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Colourimetric quantification of analytes on paper analytical devices (PADs) using smartphones has been gaining popularity. However, the accuracy of these devices is prone to be affected by different environmental conditions, including the intensity and colour of the ambient light. This work explains in depth the design and fabrication of a handheld colourimeter whose accuracy is unaffected by ambient light conditions using the commercially available spectral sensor AS7262. The device works on the principle of light reflection from the sample and can quantify as well as display the concentration of the analyte on an organic light-emitting-diode (OLED) display. The data acquisition, processing, and transmission of the data to a smartphone using Bluetooth in less than 7 seconds is also a salient feature. The accuracy of the device was validated by testing different concentrations of alkaline phosphatase (ALP) and total protein on PADs explicitly developed for this study. The colourimeter exhibited linearity with R² values of 0.98 for ALP and 0.97 for total protein. The LOD and LOQ obtained for ALP and total protein are 1.1, 3.89 U/L and 0.037, 0.12 g/dL, respectively. The relative standard deviation (RSD) calculated was 0.006 for ALP and 0.004 for total protein. The validation of the colourimeter was carried out with the clinical samples to obtain a relative error of less than 10 % for both the analytes. [Display omitted] • A low-power, handheld, reflection-based colourimeter was developed. • The device employed 0°/45° optical configuration for analyte quantification. • The device exhibited excellent linearity for alkaline phosphatase and total protein on PADs. • The developed colourimeter was validated with real and laboratory samples. • By reconfiguring the calibration equation, the device can quantify multiple analytes. [ABSTRACT FROM AUTHOR]

This paper proposes a 6Gb/s receiver for 8K displays and beyond. In the proposed receiver, a novel channel coding with 1.96% overhead is presented to guarantee minimum run‐length in the clock embedded interface. It can also reduce bandwidth for effective data transmission compared to 9b/10b coding that requires 11.11% overhead. Furthermore, we present an on‐chip eye margin tester that can measure the internal timing margin of receiver with only 1% area overhead. The prototype ICs are implemented using 0.18‐μm HVCMOS process and evaluated in an 8K 65‐inch panel. [ABSTRACT FROM AUTHOR]

In this advanced and forward-thinking era of science, data transmission is an extremely common practice. Up to this point, the majority of our data transfer has been accomplished through the use of Wi-Fi technology. But light itself is another option for us to employ as a source for the data transfer. The technique of exchanging data by the use of light is referred to as Li-Fi, which is short for "light Fidelity." The Visible Light serves as the channel of communication in the Li-Fi protocol. This is the newest technology that has been created in the field of data exchange in recent years. Additionally, this technology is in the process of being developed as a result of the increasing number of studies that are being conducted on this particular subject for the purpose of facilitating its improvement. From a scientific standpoint, this optical communication technology is now the most cutting-edge issue of discussion. Because Li-Fi uses VLC, which stands for visible light communication, the rate of data transfer is quite fast with this technology (VLC). In terms of the data transmission, it adheres to the standards established by the IEEE (Institute of Electrical and Electronics Engineers). In this study article, we will be pointing out some particular elements such as the characteristics, techniques, applications, pros and downsides, and comparison with ongoing related technologies such as Wi-Fi. [ABSTRACT FROM AUTHOR]

With the strong increase of mobile data‐communication needs, mobile devices become more important than ever. To be able to provide the users the best experience, display sizes will need to increase while portability needs to be maintained. Flexible, foldable and rollable displays are serving these emerging user needs. This challenges every layer in the display, requiring the display panel to become thinner and thinner while maintaining robustness and reliability. This paper will talk about highly reliable photo patternable interlayers in TFT stacks and touch sensor layers based on inorganic‐organic hybrid polymers. A novel solution, that improves process‐ability for flexible display devices. In addition, hybrid polymer‐based films provide good process durability, higher transparency, and higher environmental durability. Therefore, these new formulations are a key enabler for foldable and rollable OLED and e‐paper displays. [ABSTRACT FROM AUTHOR]

The emergence of the Internet has brought revolutionary changes to modern information technology. The development of electronic communication information storage technology facilitates people to access information anytime and anywhere, effectively achieving resource sharing. However, traditional methods scatter communication information to all nodes, but neglect the extraction of electronic communication information association features, resulting in low information storage efficiency. This article analyzes the efficiency management of electronic communication information storage in multi-threaded networks and sets up a control experiment. Comparing the method proposed in this article with traditional methods, this study focuses on five aspects: information redundancy storage, information space utilization, productivity, data accuracy, and data transmission efficiency. It is concluded that the average information redundancy storage capacity of traditional electronic information storage methods is 8.35 x 107 T which is 6 x 107 T higher than using multi wire network electronic communication information storage methods. It indicates that traditional redundant information occupies a large amount of storage space, and its storage value exceeds the upper limit of electronic communication information storage. This means that the stored information may be overwritten by redundant information, resulting in the loss of stored information. The experimental results show that using the method proposed in this paper for electronic communication information storage results in a high distribution density of storage space and a significant improvement in information storage efficiency. [ABSTRACT FROM AUTHOR]

