Information Packets Research Articles

Provable Security for the Onion Routing and Mix Network Packet Format Sphinx

Onion routing and mix networks are fundamental concepts to provide users with anonymous access to the Internet. Various corresponding solutions rely on the Sphinx packet format. However, flaws in Sphinx's underlying proof strategy were found recently. It is thus currently unclear which guarantees Sphinx actually provides, and, even worse, there is no suitable proof strategy available. In this paper, we restore the security foundation for all these works by building an analytical framework for Sphinx. We discover that the previously-used Decisional Diffie-Hellman (DDH) assumption is insufficient for a security proof and show that the Gap Diffie-Hellman (GDH) assumption is required instead. We apply it to prove that a slightly adapted version of the Sphinx packet format is secure under the GDH assumption. We are thus, to the best of our knowledge, the first to provide a detailed, in-depth security proof for Sphinx that holds. Our adaptations to Sphinx are necessary, as we demonstrate with an attack on sender privacy that would otherwise be possible in Sphinx's adversary model.

Preparing for Virtual Interviews: A Pilot Study to Understand the Needs of Interviewees.

Virtual interviews play a crucial role in the ranking process. National Resident Matching Program (NRMP) data shows a median number of 23.5 interviews per applicant. Considering this volume of interviews, graduate medical education programs must leverage the virtual pre-interview materials to impact applicants' attitudes and perceptions of the interview beforehand. This study is a secondary data analysis of an anonymous cross-sectional survey collected during two orientation sessions held in June and July 2022. Responses from 123 residents and fellows rated the usefulness of available print and virtual pre-interview resources. Using a 5-point Likert scale, social media sites scored an average usefulness score of 4.0, while the information packet and program website scored 3.88 and 3.90, respectively. This article provides recommendations for restructuring virtual resources to aid residents and fellows, specifically under-represented minorities in medicine (UiM) applicants, in having a quality interview experience.

Role of prior austenite grain boundary and retained austenite in strain localization of medium-carbon high-strength steels

Exploring the micromechanical behavior of lath-martensitic quenching and tempering (Q&T), as well as quenching and partitioning (Q&P) steels presents a significant challenge due to their complex multi-phase constituents and hierarchical structures. This study conducts a comprehensive comparative analysis using medium-carbon Q&T and Q&P steels with identical chemical compositions. Atom probe tomography (APT) was used to investigate the distribution of chemical elements, while high-resolution digital image correlation (HR-DIC) provided insights into nanoscopic strain localization and partitioning. Both Q&T and Q&P steels exhibit significant strain localization at prior austenite grain boundaries (PAGBs) due to substantial carbon segregation. Strain localization in Q&T steel at PAGBs and packet boundaries strongly depends on preferred geometric orientations, with boundaries inclined 45° to the loading direction experiencing severe deformation. Conversely, in Q&P steel, PAGBs adjacent to large clusters of fine lath martensite, lacking a packet with a longitudinal direction parallel to boundaries and a feasible in-lath slip system, primarily undergo deformation. Carbon partitioning from martensite to retained austenite (RA), along with coexisting carbon and manganese segregation at phase interfaces, stabilizes the RA, resulting in a neighborhood-dependent deformation behavior of RA. The existence of RA not only absorbs carbon, maintaining low strength and high deformability, but also uniformly distributes and induces stable interfaces to hinder the formation of large packets with easily activated in-lath slip transmission.

Design and Implementation of Optimized PCI Express Physical Layer for High-Speed and Low-Latency Data Transfer

The PCIe (Peripheral Component Interconnect Express) Protocol is crucial for establishing high-speed data communication between computer peripherals, such as graphics cards and network cards etc. This communication protocol is transmitting data in packet format, with each packet containing both data and destination address and other essential information for accurate data delivery. This paper focused on Physical Layer to achieve High-Speed Data Transmission by reducing delay parameter. To minimize disturbances and enhance reliability, the physical layer uses scrambling technique and an 8b – 10b encoding technique is used for synchronization and error detection. Additionally, SIPO and PISO converts data format to improve efficiency and accuracy. The design is implemented using the Cadence compiler targeting 45nm process technology. This design is delay efficient resulting in path delay of 5.0ns and the operating frequency of 200MHz, power consumption of 1.2mw and an area of 1999µm².

