, self-resonant dual-band negative permeability (SRDB-NPM) metamaterial and externally compensated dual-band negative permeability (ECDB-NPM) metamaterial, were designed. Finally, the effectiveness of two kinds of dual-band metamaterials to improve the efficiency at two different frequencies is verified by simulation and experiment.

Enhanced transmission efficiency of magneto-inductive wave propagating in non-homogeneous 2-D magnetic metamaterial array

In this work, we investigate the propagation of magneto-inductive waves (MIWs) in ordering magnetic metamaterial (MM) structures. The proposed non-homogeneous MM slab consists of 9 × 9 MM unit cells constructed from a five-turn spiral embedded on an FR-4 substrate. External capacitors with the value of 40 pF or 50 pF were added to control the resonant frequency of each unit cell in accordance with the waveguide configurations. The characteristics of metamaterial structures, such as negative permeability, current ratio, transmission response, and field distribution in the waveguide, have been thoroughly analyzed by simulation and experiment. A non-homogeneous metamaterial slab operating in the MHz frequency range with a low propagation loss is demonstrated. Because of the strong magnetic field confinement in the waveguide, the transmittance after nine elements of the non-homogeneous MM slab is 5.2 times greater than that of the homogeneous MM slab. This structure can be applied to the planar near-field wireless power transfer, position sensor, and low-frequency communication.

Piston-Mode pMUT With Mass Load

This paper proposes a novel piezoelectric micromachined ultrasonic transducer (pMUT) with a proof mass under the central circular diaphragm to enhance transmission efficiency and fractional bandwidth (FBW) in liquid-coupled operation. Compared with the traditional pMUT, the proposed pMUT has advantages: (1) the resonance frequency of pMUT can be adjusted by proof mass; (2) a large ratio of third-order resonance frequency to first-order resonance frequency can be obtained by an additional proof mass under the circular diaphragm; (3) the mode shape of proposed pMUT changes from Gaussian-like to piston-like, which enables higher transmission sensitivity; (4) the FBW can be improved through a trade-off design. The characteristics of resonance frequency, output power, and FBW of pMUT with different proof mass are analyzed with a piezoelectric layer of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1~\mu \text{m}$ </tex-math></inline-formula> and a structural layer of 5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> . In this work, the far-field sound pressure is 240.5 Pa/V in water, 49.5 Pa/V higher than the traditional pMUT, benefiting from the piston diaphragm movement. Furthermore, a 23% −6 dB FBW in water is demonstrated by theoretical analysis and parameter optimization. This work provides constructive advice for pMUT for better performance of transmission and resolution.

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of Internet-of-Things (IoT) devices on the ocean. This leads to a growing demand for high-speed and ultrareliable maritime communications. It has been reported that a large performance loss is often inevitable if the existing fourth-generation (4G), fifth-generation (5G), or satellite communication technologies are used directly on the ocean. Hence, conventional theories and methods need to be tailored to this maritime scenario to match its unique characteristics, such as dynamic electromagnetic propagation environments, geometrically limited available base station (BS) sites and rigorous service demands from mission-critical applications. Toward this end, we provide a survey on the demand for maritime communications enabled by state-of-the-art hybrid satellite-terrestrial maritime communication networks (MCNs). We categorize the enabling technologies into three types based on their aims: 1) enhancing transmission efficiency; 2) extending network coverage; and 3) provisioning maritime-specific services. Future developments and open issues are also discussed. Based on this discussion, we envision the use of external auxiliary information, such as sea state and atmosphere conditions, to build up an environment-aware, service-driven, and integrated satellite-air-ground MCN.

