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The September 2023 issue of the IETE Journal of Research features 60 articles covering a wide range of topics in electrical engineering. These include communications, electromagnetics, opto-electronics, computers and computing, control engineering, electronic circuits, devices and components, instrumentation and measurements, medical electronics, and power electronics. The articles discuss ongoing research and recent advancements in these fields, presenting innovative approaches and techniques. Some specific examples include securing sensitive data in communications, improving the performance of OFDM systems through deep learning, antenna design and bandwidth enhancement in electromagnetics, and the application of artificial intelligence in the legal field. The issue also covers topics such as image data security and medical applications of electronics. Each research paper in the issue focuses on a specific problem, proposes a solution or method, and provides results and comparisons to demonstrate its effectiveness. The authors of the papers are experts in their respective fields, with extensive experience and qualifications. [Extracted from the article]

In this paper, we present the MU (multi-user) MIMO (multiple-input & multiple-output) system which is capable to serve the maximum number of users without additional bandwidth or power budget. MIMO systems maximize the channel capability as per the DPC scheme (Dirty Paper Coding). According to DPC, several antennas distributed over the base station are used for serving multiple users simultaneously. Nevertheless, DPC is a comprehensive search algorithm employing sequences of encoded user data for transmitting information to multiple users. Due to increased user density and subsequent transmit antennas in the MU-MIMO system, the exhaustive search (i.e. DPC) becomes cumbersome with the expanded search space domain. This search task would not be completed within a coherence time frame of the packet data communication system. The required objective is to consider this as a cost function for optimization to maximize the realizable sum-rate (throughput) of the MU-MIMO systems. This paper illuminates the joint antenna and user scheduling (JAAU) process with binary artificial bee colony (binary ABC) accomplishing nearly 98–99% of system throughput with the suggestively decreased figure in computation complexity and run time. Binary ABC is observed to have the global optimum value swiftly within the stipulated packet time frame of next-generation wireless data communications. Moreover, binary ABC achieves an appreciable system capacity for MU-MIMO systems as compared with DPC (which attains the maximum system throughput with the highest complexity). These findings are corroborated with exhaustive simulation results presented in this article. [ABSTRACT FROM AUTHOR]

Monitoring and controlling of transmission lines become easier in real time with synchrophasor measurements technology. Phasor Measurement Units (PMUs) provide the time-stamped synchrophasor data of the system buses and transmission lines with a high reporting rate. In this paper, a mathematical model is implemented that allows the simulation of the characteristics of the spread of transmission line switching with load variations. In the model, the transmission lines are divided into three parts defined as susceptible, infected and recovered transmission lines inspired from epidemic model. In this paper, Reliability Test System (RTS − 1979) is divided into three zones to simulate the line switching spread behaviour with load variation for reliability and vulnerability analysis of the synchrophasor smart grid network. The anomaly exists with synchrophasor measuring devices due to cyber intrusion in communication network or failure of devices makes the system observable with the characterization of vulnerable behaviour of transmission lines. [ABSTRACT FROM AUTHOR]

The PI control structure is based on neural network models wherein real power is controlled by an artificial neural network model and reactive power is controlled by a recurrent neural network model. The design was fabricated, and its performance study is compared with simulation study and is reported in the paper. The VSWR performance, peak antenna gain and radiation patterns are presented as function of various antenna parameters from simulation studies and measurements from fabricated antenna. [Extracted from the article]

This paper studies the problem of scheduling control data transmissions from embedded processors to physical systems. For this problem, we propose novel state feedback and output feedback control architectures that are predicated on energy function-based and norm-free event-triggering conditions, where the embedded processor broadcasts a sampled data of its control signal value through a zero-order-hold operator to the physical system when the left side of the event-triggering condition equals to its right side. In this context, the energy function-based feature means that the right sides of the proposed event-triggering conditions involve an energy function as well as its time-derivative to make the selection of these right sides user-adjustable. Furthermore, the norm-free feature means that the left sides of the proposed event-triggering conditions do not depend on signal norms to allow for better control data transmission reduction. System-theoretical analyses of our event-triggered state feedback and output feedback control architectures are shown using the same energy functions and their time-derivatives used in the proposed event-triggering conditions, where illustrative numerical examples are also presented to demonstrate the efficacy of our contributions. To the best of our knowledge, the results given in this paper explore how event-triggering conditions are linked not only to energy functions but also to their time-derivatives for the first time. [ABSTRACT FROM AUTHOR]

For the security of IoT devices, the number and type of devices are generally large, so it is important to collect data efficiently and detect threats in a lightweight way. In this paper, we propose the architecture for malware detection, a method to detect malware using flow information, and a method to decrease the amount of transmission data between the servers in this architecture. We evaluate the performance of malware detection and the amount of data before and after the data reduction. And show that the performance of malware detection is maintained even though the amount of data is reduced. [ABSTRACT FROM AUTHOR]

The overarching contribution of this paper is a novel event-triggered distributed control architecture for multiagent systems that are composed of a team of nonholonomic mobile robots. Specifically, the robot dynamics are first feedback linearised to equivalently represent each robot with double integrator dynamics and the event-triggering law is then presented. This law is characterised by being decentralised (depending only on own signals of a robot), norm-free (independent of distances for reducing robot-to-robot data transmissions), and adaptive (estimating signals without using global information). Moreover, its system-theo- retical analysis is provided, which holds for both the sampled data exchange method and the solution-predictor curve-based data exchange method. In contrast to the well-studied sampled data exchange, the solution-predictor curve method further reduces robot-to-robot data transmissions by making each agent to store a generic form of this curve and exchange its parameters when an event occurs for approximating the solution trajectory of each robot. Finally, an illustrative numerical example is included to demonstrate the overall architecture. [ABSTRACT FROM AUTHOR]