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]

Driven by the need for new affordable wireless data communication technologies, special liquid crystals have been developed and optimized for use in microwave components above 10 GHz. As tunable dielectrics, they pave the way for continuously tunable antennas for SATCOM and wireless 5G/6G applications either fixed at home or on‐the‐move. This presentation gives an insight into the current material development with special focus on the application in transparent antennas for fixed 5G access. Sunlight stability tests for an equivalent device lifetime of 5 years were conducted resulting in yellowing index values of < 4, being 2.5 times less than the required threshold. [ABSTRACT FROM AUTHOR]

Wireless sensor networks which are based on distributed information processing technology are taking an increasingly key role in industrial digital twin scenarios. There are many important issues in the access of networks. One of the most important issues is how to improve network access control and the effectiveness of load balancing. Based on the industrial digital twin technology, this article first introduces several typical network access and network loads and performs tree-structured processing on the outliers generated during the chain formation process to reduce the length of the data transmission path, optimize the main chain head and subchain chain head selection strategy and chaining rules, and perform nonchain operations on common nodes and chain heads near sink to reduce data inverse transfer. The experimental results show that this paper uses the digital twin calculation formula to accurately and objectively determine the remaining cluster head and the distance head and the base station, so that when the node distance is limited, the network energy consumption can be balanced as much as possible, and the network load is promoted. [ABSTRACT FROM AUTHOR]

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]

We develope new application, in conjunction with the Internet of things hardware and software technology, E‐Paper will be used in the use of official ID Card to research, in particular on how to use low‐resolution display of human head color processing algorithms, on NFC passive driver EPD display and on‐line storage and operation data transmission. [ABSTRACT FROM AUTHOR]

Delay and stability are two key factors that affect the performance of multicast data transmission in a network. However, current algorithms of tree generation hardly meet the requirements of low delay and high stability simultaneously. Given a general network, the generation algorithm of a multicast tree with minimum delay and maximum stability is an NPhard problem, without a precise and efficient algorithm. To address these challenges, this paper studies the generation of low-delay and high-stability multicast trees under the model of spanning tree based on stability probability, degree-constrained, edge-weighted for multicast (T-SDE). A class of algorithms was proposed which creates the multicast tree greedy on the ratio of fan-out to delay (RFD) and probability of stability of terminal to obtain a high performance in multicast. The proposed algorithms greedily select terminals with a large RFD and a high probability of stability as forwarding nodes in the generation of the multicast tree, where the larger RFD and higher stability of upstream nodes are beneficial to achieve a low transmission delay and high stability in multicast. The proposed RFD can be compatible with the original model, which can take advantage of network connectivity during the generation of a multicast tree. This paper carries out simulation experiments on Matlab R2016b to measure the performance of the proposed algorithm. Experimental results show that the proposed algorithm can provide a smaller height, higher stability, and a lower transmission delay of the resulting multicast tree than other solutions. The spanning tree of the proposed algorithms can support low transmission delay and high stability in multicast transmission. [ABSTRACT FROM AUTHOR]