Effect of ultrasound combined with exogenous protein treatment on the flushing characteristics of puffed corn flour

To address issues such as clumping, spoon adherence, and the formation of powdery packets in puffed corn flour (PCF), this study incorporated three exogenous proteins—egg white powder (EWP), soybean protein isolate (SPI), and whey protein isolate (WPI)—and applied ultrasonication. This treatment improved PCF's physicochemical properties and microstructure. Ultrasonication increased the starch resistance and reduced the short-range ordering of the samples, as evidenced by in vitro digestion results, X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FT-IR) data. Unexpectedly, the sonicated samples exhibited an A + V crystal structure with diffraction peaks near 13°,17°, and 19.9°. Furthermore, by using ultrasonication, the addition of EWP, SPI, and WPI raised the samples' water solubility index by 2.97%, 1.05%, and 9.87%, respectively; however, light transmittance decreased by 34.91%, 42.60%, and 25.33%. The agglomerate rate was reduced to zero; ultrasonic treatment also resulted in microparticles that were smaller and exhibited more holes and gaps on their surfaces. Additionally, the samples' breakdown and setback values increased, while their stability and anti-aging qualities decreased. These findings suggest that ultrasound combined with protein treatment significantly enhances the flushing properties of puffed cereal flours and supports their expanded use in the food industry.

Secure transmission of IRS-UAV buffer-aided relaying system with delay constraint

This paper investigates the secure communication between legitimate users in the presence of eavesdroppers, where the Intelligent Reflective Surface-Unmanned Aerial Vehicle (IRS-UAV) and Buffer-Aided (BA) relaying techniques are utilized to enhance secrecy performance. By jointly optimizing the link selection strategy, the UAV position, and the reflection coefficient of the IRS, we aim to maximize the long-term average secrecy rate. Specifically, we propose a novel buffer in/out stabilization scheme based on the Lyapunov framework, which transforms the long-term average secrecy rate maximization problem into two per-slot drift-plus-penalty minimization problems with different link selection factors. The hybrid Particle Swarm Optimization-Artificial Fish Swarm Algorithm (PSO-AFSA) is adopted to optimize the UAV position, and the IRS reflection coefficient optimization problem is solved by iterative optimization in which auxiliary variables and standard convex optimization algorithms are introduced. Finally, the delay constraint is set to ensure the timeliness of information packets. Simulation results demonstrate that our proposed scheme outperforms the comparison schemes in terms of average secrecy rate. Specifically, the addition of BA improves the average secrecy rate by 1.37 bps/Hz, and the continued optimizations of IRS reflection coefficients and UAV positions improve the average secrecy rate by 2.46 bps/Hz and 3.75 bps/Hz, respectively.

Pan-serotype dengue virus inhibitor JNJ-A07 targets NS4A-2K-NS4B interaction with NS2B/NS3 and blocks replication organelle formation

Dengue fever represents a significant medical and socio-economic burden in (sub)tropical regions, yet antivirals for treatment or prophylaxis are lacking. JNJ-A07 was described as highly active against the different genotypes within each serotype of the disease-causing dengue virus (DENV). Based on clustering of resistance mutations it has been assumed to target DENV non-structural protein 4B (NS4B). Using a photoaffinity labeling compound with high structural similarity to JNJ-A07, here we demonstrate binding to NS4B and its precursor NS4A-2K-NS4B. Consistently, we report recruitment of the compound to intracellular sites enriched for these proteins. We further specify the mechanism-of-action of JNJ-A07, which has virtually no effect on viral polyprotein cleavage, but targets the interaction between the NS2B/NS3 protease/helicase complex and the NS4A-2K-NS4B cleavage intermediate. This interaction is functionally linked to de novo formation of vesicle packets (VPs), the sites of DENV RNA replication. JNJ-A07 blocks VPs biogenesis with little effect on established ones. A similar mechanism-of-action was found for another NS4B inhibitor, NITD-688. In summary, we unravel the antiviral mechanism of these NS4B-targeting molecules and show how DENV employs a short-lived cleavage intermediate to carry out an early step of the viral life cycle.