The motivation to make information more accessible in data communication – physically to the senses and culturally to different audiences – has led designers to experiment, for example, in data physicalization and data sonification. Experimentation overlapping data communication and the performance arts suggests another practice is emerging. Calling it data embodiment, I define the term as a communicative and artistic method that approaches the body as a choreographic medium to physicalize and perform abstract data. The intent of this paper is to sufficiently delineate the space where bodily movement and abstract data have begun to intermingle across several milieu under the concept. The paper begins by contextualizing data embodiment in design, then continues by observing how choreographers have previously approached dance as data, and finishes with a case study where an environmental migration dataset is choreographed. A brief section on human-centered datasets and the surveillant technologies that produce them peppers the overarching discussion on bodily movement and abstract data. By reconstituting data in time and space, especially in the context of performance, otherwise sterile datasets are shown to become more physically and culturally accessible as well as aesthetically expressive. [ABSTRACT FROM AUTHOR]

A key component of a digital twin is the monitored data, communicated from the physical system to the virtual representation, for visualization and simulation. Yet little attention has been paid to the practicalities of working with live-streamed data. Strategies are required for providing continuous access and storage, for processing data of indeterminate quality, and for ensuring long-term sustainability of data communication systems. This paper describes design of the data communication infrastructure, 3D visualization and data interpretation tools, and model development and implementation, for an operational digital twin. Conclusions are drawn pertaining to the informativeness of streamed data, key for successful digital twin development and operation. The paper highlights the need for further research into techniques for ensuring data quality and forecasting efficacy. Digital twins operated commercially are rarely described in detail; the discussion provides a basis for future collaborative development of a consistent operational and interactive framework. [ABSTRACT FROM AUTHOR]

The interplanetary File system (IPFS) provides data communication using plaintext over distributed and decentralized systems. Up till now, the security of data has mostly been established using keys. To facilitate classified data communication within a Closed User Group (CUG), services of IPFS private swarm are required to render additional content encryption. Currently, there is no inherent security built into IPFS. This paper presents an application DMaya on IPFS to provide keyless encryption on IPFS based on the Quasigroup-based Secret Sharing Scheme (QSS). IPFS is used as a storage medium, irrespective of the nature of data. Data security in decentralized mode with IPFS is provided with DMaya. The classified data of all types (i.e. video data, audio data, text data, and image data) when subjected to DMaya application, are fragmented into smaller fragments then processed by the probabilistic Quasigroup-based Secret Sharing (QSS) Scheme. DMaya keyless encryption generates the metadata tag file at the source node. The recipient node within the same private IPFS swarm, on receipt of metadata tag file reconstructs the original data with DMaya application. [ABSTRACT FROM AUTHOR]

This paper investigates the secure state estimation problem of the cyber-physical systems (CPSs) in the presence of malicious attacks. Considering the destructiveness and stealthiness of the attacker, a novel stochastic transmission scheme, in which the repeater generates transmission data by randomly combining some measurement values, is proposed to ensure the effectiveness of the attack detector. A filter equipped with the $ \chi ^2 $ χ 2 detector and the stochastic transmission scheme is proposed to conduct the secure state estimation. The attack probability condition of the estimation error being mean-square bounded is given, which indicates that stochastic transmission scheme has a limited effect on the filter. Some numerical simulations are given to illustrate the effectiveness of the proposed transmission scheme. [ABSTRACT FROM AUTHOR]

The problem which is concerned with filter-based neural control for switched uncertain nonlinear systems with incomplete measurement is studied in this paper. Filters are used to estimate unknown states, while neural networks approximate unknown functions. Data loss, saturation and other problems often occur during data transmission. An appropriate control law is designed by a backstepping method to solve this problem. Through using the average dwell time, it is proved that the switching system tends to be stable in a certain time. The analysis of probabilistic stability is also carried out to ensure that the system can achieve uniformly ultimately boundedness. Finally, the effectiveness of the previous design is proved by simulation. [ABSTRACT FROM AUTHOR]

Over the past decade, public blockchains have emerged as innovative, technology platforms capable of highly secure and sophisticated peer-to-peer online transmission of data between unknown parties. However, public blockchains challenge traditional regulatory models that assume centralised, single points of control facilitated via established intermediaries. In such a context, the present paper analyses the potential liability attaching to blockchain participants and considers how privacy laws apply to blockchain transactions, given the immutable nature of blockchain records. The paper then recommends reforms to strengthen blockchain regulation, including statutory recognition of fiduciary obligations for elite developers with super-user access to allow recourse for loss resulting from hard forks. A 'hard fork' is a radical change to a network's protocol that leads to formerly valid blocks and transactions becoming invalid or vice-versa. Finally, the paper considers changes to privacy laws to permit ongoing consent and cross-border disclosure of data to accommodate blockchain operations. [ABSTRACT FROM AUTHOR]