Radiation anomalies in optical remote sensing images frequently occur due to electronic issues within the image sensor or data transmission errors. These radiation anomalies can be categorized into several types, including CCD, StripeNoise, RandomCode1, RandomCode2, ImageMissing, and Tap. To ensure the retention of image data with minimal radiation issues as much as possible, this paper adopts a self-made radiation dataset and proposes a FlexVisionNet-YOLO network to detect radiation anomalies more accurately. Firstly, RepViT is used as the backbone network with a vision transformer architecture to better capture global and local features. Its multiscale feature fusion mechanism efficiently handles targets of different sizes and shapes, enhancing the detection ability for radiation anomalies. Secondly, a feature depth fusion network is proposed in the Feature Fusion part, which significantly improves the flexibility and accuracy of feature fusion and thus enhances the detection and classification performance of complex remote sensing images. Finally, Inner-CIoU is used in the Head part for edge regression, which significantly improves the localization accuracy by finely adjusting the target edges; Slide-Loss is used for classification loss, which enhances the classification robustness by dynamically adjusting the category probabilities and markedly improves the classification accuracy, especially in the sample imbalance dataset. Experimental results show that, compared to YOLOv8, the proposed FlexVisionNet-YOLO method improves precision, recall, mAP0.5, and mAP0.5:0.9 by 3.5%, 7.1%, 4.4%, and 13.6%, respectively. Its effectiveness in detecting radiation anomalies surpasses that of other models. [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 adoption of blockchain platforms to bolster the security of Internet of Things (IoT) systems has attracted significant attention in recent years. Currently, there is a lack of comprehensive and systematic survey papers in the literature addressing these platforms. This paper discusses six of the most popular emerging blockchain platforms adopted by IoT systems and analyses their usage in state-of-the-art works to solve security problems. The platform was compared in terms of security features and other requirements. Findings from the study reveal that most blockchain components contribute directly or indirectly to IoT security. Blockchain platform components such as cryptography, consensus mechanism, and hashing are common ways that security is achieved in all blockchain platform for IoT. Technologies like Interplanetary File System (IPFS) and Transport Layer Security (TLS) can further enhance data and communication security when used alongside blockchain. To enhance the applicability of blockchain in resource-constrained IoT environments, future research should focus on refining cryptographic algorithms and consensus mechanisms to optimise performance and security. [ABSTRACT FROM AUTHOR]

This paper discusses the design and implementation of a portable IoT station. Communication and data synchronization issues in several installations are addressed here, making possible a detailed analysis of the entire system during its operation. The system operator requires a synchronized data stream, combining multiple communication protocols into one single time stamp. The hardware selected for the portable IoT station complies with the International Electrotechnical Commission (IEC) industrial standards. A short discussion regarding interface customization shows how easily the hardware can be modified so that it is integrated with almost any system. A programmable logic controller enables the Node-RED to be utilized. This open-source middleware defines operations for each global variable nominated in the Modbus register. Two applications are presented and discussed in this paper; each application has a distinct methodology utilized to publish and visualize the acquired data. The portable IoT station is highly customizable, consisting of a modular structure and providing the best platform for future research and development of dedicated algorithms. This paper also demonstrates how the portable IoT station can be implemented in systems where time-based data synchronization is essential while introducing a seamless implementation and operation. [ABSTRACT FROM AUTHOR]

The article reports that looking to 2030 and beyond, revolutionary enhancement of data transmission rates in sixth generation (6G) and beyond systems are required to meet the challenge of increasing communication traffic due to the massive exchange of information. Development of technologies and systems enabling Terabit-per-second (Tbps) wireless communications need to support long term exponential capacity increase of mobile communication networks.

Gigabit-capable passive optical network (GPON) is a passive optical network that provides faster data transmission and reception using point-to-multipoint access technology with single fiber. Using passive splitter in distribution network to keep the costs down, its 2.5 Gbits/sec bandwidth can be split up to 64 times. This paper presents the study of max Q-factor, min bit error rate (BER) using Opti system 17. In this study return to zero (RZ) and nonreturn to zero (NRZ) line codes analyzed by using P-insulator-N (PIN) and avalanche photo diode (APD) receivers. This paper also studies the impact of CW laser power on Q factor and min BER of GPON with and without erbium-doped fiber amplifier (EDFA). [ABSTRACT FROM AUTHOR]

The article offers information on the journal's call for papers on topics like military communications and networks, internet of things, and artificial intelligence and data science for communications.

With the continuous progress of the society, Intelligent Connected Vehicles (ICVs) in Internet of Vehicles (IoVs) continuously generate a large amount of data. Considering the data security at the vehicle node end, the introduction of federated learning(FL) into the Internet of Vehicles may be an effective solution. However, there are some challenges in applying existing federated learning frameworks directly to IoVs. For example, the participation of malicious nodes in model training can cause federated model poisoning, and the non-IID data generated at the vehicle side can slow down the convergence speed of FL. To address these challenges, this paper proposes a novel federated learning framework based on trust evaluation. The trust evaluation module of this framework evaluates the trust of vehicle nodes from three levels: the success rate of data transmission, the reliability and real-time performance of the network, and the historical behaviors of the nodes to derive the total trust value of the vehicle nodes in order to select nodes with high trust to participate in model training. The model training module of the framework takes into account the problem of slow model convergence caused by the non-IID nature of the training data at the vehicle node side, which is mitigated with the aid of the Federated Adaptive Weighting algorithm (FedAdp). Simulation results on MNIST and Fashion-MNIST datasets demonstrate that the framework proposed in this paper can achieve 85%-90% test accuracy with training data in IID and non-IID settings and two model attack settings. [ABSTRACT FROM AUTHOR]