Impact of Genetic Variability in ACE2 Expression on the Evolutionary Dynamics of SARS-CoV-2 Spike D614G Mutation.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) glycoprotein D614G mutation became the predominant globally circulating variant after its emergence in the early coronavirus disease 2019 (COVID-19) pandemic. Studies showed that this mutation results in an open conformation of the S glycoprotein receptor-binding domain (RBD), and increased angiotensin 1-converting enzyme 2 (ACE2) binding and fusion, which result in an increase in SARS-CoV-2 transmissibility and infectivity. Dynamic tracking of SARS-CoV-2 showed that the D614G variant became predominant after emergence in Europe and North America, but not in China. The current absence of selective pressures from antiviral treatment suggests that the driving force for viral evolution could be variations in human population genetics. Results show that ACE2 expression is higher in Asian populations than that in European, North American, and African populations. This supports the idea that lower ACE2 expression is a driving force in the positive selection for the D614G mutation. This study suggests that the dynamics of the SARS-CoV-2 D614G mutation during the early-to-mid pandemic is associated with enhanced transmission efficiency in populations with lower ACE2 expression. Understanding the role that human genetic diversity plays in the adaptive evolution of SARS-CoV-2 may have an important impact on public health and measures to control the pandemic.

Free control of far-field scattering angle of transmission terahertz wave using multilayer split-ring resonators’ metasurfaces

To enhance transmission efficiency of Pancharatnam-Berry (PB) phase metasurfaces, multilayer split-ring resonators were proposed to develop encoding sequences. As per the generalized Snell’s law, the deflection angle of the PB phase encoding metasurfaces depends on the metasurface period’s size. Therefore, it is impossible to design an infinitesimal metasurface unit; consequently, the continuous transmission scattering angle cannot be obtained. In digital signal processing, this study introduces the Fourier convolution principle on encoding metasurface sequences to freely control the transmitted scattering angles. Both addition and subtraction operations between two different encoding sequences were then performed to achieve the continuous variation of the scattering angle. Furthermore, we established that the Fourier convolution principle can be applied to the checkerboard coded metasurfaces.

Multi-Agent Deep Reinforcement Learning-Based Flexible Satellite Payload for Mobile Terminals

Information dissemination in mobile networks turns out to be a problem when the network is sparse. Mobile networks begin to establish a separate cluster attributable to the limited communication range of terminals. The multi-beam satellite communication systems can play a significant role in providing direct-to-user satellite mobile services and connecting the separated clusters. This paper focuses on how to efficiently schedule limited satellite-based radio resources to enhance transmission efficiency and meet the requested traffic with low complexity. Taking the inter-beam interference and resource utilization variance into consideration, we build a game-theoretic based model for bandwidth allocation in the forward link. As the size of satellite beams increases, the size of the action space for deep reinforcement learning based on a single agent becomes large, resulting in high time complexity. Thus, we extend the single-agent deep reinforcement learning to the multi-agent context and then propose a cooperative multi-agent deep reinforcement learning method to achieve the optimal bandwidth allocation strategy. Each beam works as a player who is willing to satisfy the request traffic with flexible payloads. We built a multi-beam satellite platform using real historical data. The experimental results show that this approach is capable of enhancing transmission efficiency and can be flexible to achieve the desired goal with low complexity.

Distributed Intelligence: A Verification for Multi-Agent DRL-Based Multibeam Satellite Resource Allocation

Centralized radio resource management method puts all of the computational burdens in an agent, which is unbearable with the increasing of data dimensionality. This letter focuses on how to schedule limited satellite-based radio resources efficiently to enhance transmission efficiency and extend broadband coverage with low complexity. We propose a cooperative multi-agent deep reinforcement learning (CMDRL) framework to achieve the radio resources management strategy. The bandwidth allocation problem is taken as an example to analyze the proposed novel method in simulation. The experimental results show that this approach is capable of enhancing transmission efficiency and be flexible to achieve the desired goal with low complexity.

Understanding the mechanisms driving the spread of subtype C HIV-1.

Human immunodeficiency virus type 1 (HIV-1) subtype C (C-HIV) is the most prevalent form of HIV-1 globally, accounting for approximately 50% of infections worldwide. C-HIV is the predominant and near-exclusive subtype in the low resource regions of India and Southern Africa. Given the vast diversity of HIV-1 subtypes, it is curious as to why C-HIV constitutes such a large proportion of global infections. This enriched prevalence may be due to phenotypic differences between C-HIV isolates and other viral strains that permit enhanced transmission efficiency or, pathogenicity, or might due to the socio-demographics of the regions where C-HIV is endemic. Here, we compare the mechanisms of C-HIV pathogenesis to less prominent HIV-1 subtypes, including viral genetic and phenotypic characteristics, and host genetic variability, to understand whether evolutionary factors drove C-HIV to predominance.