Polarization-Dependent Formation of Extremely Compressed Femtosecond Wave Packets and Supercontinuum Generation in Fused Silica

Previous studies of formation of extremely compressed wave packets during femtosecond filamentation in the region of anomalous group velocity dispersion in solid dielectrics mostly considered the case of linearly polarized laser pulses. However, recent results suggest potential applications of polarization state manipulation for ultrafast laser writing of optical structures in bulk solid-state media. In the present work, evolution of radiation polarization parameters during formation of such extreme wave packets at the pump wavelength of 1900 nm in fused silica is studied numerically on the basis of the carrier-resolved unidirectional pulse propagation equation (UPPE). It was revealed that initial close-to-circular polarization leads to higher intensity of the anti-Stokes wing in the spectrum of the generated supercontinuum. Numerical simulations indicate a complex, space–time variant polarization state, and the resulting spatiotemporal electric field distribution exhibits a strong dependence on the initial polarization of the femtosecond pulse. At the same time, electric field polarization tends to linear one in the region with the highest field strength regardless of the initial parameters. The origin of this behavior is attributed to the properties of the supercontinuum components generation during filament-induced plasma formation.

Deciphering Mineralogical Composition and Clay Diagenesis in Exposed Shales of Jaintiapur, Surma Basin: Unveiling Insights into Burial Diagenesis

Mineralogical analysis of exposed shale samples in the Jaintiapur region was conducted utilizing X-ray diffraction (XRD) techniques. The studied shales are characterized by illite, chlorite, illite/ smectite mixed layer clay, and kaolinite as the predominant clay minerals, with a relatively lower proportion of smectite. Additionally, the non-clay fraction consists mainly of quartz, feldspar, dolomite, and trace amounts of pyrite. Notably, illite and chlorite exhibit prominent abundance within the clay portion, while quartz is the prevailing non-clay mineral. Furthermore, the investigation reveals a notable enrichment of illite and chlorite with the advancement from younger to older stratigraphic formations in the studied shale samples, indicating greater intensity in clay mineral diagenesis in deeper stratigraphic formations. The transition from smectite to illite minerals can release Si, Ca, Fe, and Mg ions, potentially entering nearby sandstones and leading to cementation with quartz, chlorite, and calcite. This process aids in retaining pore water in shales. In this context, overpressure development influenced by clay diagenesis is not primarily due to cementation while undergoing smectite to illite conversion but due to illite packet formation within smectite, reducing shale permeability. During this conversion, interlayer water shifts to free water, causing volume reduction compounded by the low permeability of shale, trapping fluids in the pores. This expansion of pore water, reduced velocity, and increased pore pressure suggest that mineral transformation with burial depth might contribute to overpressure development. However, the observed decline in smectite clays in sediments transitioning from younger to older, culminating in their absence in older shale-dominated formations, explains the presence of diagenetic illite and chlorite. This study underscores the progressive diagenetic transformation in clay mineralogical composition with progressive burial across the sedimentary succession. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 12(2), 2023, P 69-82

A lightweight packet forwarding verification in SDN using sketch

By decoupling the control plane and the data plane, Software Defined Networking (SDN) has reshaped the ossified network architecture and improved the programmability of the network. However, SDN is also susceptible to malicious injection, tampering, dropping and hijacking attacks against forwarding packets, and the SDN architecture cannot perceive the real behavior of switches in the data plane. Packet forwarding verification and exception localization are recognized as effective and promising methods, enabling reliable packet delivery in the data plane and allowing the controller in SDN to identify abnormal links. While existing mechanisms embed the linear-scale cryptographic tags into the packet header space as the transmission path lengthens to realize packet verification and exception localization, which cannot achieve a feasible tradeoff between efficiency and security. Leveraging the central controllability of SDN, we propose a lightweight packet forwarding verification mechanism. This mechanism splits the runtime of a flow into consecutive epochs by address hopping. The switches in the data plane forward packets based on hopping address, collecting the information of packets forwarded in a compact data structure, namely traffic sketch. The controller verifies traffic sketches and localizes exception in the epoch. We further prototype the proposed mechanism based on simulation network. The analysis and experiments demonstrate that the cost of proposed scheme is lower than the similar mechanisms, introducing no more than 9 % additional forwarding delay and less than 8 % throughput degradation.