At the end of 2019, a severe respiratory syndrome named COVID‐19 is started to be transmitted in the world and it has rapidly spread to a global pandemic. Every day, a series of data are collected for real‐time monitoring of the development of this pandemic. The data validation and the verification are becoming very important to manage the pandemic and give recommendations to the people. Nevertheless, sometimes, it is not possible to guarantee the truthfulness of such data and some information may be lost during collection. Due to its characteristics, the Blockchain technology can become an important support to face the COVID‐19 pandemic. In this regard, the aim of this research is to propose a literature review to understand how the blockchain technology has been used for health care and supply chain management to guarantee an efficient tracing, tracking, and monitoring solution, ensure a transparent and safe data transmission, and to delineate the emerging future research directions. [ABSTRACT FROM AUTHOR]

Multi-class geospatial object detection in high-resolution remote sensing images has significant potential in various domains such as industrial production, military warning, disaster monitoring, and urban planning. However, the traditional process of remote sensing object detection involves several time-consuming steps, including image acquisition, image download, ground processing, and object detection. These steps may not be suitable for tasks with shorter timeliness requirements, such as military warning and disaster monitoring. Additionally, the transmission of massive data from satellites to the ground is limited by bandwidth, resulting in time delays and redundant information, such as cloud coverage images. To address these challenges and achieve efficient utilization of information, this paper proposes a comprehensive on-board multi-class geospatial object detection scheme. The proposed scheme consists of several steps. Firstly, the satellite imagery is sliced, and the PID-Net (Proportional-Integral-Derivative Network) method is employed to detect and filter out cloud-covered tiles. Subsequently, our Manhattan Intersection over Union (MIOU) loss-based YOLO (You Only Look Once) v7-Tiny method is used to detect remote-sensing objects in the remaining tiles. Finally, the detection results are mapped back to the original image, and the truncated NMS (Non-Maximum Suppression) method is utilized to filter out repeated and noisy boxes. To validate the reliability of the scheme, this paper creates a new dataset called DOTA-CD (Dataset for Object Detection in Aerial Images-Cloud Detection). Experiments were conducted on both ground and on-board equipment using the AIR-CD dataset, DOTA dataset, and DOTA-CD dataset. The results demonstrate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm for the conversion of raster data to hexagonal DGGSs in the GPU by redevising the encoding and decoding mechanisms. The researchers first designed a data structure based on rhombic tiles to convert the hexagonal DGGS to a texture format acceptable for GPUs, thus avoiding the irregularity of the hexagonal DGGS. Then, the encoding and decoding methods of the tile data based on space-filling curves were designed, respectively, so as to reduce the amount of data transmission from the CPU to the GPU. Finally, the researchers improved the algorithmic efficiency through thread design. To validate the above design, raster integration experiments were conducted based on the global Aster 30 m digital elevation dataDEM, and the experimental results showed that the raster integration accuracy of this algorithms was around 1 m, while its efficiency could be improved to more than 600 times that of the algorithm for integrating the raster data to the hexagonal DGGS data, executed in the CPU. Therefore, the researchers believe that this study will provide a feasible method for the efficient and stable integration of massive raster data based on a hexagonal grid, which may well support the organization of massive raster data in the field of GIS. [ABSTRACT FROM AUTHOR]

For the transmission of data at high speed, the requirement of using a larger bandwidth increases due to the rise in wireless communication technologies like smart devices, mobiles, etc. An abrupt increase in the requirement for internet data due to an increase in internet users demanded time-to-time upgrades in available techniques. A significant modernization has been done by technology in mobile and wireless communication and networking fields. Therefore, the development of mobile communication began with the First Generation (1G) and has progressed continuously to the Fifth Generation (5G). To address the weaknesses of previous generations, each successive generation has been developed with improvements. Fifth Generation (5G) is the latest technology in wireless communication cellular systems, providing the highest internet speeds to everyone, anywhere, anytime. 5G has attracted many global researchers, universities, and research institutes to invent new techniques for enhancement in channel capacity and spectrum utilization of communication systems. This paper describes the evolution of cellular networks, expectations from 5G, the challenges and advantages of 5G, and the techniques on which 5G relies. [ABSTRACT FROM AUTHOR]

