Bandwidth Information Research Articles

Time domain correlation entropy image conversion: A new method for fault diagnosis of vehicle-mounted cable terminals

The identification of partial discharge (PD) in cable terminals is crucial for the safe operation of trains. However, the complexity of the operational environment and the similarity of PD signals make defect identification challenging. Consequently, this paper proposes a Time-domain Local Correlation Entropy Image (T-LCEI) transformation method, which constructs an entropy matrix to convert raw PD signals into images. These images embed feature and bandwidth information from the original PD data, significantly enhancing the ability to differentiate between similar PD signals. Furthermore, the method combines a Dual Attention Convolutional Neural Network (DA_CNN) for the effective classification of correlation entropy images. Experimental results demonstrate that this approach achieves an average classification accuracy of 99.69% across four typical PD defect datasets, with a testing accuracy of 97.75% in practical scenarios. Compared to existing PD detection methods, T-LCEI offers significant improvements in effectiveness and discriminability. The integration of DA_CNN further enhances recognition accuracy. The study demonstrates that the proposed method excels in PD defect identification, providing reliable technical support for on-site fault detection and maintenance, thereby significantly improving the operational safety of cable terminals.

The role of visual spatial frequencies in newborns' processing of dynamic facial expressions of emotion.

Evidence on newborns' discrimination of emotional facial expressions is scarce, and the question of what is the nature of the visual information that newborns rely on to perform such discrimination remains open. Here, we manipulated the spatial frequency (SF) content of the stimuli by selectively removing low spatial frequency (LSF) and high spatial frequency bands using newborn-appropriate cutoffs to investigate what information newborns use when preferring and discriminating between dynamic displays showing happy and fearful expressions unfolding over time. Using a preferential looking paradigm, in Study 1 (N = 63, 59% females, 92% White), we showed that newborns looked longer to happy over fearful expressions in unfiltered (broad spatial frequency) and high-pass (high spatial frequency > 0.6 cycles per degree [cpd]) faces but not in low-pass (LSF < 0.5 cpd) faces. In Study 2 (N = 22, 59% females, 91% White), newborns tested in a visual habituation paradigm showed successful discrimination of the two LSF emotions. Results show that newborns can discriminate between dynamic images of happy and fearful facial expressions containing either extreme low SF (< 0.5 cpd) information or higher SF (> 0.6 cpd) bandwidth. Their preference for the happy expression was present for intact and high-pass filtered faces but not for low-pass faces. This SF effect is tentatively driven by an enhancement of attentional response to the LSF fearful face, whereas the response to the happy face is unaffected by the SF manipulation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

SDN-Based Congestion Control and Bandwidth Allocation Scheme in 5G Networks

5G cellular networks are already more than six times faster than 4G networks, and their packet loss rate, especially in the Internet of Vehicles (IoV), can reach 0.5% in many cases, such as when there is high-speed movement or obstacles nearby. In such high bandwidth and high packet loss network environments, traditional congestion control algorithms, such as CUBIC and bottleneck bandwidth and round-trip propagation time (BBR), have been unable to balance flow fairness and high performance, and their flow rate often takes a long time to converge. We propose a congestion control algorithm based on bottleneck routing feedback using an in-network control mode called bottleneck routing feedback (BRF). We use SDN technology (OpenFlow protocol) to collect network bandwidth information, and BRF controls the data transmission rate of the sender. By adding the bandwidth information of the bottleneck in the option field in the ACK packet, considering the flow fairness and the flow convergence rate, a bandwidth allocation scheme compatible with multiple congestion control algorithms is proposed to ensure the fairness of all flows and make them converge faster. The performance of BRF is evaluated via Mininet. The experimental results show that BRF provides higher bandwidth utilization, faster convergence rate, and fairer bandwidth allocation than existing congestion control algorithms in 5G cellular networks.

Dynamic primitives in constrained action: systematic changes in the zero-force trajectory.