On the spatio-temporal dynamics of cavitating turbulent shear flow over a microscale backward-facing step: A numerical study

The influence of cavitation on the mean characteristics and unsteady behavior of turbulent separated flows was comprehensively investigated in this study over a microscale backward-facing configuration at the Reynolds number (ReD) of 7440. The computational approach took both compressibility and finite mass transfer (Thermodynamic non-equilibrium) into account, to accurately capture the effects of shock waves, as well as to capture baroclinic phenomena on vortex dynamics within the turbulent separated flow. The compressibility effects were handled by using appropriate equation of states for each phase and for the mixture. Phase-change was considered through a transport equation for the vapor volume fraction, allowing for finite mass transfer contributions. Additionally, a wall adaptive large eddy simulation (LES) approach was utilized for simulating turbulent structures and their effects. The findings reveal that vapor development diminishes the mean growth rate of the shear layer and delays its reattachment to a longer distance from the step. Moreover, analysis of Reynolds normal and shear stresses, as well as the root mean square (RMS) of pressure fluctuations, demonstrates that the formation and collapse of vapor packets significantly influence turbulence decay and production in the second half of the shear layer and reattachment. It was also observed that both mean pressure and pressure fluctuations increased in vicinity of the reattachment region when cavitation was present, which was attributed to the condensation and collapse events. Spectral analysis further indicates the emergence of two dominant low frequency modes, linked to the displacement of the reattachment point. In the presence of cavitation, the frequencies associated with dominant Power Spectral Densities (PSDs) were smaller than those in the absence of cavitation. Additionally, each of these low frequencies corresponded to a specific vapor transport mechanism within the Turbulent Separation Bubble (TSB). Furthermore, it is shown that cavitation leads to a significantly higher spectral energy of high frequency fluctuations within the reattachment region in comparison to the condition where cavitation is absent. This can be attributed to the frequent collapse of bubbles in this region. At the end, we employed Spectral Proper Orthogonal Decomposition (SPOD) for modal analysis. This method offers valuable insights into the coherent structures and associated frequencies that arise in both the presence and absence of cavitation, which provides a deeper understanding of the effect of cavitation on the coherent structures and their dynamics.

Important-Data-Based DoS Attack Mechanism and Resilient H∞ Filter Design for Networked T-S Fuzzy Systems.

This article is concerned with the security problems for networked Takagi-Sugeno (T-S) fuzzy systems with asynchronous premise constraints. The primary objective of this article is twofold. First, a novel important-data-based (IDB) denial-of-service (DoS) attack mechanism is proposed from the perspective of the adversary for the first time to reinforce the destructive effect of the DoS attacks. Different from most existing DoS attack models, the proposed attack mechanism can utilize the information of packets, evaluate the importance degree of packets, and only attack the most "important" ones. As such, a larger system performance degradation can be expected. Second, corresponding to the proposed IDB DoS mechanism, a resilient H∞ fuzzy filter is designed from the defender's point of view to alleviate the negative effect of the attack. Furthermore, since the defender does not know the attack parameter, an algorithm is designed to estimate it. In a word, a unified attack-defense framework is developed in this article for networked T-S fuzzy systems with asynchronous premise constraints. With the help of the Lyapunov functional method, sufficient conditions are successfully established to compute the desired filtering gains and ensure the H∞ performance of the filtering error system. Finally, two examples are exploited to demonstrate the destructiveness of the proposed IDB DoS attack and the usefulness of the developed resilient H∞ filter.

AoI-Aware Resource Scheduling for Industrial IoT with Deep Reinforcement Learning

Effective resource scheduling methods in certain scenarios of Industrial Internet of Things are pivotal. In time-sensitive scenarios, Age of Information is a critical indicator for measuring the freshness of data. This paper considers a densely deployed time-sensitive Industrial Internet of Things scenario. The industrial wireless device transmits data packets to the base station with limited channel resources under the constraints of Age of Information. It is assumed that each device has the capacity to store the packets it generates. The device will discard the data to alleviate the data queue backlog when the Age of Information of the data packet exceeds the threshold. We developed a new system utility equation to represent the scheduling problem and the problem is expressed as a trade-off between minimizing the average Age of Information and maximizing network throughput. Inspired by the success of reinforcement learning in decision-processing problems, we attempt to obtain an optimal scheduling strategy via deep reinforcement learning. In addition, a reward function is constructed to enable the agent to achieve improved convergence results. Compared with the baseline, our proposed algorithm can achieve better system utility and lower Age of Information violation rate.