Voice over Internet Protocol (VoIP) is an interactive telecommunication technology that suggests shared, cooperative, and quality transactions in the form of communications over the internet. VoIP normally differs from traditional and conventional circuit-based networks in the form of a low rate because all the communication takes place through the internet. The user has to pay only for an internet connection. Real-time voice data transmission is very difficult when compared with ordinary text data transmission. A main challenge in telecom engineering is maintaining quality. The VoIP transmission faces a lot of inconvenience. It suffers from packet loss, low quality, jitter, delay, and on-time delivery. These parameters influence and degrade performance. The codec plays a major role in VoIP transmission. This paper reports on the fundamental functionalities of VoIP, including coder and decoder operations for quality output, broadcast technology, VoIP connection setups, advantages, applications, and emerging trends in VoIP. The performance of various codecs was analyzed to identify the most suitable codec for voice transmission. [ABSTRACT FROM AUTHOR]

The article offers information on the journal's call for feature topic (FT) proposals to complement its Series and Open Call publication tracks.

Real-time health data monitoring is pivotal for bolstering road services' safety, intelligence, and efficiency within the Internet of Health Things (IoHT) framework. Yet, delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems. We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this. This strategy is devised to streamline the data retrieval path, subsequently diminishing network strain. Crafting an adept cache processing scheme poses its own set of challenges, especially given the transient nature of monitoring data and the imperative for swift data transmission, intertwined with resource allocation tactics. This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach, facilitating nuanced health monitoring via edge devices. The system capitalizes on cloud computing for intricate health data analytics, especially in pinpointing health anomalies. Given the dynamic locational shifts and possible connection disruptions, we have architected a hierarchical detection system, particularly during crises. This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times. Furthermore, we introduce the Cache-Assisted Real-Time Detection (CARD) model, crafted to optimize utility. Addressing the inherent complexity of the NP-hard CARD model, we have championed a greedy algorithm as a solution. Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio (CHR) and data freshness, outshining its contemporaneous benchmark algorithms. The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution. To encapsulate, this paper tackles the nuances of real-time health data monitoring in the IoHT landscape, presenting a joint edge-cloud caching strategy paired with a hierarchical detection system. Our methodology yields enhanced cache efficiency and data freshness. The corroborative numerical data accentuates the feasibility and relevance of our model, casting a beacon for the future trajectory of real-time health data monitoring systems. [ABSTRACT FROM AUTHOR]

High resolution and high refresh rate increase the pressure of wide transmission. Usually, video compression is used to solve this problem. However, traditional video compression methods cannot be performed in bit‐plane, which will increase the cost of storage area. For this reason, this paper first introduces a bit just noticeable difference (BJND) model based on bit‐plane. By analyzing the relationship between the bit‐plane, frequency and eccentricity, the bit just noticeable difference threshold of viewpoint is calculated. Finally, the just noticeable difference model applied to bit‐plane is obtained. Then this paper proposes a video compression scheme based on bit motion estimation algorithm, which optimizes the search range of motion estimation into two small rhombuses of time dimension and gray‐scale dimension. According to human visual system and probability statistical analysis, supplementary matching blocks are added to replace residual data, so that the compression ratio will be constant. The experimental results show that the proposed scheme has the best comprehensive effect on the compression of the lower five‐bit plane. The compression ratio is 1.385, the data transmission is constant, and there is no obvious difference between the restored image and the original image, which conforms to the intuitive perception of the human eye. [ABSTRACT FROM AUTHOR]

Graham and Pollack in 1971 presented applications of eigenvalues of the distance matrix in addressing problems in data communication systems. Spectral graph theory employs tools from linear algebra to retrieve the properties of a graph from the spectrum of graph-theoretic matrices. The study of graphs with "few eigenvalues" is a contemporary problem in spectral graph theory. This paper studies graphs with few distinct distance eigenvalues. After mentioning the classification of graphs with one and two distinct distance eigenvalues, we mainly focus on graphs with three distinct distance eigenvalues. Characterizing graphs with three distinct distance eigenvalues is "highly" non-trivial. In this paper, we classify all trees whose distance matrix has precisely three distinct eigenvalues. Our proof is different from earlier existing proof of the result as our proof is extendable to other similar families such as unicyclic and bicyclic graphs. The main tools which we employ include interlacing and equitable partitions. We also list all the connected graphs on ν ≤ 6 vertices and compute their distance spectra. Importantly, all these graphs on ν ≤ 6 vertices are determined from their distance spectra. We deliver a distance cospectral pair of order 7, thus making it a distance cospectral pair of the smallest order. This paper is concluded with some future directions. [ABSTRACT FROM AUTHOR]