A Hybrid Spectrum Access Strategy with Channel Bonding and Classified Secondary User Mechanism in Multichannel Cognitive Radio Networks.

Cognitive radio networks (CRNs) can improve spectrum utilization by allowing secondary users (SUs) to dynamically access channels unoccupied by primary users (PUs). The spectrum access strategy, as a point to enhance user performance, has received much attention. In this paper, we propose a hybrid access mode for network users in multichannel CRNs. For meeting different SU demands, SUs are classified as SU1s and SU2s. We further introduce a channel bonding scheme for high-priority (PU and SU1) user packets to enhance transmission efficiency. At the same time, we propose a hybrid spectrum access strategy for SU2 packets to improve their transmission stability. By establishing a Markov chain model, some important SU2 packets’ performance measures are derived. Furthermore, we display the comparison of hybrid, overlay and underlay modes by numerical results to analyze the advantages of different modes.

Identifying Transmission Opportunity through Transmission Power and Bit Rate for Improved VANET Efficiency

With the development of vehicular industry and wireless communication technology, vehicular ad hoc network (VANET) has become a popular research field. However, timely dissemination of safety related information in VANET is always challenging due to the highly dynamic vehicular environment. In this paper, we investigate an analytic approach in enhancing transmission efficiency of VANET by adapting transmission power and bit rate for IEEE 802.11p based VANET. The proposed algorithm, Joint Adaptation of Transmission power and Bit rate (JATB) algorithm uses modified Dynamic Programming (DP) to search for optimal value of transmission power and bit rate with the aim to increase packet success rate, minimize end-to-end delay and minimize busy time. JATB also uses vehicle density to improve vehicular environment awareness, and adapt transmission power and bit rate accordingly. Adaptability of JATB algorithm is tested with different beacon rates and simulation scenarios. Simulation results show an improvement in transmission efficiency as compared to standard protocol [original algorithm set in VANET standard which has fixed transmission power (20 mW) and fixed bit rate (6Mbps)] and reference journal’s Transmission Power Transmission Range (TPTR) [algorithm from reference journal that adapts transmission power according to transmission range] algorithms.

Enhanced Optical Properties of Colored Semitransparent Ultrathin Hybrid Solar Cells Employing Fabry–Pérot Etalon With a Dielectric Overlay

We investigate the effect of a dielectric overlay in a planar microcavity on optical performances of colorful, see-through ultrathin amorphous silicon/organic hybrid solar cells, where a conventional Fabry–Perot cavity is integrated with a cathode. The proposed colored solar cell devices show an enhanced transmission efficiency by optimizing both a thickness and a refractive index of the dielectric overlay at a resonance wavelength, which is primarily attributed to a better admittance matching. In addition, a purity of semitransparent red, green, and blue colors is improved by increasing a thickness of metallic layers in the microcavity with little sacrificing the transmission efficiency; thus, achieving a wide color gamut coverage as compared to conventional liquid crystal displays. Furthermore, mitigating reflection losses at complementary wavelength ranges and creating sharp resonances lead to an improved photocurrent generation from the semitransparent hybrid solar cells. The study described in this work provides insights and possibilities to enhance the characteristic performances of diverse applications, such as energy-efficient display technologies and decorative solar cells.

Single reflection nanocavity enhanced transmission efficiency of a nanoplasmonic wavelength demultiplexer

As a kind of nanostructure device, a surface plasmon polariton (SPP) nanostructure filter can realize effective manipulation of photons at the nanometer or subwavelength scale. In particular, resonator-based multiplexer channel drop filters have been proposed and studied widely. However, a main problem is that the transmission efficiencies of such filters are relatively low. Thus, reflection cavities are designed to enhance the transmission efficiency obviously. However, a traditional demultiplexer usually requires several reflection cavities because only one mode is utilized in a reflection cavity. In this paper, for the first time to our knowledge, a single reflection cavity is designed to enhance the transmission efficiency of three channels at the same time via the use of multiple modes in the reflection cavity. The theory and simulation analysis confirm the validity of such a structure, and the transmission efficiency of the three channels can be doubled. We believe this work provides novel notions for the design of a demultiplexer filter.