The synchronisation problem is studied for master–slave memristive neural networks (MNNs) in this paper. For alleviating the burden of communication bandwidth, a novel event-triggered scheme of data transmission is designed in the sensor-to-controller (S-C) channel. To deal with the unknown parameters and disturbances of master–slave MNNs, the adaptive controller is designed with the system states of triggering instants. Different from existing results about event-triggered adaptive control (ETAC) for MNNs, in which the event-triggered mechanism (ETM) is installed in the controller-to-actuator (C-A) channel, the event-triggered scheme in this paper is designed between the sensor and the controller, so the information flow of S-C channel is discontinuous. The adaptive laws can only use discrete-time system states transmitted at triggering instants to update control gains in this paper. By means of the Lyapunov methods, adaptive control theories and event-triggered techniques, sufficient conditions for synchronisation and quasi-synchronisation are obtained. At the same time, the designed ETM can avoid Zeno behaviour theoretically. Finally, the validity of the obtained results is shown by two simulation examples. [ABSTRACT FROM AUTHOR]

We review the latest developments in Fiber-optic Telecommunications and Networks presented at OFC 2023 and compare the progress accomplished in the previous years. Topics of interest this year and discussed in this review include Long Haul and Intra Data Centers communications, Optical switches, sensors in submarine communications, some invited presentations (alas without papers such as in Optical Computers!), Secure Communications through Quantum effects, and Passive Optical Networks, PONs [ABSTRACT FROM AUTHOR]

The Multiple-Input Multiple-Output (MIMO) scheme uses multiple antenna configurations to achieve high throughput data transmission in current communication systems. The new generation wireless communication system considers using generalised frequency division multiplexing (GFDM) due to its advantages such as lower out-of-band (OOB) emission and peak-to-average power ratio (PAPR), etc. However, inter-symbol interference (ISI) and inter-carrier interference (ICI) occur due to GFDM utilises the pulse shaping filter. This paper proposes a low-complexity joint minimum mean square error (MMSE) receiver to suppress ISI, ICI, and multi-user interference (MUI) for multi-user MIMO-GFDM (MU-MIMO-GFDM) system. The conventional approach is to design the equalisation and the GFDM demodulation separately. This paper jointly designs the equalisation and demodulation process that significantly reduces the complexity and enhances the error rate performance. This paper also analyzes the closed-form expression and two low-complexity methods for the proposed receiver. The simulations demonstrate the effectiveness of the proposed low-complexity multi-user MIMO-GFDM receivers. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to contribute to the scientific debate on Quality 4.0 by exploring the main theoretical themes underpinning the Quality 4.0 model and how the model may be developed. An exploratory sequential mixed methods design was employed to study two different samples of Italian manufacturing companies over two phases. For each sample, a different questionnaire was distributed to the companies' quality managers. As a result, eleven themes were elicited and tested. These themes are related to model development, top management, process mapping, data collection and integration with the enterprise resource planning system, use of artificial intelligence software, machine-to-machine data communication, product identification and traceability, document control and digital skills for quality control staff. A theoretical model for Q4.0 is proposed that encapsulates eleven themes of Q4.0 across three categories- people, process, and technology. Results could be particularly helpful for practitioners who may use them as a guideline for implementing and developing Quality 4.0 in a typical Industry 4.0 environment. [ABSTRACT FROM AUTHOR]

WSN consists of many sensors, they need high throughput and network lifetime to get involved in communication. Duty Cycle is a key factor in sensor nodes to maintain sleep, active condition in the presence of overhearing, collisions of packets while data transmission between sensor nodes. The key challenge of sensor nodes is to attain high energy efficiency, throughput and low End-End Delay. This paper presents several of existing approaches for MAC protocol. They are (1) Synchronization between nodes (2) Mathematical Analysis (3) TDMA based MAC and (4) Cross-Layer Design. We proposed a new method for MAC protocol with variable duty cycle. Neighboring nodes follow same duty cycle and same active time. Far away nodes doesn't maintain same duty cycle, hence their active time is not same. The duty cycle is maintained in synchronous way and adaptive manner among the nodes within the network. In this paper, a conventional MAC and proposed MAC are simulated using NS-2.35. Variable duty cycle approach in the proposed MAC with sleep and idle states for the nodes yields better throughput and energy efficiency with respect to other conventional technique. These results validate that the proposed variable DC-MAC is feasible for Wireless Sensor Network applications. [ABSTRACT FROM AUTHOR]

In order to improve the effect of agricultural data collection and transmission, based on the technology adopted by the mainstream agricultural environmental information monitoring system on the market, this paper uses game theory to innovatively improve the algorithm mechanism of wireless sensor nodes, optimise the clustering structure and routing method of wireless sensor networks, design a remote monitoring platform for field farm information and finally build a complete agricultural information monitoring system. Moreover, taking the temperature and humidity sensor as an example, this paper improves the parameters on the basis of testing the various performance of the sensor, and develops the software of the main chip on the basis of the improved node, and completes the driver design of the sensor. In addition, this paper constructs a wireless sensor network data transmission model based on game theory, and combines simulation experiments to conduct experimental research on the system model constructed in this paper. From the test results, it can be seen that the model constructed in this paper has a better effect. [ABSTRACT FROM AUTHOR]