With the rapid development of wireless technology and Mobile communication technology worldwide, Mobile Learning represents a new learning trend in the field of higher education, and has gradually become the development trend and research hotspot of independent learning and lifelong learning. Based on modern wireless network mobile communication terminal technology, this paper proposes a Granott model-driven mobile learning system. Firstly, the Granott model is studied and analyzed, and the ubiquitous computing with physical integration and spontaneous interoperation is used to control the Android mobile terminal, which greatly improves the interactivity of M-Learning. Then JSON is selected to optimize the data transmission format in Ajax, and j Query is used to parse JSON data. Ajax + JSON + j Query can shield the complexity of DOM parsing XML files, greatly shorten the data transmission time and improve the efficiency of Granott model. Finally, the Fast kernel density estimation (Fast KDE) algorithm is introduced to compress the data transmitted by Ajax + JSON + j Query, so as to obtain a reasonable number of training samples. Through experiments and relevant data analysis, the proposed mobile learning system based on modern wireless network mobile communication terminal technology, optimized by JSON and Fast KDE algorithm, driven by Granott model, can efficiently complete the learning task, and improve the ubiquity, interactivity, timeliness of mobile learning. [ABSTRACT FROM AUTHOR]

As blockchain technology advances, cross-chain interoperability has become a crucial requirement for achieving seamless interaction among multiple chains. To solve this problem, this paper proposes a scholarly approach to the development of a cross-chain-secure transmission technique, incorporating the Trusted Platform Module (TPM) and the SM algorithm, which is based on trusted roots. This research paper elaborates on the design and implementation of the cross-chain-secure transmission technique based on TPM and the SM algorithm, emphasizing the academic rigor necessary for addressing the security requirements of cross-chain interactions. The research shows that compared with the previous method, the throughput of production capacity is not significantly different from that before and after adding the network delay, and the success rate of preventing attacks is increased by 46.9% by simulating related attacks. After multiple rounds of experiments, the effectiveness and feasibility of this technology in protecting cross-chain communication data are verified. [ABSTRACT FROM AUTHOR]

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]

Wireless Power Transmission (WPT) is widely used. In practical engineering applications, the transmitter and receiver of a stable and reliable WPT system need to establish not only a power transmission channel but also a data transmission channel to realize closed-loop control and information interaction. In this paper, a novel simultaneous wireless power and data transfer system based on a series–parallel (SP) resonant network is proposed. The system integrates an SP higher-order resonant network with series carrier injection, which makes power transmission and data transmission share a magnetic coupling channel. The isolation between power and data is realized by exploiting the frequency characteristics of the compensation network, thus realizing efficient power transmission and data transmission. In this paper, accurate and detailed mathematical modeling of the system is conducted, and the gain characteristics of the power transmission channel and the data transmission channel are demonstrated. Meanwhile, the mutual interference between the two channels is analyzed, and a feasible and effective parameter design method is developed. Finally, an experimental prototype with an output power of 16 W and a backward data rate of 100 Kbps is constructed to verify the feasibility of the proposed system and the correctness of the parameter design. [ABSTRACT FROM AUTHOR]

As an open network architecture, Wireless Computing Power Networks (WCPN) pose new challenges for achieving efficient and secure resource management in networks, because of issues such as insecure communication channels and untrusted device terminals. Blockchain, as a shared, immutable distributed ledger, provides a secure resource management solution for WCPN. However, integrating blockchain into WCPN faces challenges like device heterogeneity, monitoring communication states, and dynamic network nature. Whereas Digital Twins (DT) can accurately maintain digital models of physical entities through real-time data updates and self-learning, enabling continuous optimization of WCPN, improving synchronization performance, ensuring real-time accuracy, and supporting smooth operation of WCPN services. In this paper, we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models. We adopt an enumeration-based optimal placement algorithm (EOPA) and an improved simulated annealing-based near-optimal placement algorithm (ISAPA) to achieve minimum average DT synchronization latency under the constraint of DT error. Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency. [ABSTRACT FROM AUTHOR]

The study aimed to solve the common problem that hardware limitations and degradation make the data obtained in reality usually incomplete and improve the quality of communication transmission. In this paper, we propose a new low-rank tensor complementation model LRTC-CSC, which is based on tensor kernel parametrization (TNN), preserves the low-rank structure of information while restoring the detail features, and finally solves the problem using the efficient alternating direction multiplier method (ADMM). Based on the low-rank nature of the tensor, adding convolutional sparse coding (CSC) can well represent the characteristics of the high-frequency part of the information to handle the details while recovering the global information. The experimental results show that the training set of this paper saves much time compared with other models in several metrics by using only ten images of similar color for each data. At the same time, the data recovery effect is much higher than the novel TV canonical prior. In particular, the LRTC-CSC model is 5.18 dB higher than the LRTC-TV model in terms of PSNR value for image recovery at a 70% missing rate. The LRTC-CSC model proposed in this paper is more accurate and efficient for communication data restoration. [ABSTRACT FROM AUTHOR]