Humans substantially outperform robotic systems in tasks that require physical interaction, despite seemingly inferior muscle bandwidth and slow neural information transmission. The control strategies that enable this performance remain poorly understood. To bridge that gap, this study examined kinematically constrained motion as an intermediate step between the widely studied unconstrained motions and sparsely studied physical interactions. Subjects turned a horizontal planar crank in two directions (clockwise and counterclockwise) at three constant target speeds (fast, medium, and very slow) as instructed via visual display. With the hand constrained to move in a circle, nonzero forces against the constraint were measured. This experiment exposed two observations that could not result from mechanics alone but may be attributed to neural control composed of dynamic primitives. A plausible mathematical model of interactive dynamics (mechanical impedance) was assumed and used to "subtract" peripheral neuromechanics. This method revealed a summary of the underlying neural control in terms of motion, a zero-force trajectory. The estimated zero-force trajectories were approximately elliptical and their orientation differed significantly with turning direction; that is consistent with control using oscillations to generate an elliptical zero-force trajectory. However, for periods longer than 2-5 s, motion can no longer be perceived or executed as periodic. Instead, it decomposes into a sequence of submovements, manifesting as increased variability. These quantifiable performance limitations support the hypothesis that humans simplify this constrained-motion task by exploiting at least three primitive dynamic actions: oscillations, submovements, and mechanical impedance.NEW & NOTEWORTHY Control using primitive dynamic actions may explain why human performance is superior to robots despite seemingly inferior "wetware"; however, this also implies limitations. For a crank-turning task, this work quantified two such informative limitations. Force was exerted even though it produced no mechanical work, the underlying zero-force trajectory was roughly elliptical, and its orientation differed with turning direction, evidence of oscillatory control. At slow speeds, speed variability increased substantially, indicating intermittent control via submovements.

The hybrid pulse amplitude width modulation scheme: high efficiency technique for dimmable VLC systems

Abstract Visible-light communications (VLC) is an environmentally friendly optical wireless communication (OWC) technology that operates in the 400–800 THz frequency band. It is currently a critical technology for 5G and 6G wireless indoor applications due to its high data rates, low latency, and superior reliability. Intensity modulated direct detection (IM/DD) is widely used in VLC systems. A channel modulation scheme is designed using L-level pulse modulation techniques such as on–off keying (OOK), amplitude modulation (PAM), position modulation (PPM), and the width modulation (PWM). We introduce a novel hybrid modulation scheme n-M-PAWM based on both PAM and PWM schemes to improve throughput and significantly increase power and spectrum efficiency in VLC communication systems. The performance of our proposed hybrid n-M-PAWM scheme is studied in several aspects, including the number of transmitted bits per symbol, average BER, information rate ratio (IRR), PAPR, bandwidth, and power requirement. In an extremely noisy VLC system, the proposed 2-M-PAWM modulation outperforms both PPWM and PAPM modulation schemes due to its better BER performances. Additionally, we examine the performance of the VLC system in terms of spectral efficiency (SE) using our proposed PAWM-based dimming control system by varying the number of pulses transmitted during one symbol period. We demonstrate through simulation results that our PAWM-based dimming control system performs significantly better compared to the other pulse modulation schemes. All results of this research show that our proposed hybrid PAWM modulation scheme has high potential for VLC technology in indoor and noisy environments.

Edge ai technology in the defense industry via reinforcement learning in simulation environments

Edge artificial intelligence (Edge AI) technology helps to avoid vulnerabilities while benefiting from the advantages of cloud technologies, which are widely used today, especially with artificial intelligence and big data. In the case of transferring systems to the cloud, and needs such as protection of sensitive information and high bandwidth emerges in cloud approaches. Edge AI, which provides solutions to issues such as the security of sensitive data and reducing system traffic, while meeting the needs in this field, can offer a new perspective, especially to projects in the military field, when used with digital twin and autonomous system technologies. In this study, we evaluated the “Forces in virtual environment machine learning (FIVE-ML)” simulation system technically in which we use edge AI technology, analyzed the results obtained with the use of this technology. It has been determined that the current work is at the 2nd level in Edge AI levelling system, also there is a 54% performance (in terms of time with accuracy) increase with edge AI. Besides, the accuracy of hitting the target in simulation system is also increased, with the rate of 34%.