The ability to predict performance of manufacturing equipment during early stages of process planning is vital for improving efficiency of manufacturing processes. In the metal cutting industry, measurement of machining performance is usually carried out by collecting machine-monitoring data that record the machine tool’s actions (e.g. coordinates of axis location and power consumption). Understanding the impacts of process planning decisions is central to the enhancement of the machining performance. However, current methodologies lack the necessary models and tools to predict impacts of process planning decisions on the machining performance. This paper presents the development of a virtual machining model (calledSTEP2Mmodel) that generates machine-monitoring data from process planning data. TheSTEP2Mmodel builds upon a physical model-based analysis for the sources of energy on a machine tool, and adopts STEP-NC and MTConnect standardised interfaces to represent process planning and machine-monitoring data. We have developed a prototype system for 2-axis turning operation and validated the system by conducting an experiment using a Computer Numerical Control lathe. The virtual machining model presented in this paper enables process planners to analyse machining performance through virtual measurement and to perform interoperable data communication through standardised interfaces. [ABSTRACT FROM PUBLISHER]

This paper concerns an event-triggered control for uncertain linear systems with process time-varying delays. An adaptive event trigger (AET) is employed for reducing the data transmission amount from the sensor to the controller. Because a positive constant and a positive variable are simultaneously involved in the AET, the AET condition may be difficult to be violated and the data transmission amount may be reduced. A discrete-time feedback control law is employed to guarantee the uniformly ultimately bounded (UUB) of the closed-loop systems. If the gain matrix of the time-delayed state is compromised with the sufficient stability condition, the desired stability can be always achieved regardless of the time-varying delays. In addition, the bound region can be specified by regulating the threshold of the AET. It is proved that the unwanted Zeno phenomena is naturally excluded since the minimal event-triggered time-interval of the AET is a positive real number. Furthermore, the maximal event-triggered time interval can also be quantitatively approximated. A numerical example is provided to demonstrate the effectiveness of the proposed method, and the influences of the AET threshold and time delay are discussed as well. [ABSTRACT FROM AUTHOR]

This paper studies the iterative learning fault-tolerant control (ILFTC) problem for networked batch processes with event-triggered transmission strategy and data dropouts. During the transmission of input signal, the event-triggered mechanism is adopted to reduce the number of updated data items. The data dropouts are assumed to obey the Bernoulli random binary distribution. The objective of this paper is to design a state feedback controller such that the system is fault-tolerant and satisfies the robust performance requirement. By combining 2D stochastic system theory and linear matrix inequality (LMI) technique, some sufficient conditions are given to ensure the existence of the designed controller. Finally, an example of nozzle pressure control is utilized to verify the availability of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the distributed filtering problem for a class of time-varying systems subject to deception attacks and event-triggering protocols. Due to the bandwidth limitation, an event-triggered communication strategy is adopted to alleviate the data transmission pressure in the algorithm implementation process. The partial nodes-based filtering problem is considered, where only a partial of nodes can measure the information of the plant. Meanwhile, the measurement information possibly suffers the deception attacks in the transmission process. Sufficient conditions can be established such that the error dynamics satisfies the prescribed average performance constraints. The parameters of designed filters can be calculated by solving a series of recursive linear matrix inequalities. A simulation example is presented to demonstrate the effectiveness of the proposed filtering method in this paper. [ABSTRACT FROM AUTHOR]

In the last decades, space activities have become more automated and digitized due to the technological development. As such, it is crucial to consider cyberspace and its risks to guarantee safety, security, and long-term sustainability of space activities, as well as to ensure that activities in outer space are carried out for the benefit of humankind. The paper assumes that both areas are global commons and numerous interactions exist between them, notably in terms of cybersecurity. Indeed, there is an increasing risk of attack against satellites, including interferences, jamming, and hacking, which reveals that the security aspects of satellite systems and data transmission cannot be overlooked, and the risk of cyberwarfare is real. Cybersecurity regulations at international, regional, and national levels to determine the potential elements applicable to space activities are examined in this paper. The paper stresses the need to bring together actors involved in the domain of cyber and in space activities with the aim to implement a structured, appropriated, and responsive regulatory framework to cyberthreats by considering the interdependence between these two areas. In this regard, it is argued that a compartmentalized approach with relation to cyber and outer space should be avoided. [ABSTRACT FROM AUTHOR]

High-quality airborne display benefits pilots of making correct interpretation and operation in time, and avoids from moving body due to the unclear transmission of flight data which may lead to flying risk. A directional modulated light-emitting technology based on airborne display is proposed in this paper which can be used on Diamond DA42 New Generation aircraft. Using the proposed technology, a composite optical film with micro-structure is designed which can realise the redistribution of light intensity according to the viewing demand. A collimated display is introduced to reduce the colour shift. When the optical film is attached on a collimated display, the incident light of small viewing angles can be directionally modulated and concentrated to the large viewing angles which are just effective pilot and co-pilot viewing angles. The calculation results show that the brightness of airborne display on two pilots' viewing angles can be increased by 38.9% and 58.7% respectively after using the proposed technology. Meanwhile, the emergent angles from the collimated display are smaller than both two pilots' viewing angles, so the proposed optical film is beneficial to reduce the colour shift and resulting in a better display quality. [ABSTRACT FROM AUTHOR]

The 5G networks which have begun to spread worldwide are expected to contribute to an increase in the use of Internet of Things (IoT) technologies and applications, which require massive connectivity, security, and ultra-low latency. However, it is known that 5G alone is not sufficient for many IoT devices to exchange various types of data in real time. These constraints promote the emergence of 6G technologies which can support higher network capacity, lower latency, and faster data transmission than 5G networks. To understand the current trends in 6G research and their relation to IoT, this paper introduces the main drivers of 6G technology, describes 6G's enabling technologies, summarizes current 6G research, and introduces the possible applications of 6G to IoT technologies and service areas. [ABSTRACT FROM AUTHOR]