Due to the poor effect of the traditional vocational education platform, it is difficult to meet the requirements of the current Internet education platform. To solve this problem, this paper designs a vocational education platform system based on blockchain and Internet of Things (IoT) technology. First, the system access control strategy based on blockchain technology is introduced into the teaching system so as to improve the security of the teaching system. Then, in order to solve the single point of failure and efficient transmission problems of access control in the IoT environment, this paper proposes an access control strategy based on main side chain cooperation. This strategy introduces a side chain to expand the blockchain and improve the data carrying capacity of the blockchain. To meet the requirements of high-speed data transmission, this paper designs an access control model suitable for the main side chain blockchain structure. Experimental results show that compared with other algorithms, the data request speed of the system in this paper is faster, and the storage space is smaller. Therefore, the proposed technology based on blockchain and IoT can meet the use requirements of vocational education platforms. [ABSTRACT FROM AUTHOR]

Cloud computing is an online data storage system that can be easily accessed anywhere. Various algorithms and techniques have been developed to secure cloud data, which, if used correctly, can detect cloud attacks. These algorithms can only detect cloud data attacks and cannot prevent such attacks. If an attacker gains access to the data, he or she can tamper with the data in any way that could lead to misuse of the data. This paper will design a secure architecture for securing data with various algorithm implementations on the architecture so that cloud data can be saved from replay attacks. First, a text file will be taken, the text file will be encrypted using the encryption mechanism, and this file will be transmitted on the SaaS cloud server platform. Whenever a file is uploaded to a cloud server, it will be broadcast across the network, after which any user can access it, whether it is valid or invalid. Whenever a file is downloaded from a cloud server, it will be necessary to decrypt it to access it. If the file is successfully decrypted, then the file will be verified. A verification mechanism will be used to verify the data, which will be used to check whether a replay attack has been made on the data or not. If the data authentication is successful, this data will be called authentic data. The novelty of this paper is that an algorithm has been developed in this paper to prevent replay attacks so that if the data is retransmitted with slight changes, then the authenticity and inauthenticity of the data will be identified. Recent papers will be compared with the proposed paper in the conclusion, and it will be pointed out how much better the current technique is than the previous one. [ABSTRACT FROM AUTHOR]

Vehicle-to-vehicle (V2V) communication has played a pivotal role in modern intelligent transportation systems, enabling seamless information exchange among vehicles to enhance road safety, traffic efficiency, and overall driving experience. However, the secure transmission of sensitive data between vehicles remains a critical concern due to potential security threats and vulnerabilities. This research focused on investigating the security protocols that have been employed in vehicle-to-vehicle communication systems. A comprehensive review and analysis of relevant literature and research papers was conducted to gather information on existing V2V communication security protocols and techniques. The analysis encompassed key areas, including authentication mechanisms, encryption algorithms, key management protocols, and intrusion detection systems specifically applicable to V2V communication networks. Within the context of real-world V2V environments, this study delved into the challenges and limitations associated with implementing these protocols. The research aimed to provide a comprehensive understanding of the strengths and weaknesses of the current V2V communication security protocols. Furthermore, based on the findings, this paper proposes improvements and recommendations to enhance the security measures of the V2V communication protocol. Ultimately, this research contributes to the development of more secure and reliable V2V communication systems, propelling the advancement of intelligent transportation technology. [ABSTRACT FROM AUTHOR]

When traditional EEG signals are collected based on the Nyquist theorem, long-time recordings of EEG signals will produce a large amount of data. At the same time, limited bandwidth, end-to-end delay, and memory space will bring great pressure on the effective transmission of data. The birth of compressed sensing alleviates this transmission pressure. However, using an iterative compressed sensing reconstruction algorithm for EEG signal reconstruction faces complex calculation problems and slow data processing speed, limiting the application of compressed sensing in EEG signal rapid monitoring systems. As such, this paper presents a non-iterative and fast algorithm for reconstructing EEG signals using compressed sensing and deep learning techniques. This algorithm uses the improved residual network model, extracts the feature information of the EEG signal by one-dimensional dilated convolution, directly learns the nonlinear mapping relationship between the measured value and the original signal, and can quickly and accurately reconstruct the EEG signal. The method proposed in this paper has been verified by simulation on the open BCI contest dataset. Overall, it is proved that the proposed method has higher reconstruction accuracy and faster reconstruction speed than the traditional CS reconstruction algorithm and the existing deep learning reconstruction algorithm. In addition, it can realize the rapid reconstruction of EEG signals. [ABSTRACT FROM AUTHOR]