Cryogenic electron ptychographic single particle analysis with wide bandwidth information transfer

Advances in cryogenic transmission electron microscopy have revolutionised the determination of many macromolecular structures at atomic or near-atomic resolution. This method is based on conventional defocused phase contrast imaging. However, it has limitations of weaker contrast for small biological molecules embedded in vitreous ice, in comparison with cryo-ptychography, which shows increased contrast. Here we report a single-particle analysis based on the use of ptychographic reconstruction data, demonstrating that three dimensional reconstructions with a wide information transfer bandwidth can be recovered by Fourier domain synthesis. Our work suggests future applications in otherwise challenging single particle analyses, including small macromolecules and heterogeneous or flexible particles. In addition structure determination in situ within cells without the requirement for protein purification and expression may be possible.

Efficient congestion control scheme based on caching strategy in NDN

As a pioneering network architecture, Named Data Networking (NDN) leverages the content-centric model and connectionless transmission mode to enhance network capacity. Despite the emergence of numerous congestion control protocols aimed at improving NDN transmission efficiency, most of these approaches implicitly assume that each interest packet elicits one single data packet, which significantly restricts network performance. To address this issue, we introduce C3NDN, a Congestion Control scheme that leverages caching strategy in NDN. C3NDN formulates a One-Interest-Multiple-Data model to improve network efficiency, and employs a probabilistic caching strategy to cache popular content at important nodes and optimize the in-network caching characteristic of NDN. Furthermore, C3NDN incorporates a congestion control algorithm based on the One-Interest-Multiple-Data model, which considers the bandwidth and delay information of the transmission path. Additionally, C3NDN implements a marking method that takes full advantage of node cache and reduces transmission time. Extensive experiments have been conducted to show the performance of C3NDN, and the results demonstrate that C3NDN can reduce the transmission time by up to 41.68% when compared with the other congestion control schemes.

Fully Distributed Dynamic Edge-Event-Triggered Current Sharing Control Strategy for Multibus DC Microgrids With Power Coupling

Although the current sharing control of dc microgrids has been widely studied, the high communication bandwidth and global communication network structure information demands hander the renewable energy consumption. Thus, this article proposes a fully distributed dynamic edge-event-triggered current sharing control strategy for multibus dc microgrids with power coupling. First, the system model with power coupling is built, which is further switched to the linear heterogeneous multiagent systems with unknown disturbance. It is an indispensable preprocessing for controller design. Furthermore, the fully distributed current sharing control strategy is proposed through adaptive coupling weights. Note that the global communication network structure information demand is eliminated. Moreover, the fully distributed dynamic edge-event-triggered mechanism is proposed to reduce communication bandwidth. Compared with the previous dynamic event-triggered mechanisms applied into dc microgrids, the continuous communication between neighboring agents is avoided, and controller updating frequency is reduced. Finally, the simulation and experimental results verify the proposed control performance.

Research on Robustness of Financial Accounting Intelligent System Based on Offline Network Data Protection Algorithm

In cloud computing, user data storage and computing process are all carried out in the cloud, and the homomorphic encryption technology is used to realize end-to-end aggregation encryption. The objective requirements and development trends of the construction of financial and accounting information systems of banks in my country are discussed. Transaction and accounting Separated Yinqiao financial accounting information system. The primary task of BPM is to ensure that the business process of the enterprise should be oriented to customers and market demands, and then it studies the robustness of financial information systems, saving energy and bandwidth. At the same time, the track graph topology is constructed so that each node has multiple parent nodes, and when the link between the node and the main parent node fails, other parent nodes can repair the aggregated value.

Deep Learning for Inverse Design of Broadband Quasi-Yagi Antenna

Deep learning (DL) approaches have been increasingly adopted to design antenna autonomously. For obtaining geometry of the broadband quasi-Yagi antenna from its physic response images directly, we propose an inverse design approach based on the optimized bidirectional symmetry GoogLeNet, which can extract the required bandwidth information to redesign the geometric parameters of antenna without changing its physical structure. It demonstrates that the bandwidth of a reference quasi-Yagi antenna is improved from 0.6 GHz to 1.15 GHz through the proposed inverse design DL approach, and the measured bandwidth value of this redesigned quasi-Yagi antenna achieves 1.16 GHz, which is improved 93% actually. The numerical and measured results indicate that the proposed DL approach could significantly improve the performance of the existed quasi-Yagi antenna and present a new attempt to apply the image processing techniques in resolving physical problem.