In this paper, the proportional–integral-type estimator design problem is studied for recurrent neural networks under the encoding–decoding communication mechanism. In the process of the measurement data transmission, an encoding–decoding mechanism is introduced to improve the security of the network by encrypting the measurement data. The purpose of this paper is to design a proportional–integral-type estimation algorithm such that the estimation error dynamics is exponentially ultimately bounded in mean square. First, a sufficient condition is obtained for the existence of the desired estimator. Then, the parameters of the estimator are obtained by solving certain matrix inequality. Finally, a simulation example is given to verify the effectiveness of the designed estimation algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the set-membership filtering problem is investigated for a class of polytopic uncertain two-dimensional shift-varying systems with delays and sensor saturation. The measurement information is transmitted between the sensors and the filter through a shared communication network. To avoid data congestions, the Round-Robin (R-R) protocol is employed to regulate the data transmission order. This paper aims to design a robust set-membership filter such that the real system states are always contained in the state estimate ellipsoid in the presence of the state delays, the sensor saturation, the parameter uncertainties, the R-R protocol and the unknown-but-bounded external perturbations. By using the mathematical induction, sufficient condition for the existence of the desired robust set-membership filter is given in the form of recursive linear matrix inequalities, and a convex optimisation method is also proposed to determine the optimal state estimation ellipsoid in the trace sense. One numerical example is also given to illustrate effectiveness of the proposed filtering strategy. [ABSTRACT FROM AUTHOR]

With the developments of wireless data communication and network technology, time-delays are widely found in nowadays' control systems, e.g. networked control systems, mobile robot systems, and multi-agent systems. Predictor-based control is an effective method dealing with long time-delays because it can generally lead to a delay-free closed-loop system by introducing a prediction for future states. Recently, various predictor-based control methods have been developed for numerous control systems subject to different time-delays, which motivates this survey. This paper presents a comprehensive review of the up-to-date results on the predictor-based control of time-delay systems. Firstly, the ordinary differential equation-based approaches for designing and analysing predictor-based controllers are summarised. Secondly, one reports an alternative method of predictor-based control, in which the systems/controllers are understood in the sense of partial differential equations. Next, several integration-free predictor-based controllers are introduced: by abandoning the infinite-dimensional integral terms, the control laws become easier to realise in practice. Hereafter, the paper discusses the real-time implementations and the practical applications of predictor-based control methods to several particular control systems. Finally, this paper suggests some new trends of predictor-based control for future research. [ABSTRACT FROM AUTHOR]

In this paper, the networked model predictive control (MPC) for the linear system with the arbitrary bounded delays and packet losses during the data transmission and processing is studied. Since MPC requires the prediction of the input and state within the two links (i.e. sensor to controller and controller to actuator links), the closed-loop model is constructed by considering all possible transmission statuses. The obtained controller generalises the results of Kothare et al. (1996), in specifying the system model, physical constraints and closed-loop stability, while guaranteeing the recursive feasibility of the optimisation problem. Two simulations are implemented to show the effectiveness of the presented networked MPC approach. [ABSTRACT FROM AUTHOR]

The standard communication protocols transfer big data over the internet. However, the challenge lies while sharing the massive amount of genomics data quickly over limited bandwidth networks. Managed File Transfer (MFT) that uses File Transfer Protocol Secure (FTPS) or Secure Shell File Transfer Protocol (SFTP) is a scalable and secure alternative for the purpose. This paper proposes a framework consisting of a Variable-length Genomic Binary Encoding (VGBE) scheme and a hybrid Gated Recurrent Unit-Convolutional Neural Network model (GRU-CNN). The Method exploits Managed File Transfer to reduce the bit size before transmission and increases the bit rate during the transmission of genomics data. Consequently, the method ensures a minimum number of bits per word and less latency. The methodology is tested on various communication protocols. It is validated in terms of performance metrics viz. transfer rate and the size of transferred data using diverse benchmark datasets such as protein sequences and human reference genome taken from the University of California Santa Cruz (UCSC) and National Center for Biotechnology Information (NCBI), respectively. Furthermore, simulation and implementation results show that the model is 98% faster, has 96% less data size, and is more secure than standard communication protocols. Thus, the proposed method is an efficient and secure genomics data transfer method using deep learning techniques. [ABSTRACT FROM AUTHOR]

In this research work, the authors propose an error constrained data transmission approach using non-orthogonal multiple access (NOMA) protocol with hybrid automatic repeat request (HARQ) and different packet combining schemes. In this proposed work, the transmitter simultaneously transmits two data packets to the users (UEs) by considering the superposition coding technique in the power domain. The decoding scheme of the receiver changes according to the message decoding status in the previous rounds. This combined protocol has the capability of realizing ultra-reliability, error correction power in high error prone wireless links. The receiver adopts successive interference cancelation (SIC) to decode its own packet. Retransmission process is performed when the data is erroneously received by the destination and the receiver corrects the error by applying HARQ with Packet Combining (HARQ-PC) and HARQ with Aggressive Packet Combining (HARQ-APC) schemes. This paper analyzes the data rates, outage probabilities and bit error rates of UEs for downlink NOMA systems with respect to the transmit power using some basic parameters. The proposed schemes can greatly outperform the conventional NOMA with HARQ (NOMA-HARQ) in terms of data rates, outage probability and bit error rate in dynamic wireless channels. [ABSTRACT FROM AUTHOR]