A Markovian Analysis of an IEEE-802.11 Station with Buffering

The purpose of this paper is to analyze the so-called backoff tech- nique of the IEEE 802.11 protocol with buffers. This protocol rules the trans- missions on a radio channel between nodes (or stations) of a network exchanging packets of information. In contrast to existing models, packets arriving at a sta- tion which in the backoff state are not discarded, but are stored in a buffer of in nite capacity. The backoff state corresponds to the number of time-intervals (mini-slot) that a node must wait before its packet is actually transmitted. As in previous studies, the key point of our analysis hinges on the assumption that the time on the radio channel is viewed as a random succession of trans- mission slots (whose duration corresponds to a packet transmission time) and mini-slots, which stand for the time intervals during which the backoff of the station is decremented. During these mini-slots the channel is idle, which im- plies that there is no packet transmission. These events occur independently with given probabilities, and the external arrivals of messages follow a Pois- son process. The state of a node is represented by a three-dimensional Markov chain in discrete-time, formed by the triple (backoff counter, number of packets at the station, number of transmission attempts). Stability (ergodicity) condi- tions are obtained for an arbitrary station and interpreted in terms of maximum throughput. Several approximations related to these models are also discussed.

Vortex dynamics and boundary layer transition in flow around a rectangular cylinder with different aspect ratios at medium Reynolds number

The numerical investigation focuses on the flow patterns around a rectangular cylinder with three aspect ratios ( $L/D=5$ , $10$ , $15$ ) at a Reynolds number of $1000$ . The study delves into the dynamics of vortices, their associated frequencies, the evolution of the boundary layer and the decay of the wake. Kelvin–Helmholtz (KH) vortices originate from the leading edge (LE) shear layer and transform into hairpin vortices. Specifically, at $L/D=5$ , three KH vortices merge into a single LE vortex. However, at $L/D=10$ and $15$ , two KH vortices combine to form a LE vortex, with the rapid formation of hairpin vortex packets. A fractional harmonic arises due to feedback from the split LE shear layer moving upstream, triggering interaction with the reverse flow. Trailing edge (TE) vortices shed, creating a Kármán-like street in the wake. The intensity of wake oscillation at $L/D=5$ surpasses that in the other two cases. Boundary layer transition occurs after the saturation of disturbance energy for $L/D=10$ and $15$ , but not for $L/D=5$ . The low-frequency disturbances are selected to generate streaks inside the boundary layer. The TE vortex shedding induces the formation of a favourable pressure gradient, accelerating the flow and fostering boundary layer relaminarization. The self-similarity of the velocity defect is observed in all three wakes, accompanied by the decay of disturbance energy. Importantly, the decrease in the shedding frequency of LE (TE) vortices significantly contributes to the overall decay of disturbance energy. This comprehensive exploration provides insights into complex flow phenomena and their underlying dynamics.

An ICN-Based On-Path Computing Resource Scheduling Architecture with User Preference Awareness for Computing Network

The Computing Network is an emerging network paradigm that aims to realize computing resource scheduling through the intrinsic capabilities of the network. However, existing resource scheduling architectures based on conventional TCP/IP networks for the Computing Network suffer from deficiencies in routing flexibility and a lack of user preference awareness, while Information-Centric Networking (ICN) holds the potential to address these issues. ICN inherently supports dynamic routing in scenarios such as multi-homing and mobility due to its routing mechanism that is based on content names rather than host addresses, and it is further enhanced by the integration with Software-Defined Networking (SDN) technologies, which facilitate convenient network-layer route readdressing, thus offering a conducive environment for flexible routing scheduling. Furthermore, ICN introduces novel routing protocols that, compared with the more rigid protocol designs in conventional TCP/IP networks, offer greater flexibility in field usage. This flexibility allows for the incorporation of customized fields, such as “preference”, enabling the perception of user preferences within the network. Therefore, this paper proposes a novel ICN-based on-path computing resource scheduling architecture named IPCRSA. Within this architecture, an original design for computing resource request packet format is developed based on the IPv6 extension header. Additionally, preference-based computing resource scheduling strategies are incorporated, which employ the technique for order preference by similarity to ideal solution (TOPSIS) combined with the entropy weight method, to comprehensively evaluate computing resource nodes and use a roulette-selection algorithm to accomplish the probability selection of destination nodes. Experimental results indicate that, in comparison to alternative scheduling schemes, IPCRSA exhibits significant advantages in enhancing scheduling flexibility, improving scheduling success rates, and catering to diverse user requirements.