Optimized Resource Allocation for IoT-D2D Communication Using WSN

The need for a strong system to access radio resources demands a change in operating frequency in wireless networks as a part of Radio Resource Management (RRM). In the fifth-generation (5G) wireless networks, the capacity of the system is expected to be enhanced by Device-to-Device (D2D) communication. The cooperation and Resources Allocation (RA) in the development of Internet of Things (IoT) enabled 5G wireless networks are investigated in this paper. Developing radio RA methods for D2D communication while not affecting any Mobile Users’ (MU) communication is the main challenge of this research. Distinct performance goals such as practising equality in the rates of user data, increasing Network Throughput (NT), and reducing End-to-End Delay (EED) are achieved by RA. The study undertaken on optimising performance for various wireless networks is focused on in this research work. Proposing a polynomial-time Proportional Fair Resource Allocation Method (PFRAM), which considers the MU’s rate requirements, is the prime objective of this paper. Any Resource Allocation Method (RAM) can be used by the proposed method for MU, and the time and differing location channel conditions are the factors to be adapted with. Allotting more than one resource block is allowed by our PFRAM to a D2D pair. The automatic maintenance of battery-less IoT wireless devices’ energy level is done potentially using an Extensible Energy Management System (EEMS). Finally, the device’s Node Transmission Power (NTP) can be managed using an Energy-Saving Algorithm (ESA) designed in this work for Node Uplink Data Transmission (NUDT). The trade-off between the Packet Loss Rate (PLR) and NTP is balanced by the algorithm. The cost of NUDT’s average Energy Consumption (EC) is reduced by locating the optical NTP. In order to free much bandwidth for wireless information, NUDT conserves the harvested energy for minimising Radio Frequency (RF) Energy Transmission (ET). MATLAB simulations are used to assess the proposed EEMS. The IoT device’s NTP is managed using ESA designed for NUDT. The significant minimisation of channel hopping EED and the selection of the premium quality communication channel by the proposed framework are indications of the simulation results. 67.19% is the bandwidth to transmit DPs with the Bandwidth Allocation Algorithm (BAA), which is greater than the cases in its absence.

Closed-Loop Control of a Multifunctional Myoelectric Prosthesis With Full-State Anatomically Congruent Electrotactile Feedback.

State-of-the-art myoelectric hand prostheses provide multi-functional control but lack somatosensory feedback. To accommodate the full functionality of a dexterous prosthesis, the artificial sensory feedback needs to convey several degrees of freedom (DoF) simultaneously. However, this is a challenge with current methods as they are characterized by a low information bandwidth. In this study, we leverage the flexibility of a recently developed system for simultaneous electrotactile stimulation and electromyography (EMG) recording to present the first solution for closed-loop myoelectric control of a multifunctional prosthesis with full-state anatomically congruent electrotactile feedback. The novel feedback scheme (coupled encoding) conveyed proprioceptive (hand aperture, wrist rotation) and exteroceptive information (grasping force). The coupled encoding was compared to the conventional approach (sectorized encoding) and incidental feedback in 10 non-disabled and one amputee participant who used the system to perform a functional task. The results showed that both feedback approaches increased the accuracy of position control compared to incidental feedback. However, the feedback increased completion time, and it did not significantly improve grasping force control. Importantly, the performance of the coupled feedback was not significantly different compared to the conventional scheme, despite the latter being easier to learn during training. Overall, the results indicate that the developed feedback can improve prosthesis control across multiple DoFs but they also highlight the subjects' ability to exploit minimal incidental information. Importantly, the current setup is the first to convey three feedback variables simultaneously using electrotactile stimulation while providing multi-DoF myoelectric control with all hardware components mounted on the same forearm.

Model-data-driven P-wave impedance inversion using ResNets and the normalized zero-lag cross-correlation objective function

Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance, which is significant in reservoir description and identification. Based on proper initial models, most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy, but not high resolution. Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and high-resolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks. However, these methods require a significant number of training samples, which are frequently insufficient. To obtain P-wave impedance with both high accuracy and high resolution, we propose a model-data-driven inversion method using ResNets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise. By using initial models and training samples, the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution. Tests on synthetic and field data demonstrate the proposed method's efficacy and practicability.