In this paper, we consider the energy-to-peak filtering issue for a class of linear parameter-varying (LPV) systems with time delays subject to certain communication regulation under which only one sensor is allowed to transmit its measurement data at each transmission instant. The data communication is regulated by the random access protocol (RAP) for the purpose of avoiding data collisions. The main purpose of this paper is to design an LPV filter such that the resultant filtering error system is asymptotically stable and also satisfies the prescribed l 2 - l ∞ performance in the mean square. Taking into account both the LPV nature and the possible gain perturbations, a parameter-dependent resilient filter is constructed according to the plant dynamics and scheduling behaviour of the RAP. The desired filter gain matrices are obtained by solving a set of linear matrix inequalities. Finally, a simulation example is given to validate the effectiveness and correctness of the filter design scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of distributed fusion over sensor networks with probabilistic constraints and stochastic perturbations. In order to save the bandwidth resources, a new event-triggering mechanism (ETM), called torus-event-triggering mechanism (TETM), is utilised for data transmission. Compared with the traditional ETMs, the TETM has two thresholds, which will not only discard the sampling data smaller than the lower threshold but also hold back the packet larger than the upper threshold. The main purpose of this paper is to design a time-varying distributed fusion filter such that: (1) the probability of the filtering error falling in a given ellipsoid domain is greater than a specified value and (2) the ellipsoidal set is minimised in the sense of matrix norm at each time point. To achieve the above-mentioned purpose, sufficient conditions are given to obtain the global fusion with the help of the recursive linear matrix inequality technique. The desired local filter parameters are then computed by solving an optimisation problem with some inequality constraints. Finally, a numerical simulation is given to illustrate the effectiveness and applicability of the proposed distributed fusion strategy. [ABSTRACT FROM AUTHOR]

Wireless sensor network is the network of tiny size of sensor nodes. These sensor nodes have sensing capability and transmit the sensed information to sink node. If the energy of sensor nodes is not utilised properly, it results in performance degradation of the network. Sleep scheduling approach and cooperative communication techniques can be employed to enhance the network performance. Cooperative communication follows the relay-based transmission. The nodes turn its radio sleep and awake in sleep scheduling approaches. This paper considers the merits of both techniques and proposes the sleep scheduling-based cooperative data transmission approach for WSN. In this approach, optimal number of virtual cluster heads are calculated by the sink node according to the number of nodes and area of interest. The real cluster head is decided based on the distance and energy of the sensor nodes from the virtual cluster head. The node is paired with each other and follows the sleep scheduling approach. Further, the energy-efficient relay selection and data transmission according to cooperative technique improves the network performance. The simulation analysis shows that the proposed routing protocol outperforms the related existing routing protocols. [ABSTRACT FROM AUTHOR]

This paper optimizes a ground replenishment strategy for large-scale LEO satellite constellations, aiming for ensuring high economic efficiency and performance requirements. Firstly, the uncertainties of influential elements are analyzed and satellite lifetime distributions are estimated to determine satellite operating statuses. Secondly, satellite statuses are used for obtaining real-time constellation status and simulating data package transmission paths. Performance degradation function is then derived by selecting time delay as the key performance. To confront with the performance degradation, an optimization model of ground replenishment strategy is established with the objective of minimizing the overall replenishment cost under the time delay and loading capacity constraints. The model is solved by a Dichotomous-domain algorithm. Finally, a case study of a large-scale STARLINK constellation is adopted to validate the effectiveness of the model and sensitivity analyses are conducted to verify its robustness. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) plays an increasingly vital role in numerous domains across our modern landscape. It presents a plethora of innovative solutions that not only streamline human tasks but also enhance overall quality of life. Within this dynamic IoT framework, this paper hones in on the data transfer aspect, highlighting the pivotal role of Light Fidelity (Li-Fi) technology. Li-Fi represents a wireless data transmission methodology harnessing light as its medium. Our research endeavours culminate in the development of a tangible hardware prototype, incorporating Li-Fi technology alongside various complementary components. This bespoke prototype serves as an invaluable instrument for data transmission, harnessing the potential of light to facilitate seamless information exchange. Furthermore, to interface with this system, a dedicated mobile application has been meticulously crafted, offering users a user-friendly and efficient means of data transmission and communication. [ABSTRACT FROM AUTHOR]

The realm of vehicular safety applications driven by communication has surfaced as a paramount approach for elevating road safety standards. The adoption of Vehicular VLC (V-VLC) is rooted in its multifaceted advantages, making it a preferred choice for integrating both illumination and data transmission. Beyond its highly secure attributes, V-VLC boasts virtues such as demonstrating low complexity, and ensuring immunity to radio frequency (RF) interference. The core premise of this study revolves around the proposition of a novel system that synergistically integrates NOMA into V-VLC networks to amplify spectral efficiency, harnesses beamforming techniques to bolster Signal-to-Noise Ratio (SNR), and leverages Successive Interference Cancellation (SIC) to curtail interference. An exhaustive analysis of this system configuration is provided, accompanied by the derivation of a precise Signal-to-Interference-plus-Noise Ratio (SINR) expression tailored to the proposed scenario. This paper not only delves into the nuanced aspects of NOMA performance at the receiver but also delves into critical dimensions such as the influence of transmitter-receiver distance, elevation disparity between transmitter and receiver, and the impact of diverse channel conditions on received power and BER VS. Eb/No for different MIMO configurations. [ABSTRACT FROM AUTHOR]