A Review of the Mysterious Roles of the Autonomic Ganglia Considered as Deep Intelligence Agency in the United States of the Brain.

For centuries, the brain has been considered a single organ from an anatomical and functional perspective. However, while the cerebral cortex, consisting of many lobes and lobules, generally creates voluntary actions, autonomous parts of the brain also carry out vital activities such as survival, reproduction, and nutrition. The functions of the group of organs that carry out basic vital activities are modulated by autonomous ganglia that work like the deep intelligence networks of the brain. Information and energy packets produced as different molecules in vital organs and sent to the autonomous ganglia are decoded. These packages are then made available for use by cells, tissues, and organs. This deep information, purified and summarized by the autonomic ganglia, is presented to the cerebral cortex after passing through the control of the brainstem and insula. As a result, the entire brain and all the organs under its control decide together what to do. From this conceptual perspective, the brain is a united states group with diferent states under its management; the autonomic ganglia can also be thought of as the brain's deep intelligence networks.

Design and development of prime herder optimization based BiLSTM congestion predictor model in live video streaming

High-quality content for the user in video streaming services depends critically on the ability to predict the continuous user’s quality of experience (QoE). However, continuous QoE prediction has proven challenging due to the complexity imposed by the temporal dependencies in QoE data and the non-linear correlations among QoE impact elements. In this research congestion prediction model is developed using the prime herder optimization-based BiLSTM (PHO-based BiLSTM). The input database is first gathered from the NIMS and darpa99 week 1 database and, the data collection is analyzed and the packet information is extracted after that the extracted features are then fed into the optimized BiLSTM classifier to train the classifier. The classifier’s hyperparameters are successfully tuned by the recommended prime herder optimization, which is made by fusing the herding characteristics of a prime sheepdog and herder optimization. Based on the traffic congestion prediction achievements, at training percentage (TP) 90, the accuracy is 94.81%, specificity is 94.90%, and mean square error (MSE) is 4.91 respectively for D1, similarly based on D2 the accuracy is 95.62%, specificity is 95.96%, and MSE is 0.38 respectively.

FCA-VBN: Fog computing-based authentication scheme for 5G-assisted vehicular blockchain network

Emerging technology known as intelligent transportation systems allows for seamless two-way communication between moving vehicles and stationary infrastructure. Therefore, core security services in a vehicular network consist of encrypting and trusting information packets for intra- and inter-vehicle systems. However, conventional reconciliation methods incur high communication costs and security risks, and channel imperfection causes important extraction disparities. For a 5G-enabled vehicular blockchain network, we suggested a novel fog computing-based authentication approach for the 5G-assisted vehicular blockchain network (FCA-VBN) scheme, which incorporated fog computing and secure authentication to address these issues. The FCA-VBN scheme employs a channel stage response instituted private key extraction technique for terminal key agreement. Using the blockchain’s immutability and memorability, the novelty of this paper is that it shows how the intelligent contract could be utilized to build and issue the link among the fog server and the node’s data through a transaction. When it comes to message authenticity and integrity, conditional privacy protection, and unlinkability, we demonstrated that the proposed FCA-VBN system is safe and secure. We also spoke about how resistant the method is to various assaults. Ultimately, we theoretically analyzed the suggested FCA-VBN scheme’s achievement on a wide range of metrics, such as computation and communication costs and power usage, to arrive at a comprehensive evaluation.

Sequential output information based predictive control for event-triggered networked control systems

In a Networked Control System (NCS), event-triggering is often used to reduce the number of network transmission instances and improve network usage. This paper considers transmitting output data rather than the estimated state for such event-triggered schemes. Output transmission facilitates efficient transmission by reducing the size of the packets sent over the network. However, since the state observer utilizes delayed information output transmission deteriorates system performance and requires improved observer-based prediction schemes for closed-loop control. The performance of a new scheme involving the transmission of sequential output information in a single packet to improve the state observer’s performance is demonstrated in this paper. A sequential observer is constructed that uses successive output information to better observe the states, and a prediction scheme is used to take care of the delays due to event-triggering, network delays, and dropouts. Further, event-triggering is employed in both the feedback and forward channels. The demonstrated efficacy of this sequential approach in the networked control of an inverted pendulum system and a DC motor system emphasizes its potential as a practical solution for improved control in NCSs, particularly in the face of network constraints and communication challenges.