ANALYSIS OF RADIO COMMUNICATION SYSTEMS BY PERFORMANCE INDICATORS

The article deals with the analysis of radio communication systems based on performance indicators. It was established that modern complex radio communication systems cannot always be comprehensively characterized by one indicator. Evaluation by several indicators is more complete and more specific and allows to characterize various properties of the system. Optimization of the transmission system as a whole, i.e. taking into account encoding and decoding devices, is carried out on the basis of information theory.The most general evaluation of the efficiency of the communication system is the ratio of channel utilization by bandwidth (information efficiency). To ensure a given speed of information transmission and a given probability, it is necessary to spend some signal power and occupy a certain frequency band in the communication channel. What power and what frequency band will be needed depends on the communication system used.The efficiency of the information transmission system is evaluated by the coefficient of signal power utilization (energy efficiency) and the coefficient of channel bandwidth utilization (frequency efficiency). An increase in frequency efficiency requires an increase in energy costs (a decrease in energy efficiency).With high requirements for fidelity of transmission, it becomes expedient to use interference-resistant codes, which allow to increase energy efficiency in exchange for reducing the specific speed of information transmission. The simultaneous requirement of high speed and fidelity of information transmission in conditions of limited frequency and energy resources can be fulfilled by the joint use of multi-position signals and powerful interference-resistant codes.To assess the energy efficiency of radio communication systems, it is advisable to use the signal power utilization factor. The advantages of increasing energy efficiency are obvious: minimization of transmitter radiation power, improvement of electromagnetic compatibility of radio-electronic devices, increase of stealth of information transmission, minimization of energy consumption.

High-Performance Pockels Effect Modulation and Switching in Silicon-Based GaP/Si, AlP/Si, ZnS/Si, AlN/3C-SiC, GaAs/Ge, ZnSe/GaAs, and ZnSe/Ge Superlattice-On-Insulator Integrated Circuits.

We propose new a Si-based waveguided Superlattice-on-Insulator (SLOI) platforms for high-performance electro-optical (EO) 2 × 2 and N × M switching and 1 × 1 modulation, including broad spectrum and resonant. We present a theoretical investigation based on the tight-binding Hamiltonian of the Pockels EO effect in the lattice-matched undoped , , , , , , and wafer-scale short-period superlattices that are etched into waveguided networks of small-footprint Mach-Zehnder interferometers and micro-ring resonators to yield opto-electronic chips. The spectra of the Pockels r33 coefficient have been simulated as a function of the number of the atomic monolayers for “non-relaxed” heterointerfaces. The large obtained r33 values enable the SLOI circuit platforms to offer a very favorable combination of monolithic construction, cost-effective manufacturability, high modulation/switching speed, high information bandwidth, tiny footprint, low energy per bit, low switching voltage, near-IR-and-telecom wavelength coverage, and push-pull operation. By optimizing waveguide, clad, and electrode dimensions, we obtained very desirable values of the VπL performance metric, in the range of 0.062 to 0.275 V·cm, portending a bright future for a variety of applications, such as sensor networks or Internet of Things (IoT).

An Efficient Lightweight Image Encryption Scheme Using Multichaos

With an immense increase in Internet multimedia applications over the past few years, digital content such as digital images are stored and shared over global networks, the probability for information leakage and illegal modifications to the digital content is at high risk. These digital images are transferred using the network bandwidth; therefore, secure encryption schemes facilitate both information security and bandwidth issues. Hence, a state-of-the-art lightweight information security methodology is required to address this challenge. The main objective of this work is to develop a lightweight nonlinear mechanism for digital image security using chaos theory. The proposed scheme starts by changing a plain image into an encrypted image to improve its security. A block cipher, using lightweight chaos, has been added to achieve this objective for digital image security. We utilized multiple chaotic maps to generate random keys for each channel. Also, Arnold cat map and chaotic gingerbread map are used to add confusion and diffusion. During the permutation stage, image pixels are permuted, while in diffusion stage, pixels are distorted utilizing gingerbread map to add more security. The proposed scheme has been validated using different security parameter tests such as correlation coefficient tests (CC), whose results have been observed closer to zero and information entropy (IE) value is 7.99, respectively, which is almost equal to the ideal value of 8. Moreover, number of pixels changing rate (NPCR) obtained value is higher than 99.50%, while the unified average changing intensity (UACI) is 33.33. Other parameters such as mean absolute error (MAE), mean square error (MSE), lower value of peak to signal noise ratio (PSNR), structural content (SC), maximum difference (MD), average difference (AD), normalized cross-correlation (NCC), and histogram analysis (HA) is tested. The computed values of the proposed scheme are better. The achieved results after comparison with existing schemes highlight that the proposed scheme is highly secure, lightweight, and feasible for real-time communications.