This paper proposes an optimised Medium Access Control (MAC) protocol to minimise the number of channel access collisions and to improve the bandwidth efficiency of IoT-based Wireless Body Area Networks (WBANs). The frame structure of the proposed MAC protocol consists of three different phases, namely Contention Phase (CP), Transmission Phase (TP), and Inactive Phase (IP). During CP, the proposed protocol prioritises the life-sensitive data. Based on allocated priority, the communicating sensor nodes (SNs) compete for channel access. During TP, the successful SNs transmit their data. We use TDMA mechanism for data transmission and Spider Monkey Optimisation (SMO) technique to improve the bandwidth efficiency of the system by selecting the best possible TDMA time slot according to the data packet size of the SNs. During IP, the SNs go into sleep mode to save energy. We simulate the scenario on MATLAB simulator. The simulation results show that the proposed SMO-MAC improves the throughput by 22.23%, 14.00%, and 17.62%, residual energy by 60.76%, 81.17%, and 124.34%, communication reliability by 70.32%, 52.60%, and 52.60%, and data packet transmission delay by 80.74%, 70.10%, and 77.40% as compared to DRT-MAC, PSO-MAC, and GA-MAC, respectively. [ABSTRACT FROM AUTHOR]

The networking field plays a major role and developed significantly over the past decades. The identification of best route in Mobile Ad hoc Networks (MANETs) is a complex problem in the multipath routing method. Besides, multipath discovery is regarded as the other difficult task for improving the existence of the network. Through optimal route discovery, the routing protocol considers several parameters like link failures, topological variations, obstacles, and extended power. In this paper, based on optimal route discovery, a novel Fuzzy Beluga Whale Optimization (FBWO) is proposed for presenting effective routing and enhanced link stability. The Beluga Whale Optimization (BWO) algorithm determines multiple routes in the network for communicating data packets to their destination. However, the discovered routes may be susceptible to link failures due to the complete energy exhaustion of nodes during continuous data transmission. Therefore, the stability of links is assured by evaluating link stability indicators namely probabilistic link reliable time, link expiration time, residual battery power, link received signal strength, and link packet error rate. Moreover, optimal routes in the network are established using a fuzzy rule system by adopting fuzzy rules. Thus, the proposed FBWO approach maximizes the overall performance of the network by establishing optimal routes to broadcast packets along with enhanced link stability and signal strength. The experimental results manifest the FBWO model and achieve superior accuracy in terms of all measures than other existing methods. [ABSTRACT FROM AUTHOR]

There are interesting papers in this issue covering topics ranging from sensors, communication engineering, IoT, Image processing and RADARs. Through simulations, the authors demonstrate that the performance metrics of D4across6 are similar to those of native IPv6 and IPv4 protocols and the performance of D4across6 is better than that of all (A+P), DS-Lite and 4rd protocols. To achieve a high data rate in communication systems, resource allocation and subcarrier assignment (RASA) decides the achievable data rate and this requires sophisticated signal processing algorithms. [Extracted from the article]

Information technology acts an important role in gathering, transmitting with executing data from areas of disaster-prone such as the battlefield and international borders. In addition to the country's security, the soldier needs protection by defending himself with advanced weapons such as a bomb detector. This paper provides the capability to track the whereabouts and health of soldiers who have been lost or injured on the battlefield. It assists in reducing the time, searching and rescuing operation efforts of the military control room. This paper implements a system for health-condition monitoring that sends soldiers' health parameters, such as the electrocardiogram (ECG), blood oxygen level, pulse rate, and temperature, to the control room via a Mobile Ad hoc Network (MANET). Body parameters are sensed utilizing various body sensors fixed to the bodies of soldiers. The body parameters are broadcasted to the control room via MANET devices at the path. To preserve the health parameters data of soldiers from enemies while data transmission, this paper also proposes a cryptographic ensemble approach. This approach combines Symmetric Key Encryption, and Identity Based Encryption (IBE) with Identity Based Signature (IBS). The experimental result shows proposed cryptographic ensemble provides high security compared with existing MANET security algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a novel architecture of femto power-delay super threshold voltage level shifter (LS) for network on-chip voltage control, developed using feedback topology for error aware interconnections data transmission. The proposed LS utilises eight MOS transistors with low aspect ratios for level up or level down. The developed LS can shift as low as 0.12–1.25 V with a tremendous reduction in delay and power consumption. Implemented in 65 nm CMOS technology, the post-layout simulation substantiates the achievement of voltage translation. The proposed LS incurs energy per cycle of 44 fJ during up shift; the average of level up and level down static power consumption is 3.61 nW, while VDDL is 0.3 V and VDDH is 1.2 V at a frequency of 1 MHz. The layout area of the proposed LS is 3.21 µm × 2.13 µm. [ABSTRACT FROM AUTHOR]

In this paper, the distributed mixed H 2 / H ∞ fusion filter design problem is investigated for a class of cyber-physical systems subject to non-ideal measurements under Round-Robin protocol. To save the limited communication resources, the Round-Robin protocol is employed to schedule the data transmissions from the sensors to the remote filters. The measurement is imperfect by taking into account the noises, the random saturations, nonlinearity perturbations and packet dropouts. The objective of this study is to propose a desired fusion filtering method that ensures the prescribed performance constraints on both the local and fusion filtering error dynamics. With the aid of Lyapunov function and stochastic analysis technique, a sufficient condition is established to guarantee the mixed H 2 / H ∞ performance index for the local filtering error systems, and then the filter parameter matrices are derived by resorting to the solutions to some matrix inequalities. Subsequently, on the basis of the obtained local state estimates, the proper fusion parameters are acquired by solving a convex optimisation problem. Finally, a numerical example is provided to demonstrate the effectiveness of the designed fusion filter. [ABSTRACT FROM AUTHOR]

The basic idea of this letter is concerned with the large Peak-to-Average Power Ratio (PAPR) problem in multi-carrier Under-Water Acoustic (UWA) communication systems that implement Orthogonal Frequency Division Multiplexing (OFDM). A Tangent Rooting (TanhR) companding technique is presented in this paper to reduce the PAPR in UWA communication systems. This technique achieves a noticeable reduction of the PAPR in UWA systems, while maintaining a good Bit Error Rate (BER) performance. Channel equalisation with Linear Minimum Mean Square Error (LMMSE) and Zero-Forcing (ZF) equalisers is considered in this paper. Simulation results ensure superiority of the proposed technique compared to the Selected Mapping (SLM) and the Partial Transmit Sequence (PTS) techniques from both the PAPR and BER perspectives. [ABSTRACT FROM AUTHOR]

Based on the increasing demands of transportation development, the concept of an Intelligent Transportation System (ITS) has received increasing attention in both academic and industry arenas. It integrates information, communications, computers and other technologies, and applies them in the field of transportation to build an integrated system of people, roads and vehicles by utilizing advanced data communication technologies. It can establish a large, fully functioning, real-time, accurate and efficient transportation management system. Intelligent transportation systems shift the focus from road managers to road users. In order to achieve this purpose, intelligent transportation systems use advanced technology to provide drivers with convenient information to help reduce traffic congestion and to increase available road capacity. This special issue is dedicated to exploring the most recent advances in intelligent transportation systems and big data based on intelligent technology. [ABSTRACT FROM AUTHOR]

In this paper, a tapered waveguide design was used in mode division multiplexing (MDM) as a mode converter. It was investigated to be used for switching purposes in short haul communication in a data center. This paper shows the results of a Gaussian beam being converted into transverse modes and vice versa. It also shows the multiplexed version of the modes being converted into a specific target mode. There are two and three combinations of multiplexed modes in the tapered waveguide design, with modes computed as well as converted into targeted modes. The reason for this experiment is to accomplish the goal of replacing opto-electronic switches at data centers into an all-optical switching mechanism. Therefore, this design will enable the processing of large amounts of data using optical switching apparatus by creating additional data channels. It results in providing an all-optical mode conversion switch that incorporates high-speed routing of data from one server into another data center. [ABSTRACT FROM AUTHOR]

Medical data transmission is a major challenge in wireless communication to preserve their integrity and coherence. As the transmission takes place at high data rate, the complexity and throughput of the system, pertaining to the fetal ECG signal, is crucial. In addition to the accumulation of noises in the channel, the observation of fetal ECG signal, using diagnostic devices, also provides additive noise, thereby reducing the quality of the transmitted signal. The major motive of this paper is to demarcate the fetal ECG signal from noise at early stages of transmission using Chambolle-Pock based hybridized classifiers. This technique provides sensitivity of 91.1% followed by performance validation of Error Detection and correction adders for different decoder architectures in transceiver. Thereby area and power reduction of 86.3% and 91.1% is achieved. The simulations are carried out with MIT-BIH Arrhythmia using simulation tools, such as MATLAB 2013b, ModelSim 10.0b, and Cadence Virtuoso under 90 nm on over 200 data sets. [ABSTRACT FROM AUTHOR]

Facial recognition technology is a state-of-the-art digital tool widely used by private and public entities. Its benefits are notable, but the challenges that it presents cannot be overlooked, as this paper will expose. In Europe, a major challenge is ensuring compliance with the General Data Protection Regulation, starting with the search of a proper legal ground for data processing and the identification of an adequate exception to allow the processing of biometric data. The implementation of security measures and the risks associated with data transfer to third countries must also be considered. A further issue is the reliability of facial recognition technology, which relates to data accuracy. These challenges are substantial, but they are not insurmountable. More comprehensive and in-depth knowledge of the legal intricacies of the General Data Protection Regulation, more secure and transparent data-processing procedures, and full acknowledgement of the technology's limitations might provide a liability shield. [ABSTRACT FROM AUTHOR]

Fog Manufacturing applies both Fog and Cloud Computing collaboratively in Smart Manufacturing to create an interconnected network through sensing, actuation, and computation nodes. Fog Manufacturing has become a promising research component to be integrated into the existing Smart Manufacturing paradigm and provides reliable and responsive computation services. However, Fog nodes' relatively limited communication bandwidth and computation capabilities call for reduced data communication load and computation time latency for modeling. There has long been a lack of an integrated framework to automatically reduce manufacturing data and perform computationally efficient modeling/machine learning. This research direction is increasingly important as both the computational demands and Fog/networked Manufacturing become prevalent. This paper proposes an integrated and distributed framework for data reduction and modeling of multiple systems in a Smart Manufacturing network considering the system similarities. A simulation study and a Fog Manufacturing testbed for ingot growth manufacturing validated that the proposed framework significantly reduces the sample size used for improved computational runtime metrics while outperforming various other data reduction methods in modeling performance. [ABSTRACT FROM AUTHOR]