Conservation of orbital angular momentum and polarization through biological waveguides

A major roadblock to the development of photonic sensors is the scattering associated with many biological systems. We show the conservation of photonic states through optically self-arranged biological waveguides, for the first time, which can be implemented to transmit light through scattering media. The conservation of optical properties of light through biological waveguides allows for the transmission of high bandwidth information with low loss through scattering media. Here, we experimentally demonstrate the conservation of polarization state and orbital angular momentum of light through a self-arranged biological waveguide, several centimeters long, in a sheep red blood cell suspension. We utilize nonlinear optical effects to self-trap cells, which form waveguides at 532 nm and 780 nm wavelengths. Moreover, we use the formed waveguide channels to couple and guide probe beams without altering the information. The formed biological waveguides are in a sub-diffusive scattering regime, so the photons’ information degrades insignificantly over several centimeters of propagation through the scattering media. Our results show the potential of biological waveguides as a methodology for the development of novel photonic biosensors, biomedical devices that require optical wireless communication, and the development of new approaches to noninvasive biomedical imaging.

Deep-learning-assisted communication capacity enhancement by non-orthogonal state recognition of structured light.

In light of pending capacity crunch in information era, orbital-angular-momenta-carrying vortex beams are gaining traction thanks to enlarged transmission capability. However, high-order beams are confronted with fundamental limits of nontrivial divergence or distortion, which consequently intensifies research on new optical states like low-order fractional vortex beams. Here, we experimentally demonstrate an alternative mean to increase the capacity by simultaneously utilizing multiple non-orthogonal states of structured light, challenging a prevailing view of using orthogonal states as information carriers. Specifically, six categories of beams are jointly recognized with accuracy of >99% by harnessing an adapted deep neural network, thus providing the targeted wide bandwidth. We then manifest the efficiency by sending/receiving a grayscale image in 256-ary mode encoding and shift keying schemes, respectively. Moreover, the well-trained model is able to realize high fidelity recognition (accuracy >0.8) onto structured beams under unknown turbulence and restricted receiver aperture size. To gain insights of the framework, we further interpret the network by revealing the contributions of intensity signals from different positions. This work holds potential in intelligence-assisted large-capacity and secure communications, meeting ever growing demand of daily information bandwidth.

Encoding of spatial patterns using electrotactile stimulation via a multi-pad electrode placed on the torso.

Tactile stimulation can be used to convey information to a user in different scenarios while avoiding overloading other senses. Tactile messages can be transmitted as spatial patterns, potentially allowing for a high information throughput. The aim of the present study was to design and test different encoding schemes to determine the best approach for conveying spatial patterns. Encoding schemes with simultaneous (SIM) and sequential pad activation (SEQ) were evaluated, including four SEQ variants designed to potentially facilitate the recognition. In SEQ-col and SEQ-row, the column and row of the activated pad were signified using different frequencies, while SEQ-all and SEQ-all-fast included the activation of all pads where those belonging to the pattern were indicated by changes in frequency (ON pads). The success rate (SR) of the pattern identification and the response time were quantified in 15 participants who recognized 20 patterns delivered through a 3 × 2 pad matrix placed on the lateral torso. SIM was not a feasible method to present the patterns (median, 15%; IQR, 5%). The SR improved with SEQ (median, 60%; IQR, 20%) and further increased with additional cues, particularly with SEQ-row (median, 78.3%; IQR, 23.3%) and SEQ-all (median, 96.7%; IQR, 5%). Importantly, the stimulation time of SEQ-all could be decreased without a substantial drop in accuracy (SEQ-all-fast: median, 89.2%; IQR, 19.2%). The spatiotemporal stimulation with sequential activation of all pads (SEQ-all) seems to be the method of choice when conveying tactile messages as spatial patterns. This is an important outcome for increasing the information bandwidth of communication through the tactile channel.