The expected development of the future generation of wireless communications systems such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) while maximizing the data rates. These requirements push research into developing new advanced technologies. To this end, massive multiple input multiple output (MMIMO) is introduced as a promising transmission approach to fulfill these requirements. However, maximizing the downlink-achievable sum rate (DASR) in MMIMO with a frequency division duplex (FDD) transmission mode and limited coherence time (LCT) is very challenging. To address this challenge, this paper proposes a DASR maximization approach using a feasible power allocation optimization method. The proposed approach is based on smartly allocating the total transmit power between the data transmission and training sequence transmission for channel estimation. This can be achieved by allocating more energy to the training signal than the data transmission during the channel estimation process to improve the quality of channel estimation without compromising more training sequence length, thus maximizing the DASR. Additionally, the theory of random matrix approach is exploited to derive an asymptotic closed-form expression for the DASR with a regularized zero-forcing precoder (RZFP), which allows the power optimization process to be achieved without the need for computationally complex Monte Carlo simulations. The results provided in this paper indicate that a considerable enhancement in the DASR performance is achieved using the proposed power allocation method in comparison with the conventional uniform power allocation method. [ABSTRACT FROM AUTHOR]

The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing linkage is proposed in this paper. The primary objective of this strategy is to maximize the confidentiality capacity of the system. To tackle this, an optimization problem is formulated, taking into consideration interruption probability and interception probability as constraints. To efficiently solve this optimization problem, a low-complexity algorithm rooted in deep reinforcement learning is designed, which aims to derive a suboptimal solution for the problem at hand. Ultimately, through simulation results, the validity of the proposed strategy in guaranteed communication security, stability, and timeliness is substantiated. The results confirm that the proposed intelligent security transmission strategy significantly contributes to the safeguarding of communication integrity, system stability, and timely data delivery. [ABSTRACT FROM AUTHOR]

The rapid development of mobile Internet has promoted the rapid rise of cloud computing technology. Mobile terminal devices have greatly expanded the service capacity of mobile terminals by migrating complex computing tasks to run in the cloud. However, in the process of data exchange between mobile terminals and cloud computing centers, on the one hand, it consumes the limited power of mobile terminals, and on the other hand, it results in longer communication time, which negatively affects user QoE. Mobile cloud can effectively improve user QoE by shortening the data transmission distance, reducing the power consumption, and shortening the communication time at the same time. In this paper, we utilize the property that genetic algorithm can perform global search seeking the global optimal solution and construct a dynamic task scheduling model by combining the device-cloud link. The task scheduling model based on genetic algorithm and random scheduling algorithm is compared through comparison experiments, which show that the assignment time of the task scheduling model based on genetic algorithm is shortened by 11.82% to 48.51% and the energy consumption is reduced by 22.28% to 47.52% under different load conditions. [ABSTRACT FROM AUTHOR]

A continuing need to improve health, safety and wellbeing in construction has led to multiple research projects and technological innovations. One such innovation is the Safety Risk Library: a repository of data that functions in BIM environments to assist designers and contractors in identifying health and safety risk scenarios and offer suitable validated treatments to mitigate their effects. This paper reports on the deployment of this library in several construction projects across the United Kingdom and reviews expert and practitioner opinions of such digital solutions for improving health and safety in the future. This paper makes several contributions. The description of an effective process for knowledge base creation, including the data extraction workflow, the anonymization of data and the definition of communication channels aligned to project working practices, is instructive for innovation developers, providing informative guidance through lessons learned. The discussion of expert and practitioner opinions of the functional knowledge base to improve health and safety performance could inform further technological developments in the field and provide empirical insights for developers. Additionally, the alignment of the Safety Risk Library to existing industry standards (PAS1192:6) for better sharing and use of structured health and safety information illustrates how digital solutions can connect directly with industry standards to facilitate improvements to working practices whilst also changing perceptions of how risks may be visualised, understood and actioned by duty holders engaged in construction projects. [ABSTRACT FROM AUTHOR]

Abstract-Achieving high solution efficiency on conventional sequential computation architecture is a challenging task due to penetration of multiple renewable energy sources (RESs). This challenge has become the bottleneck for the application in real-time grid operation, grid planning and analysis of the large-scale and complicated modern power system. Therefore, this paper proposes a parallel multi-GPU and multi-process Fast Decoupled (FD) method to accelerate the power flow calculation, reducing the system responsive time and guaranteeing real-time performance on a large-scale modern power system. In this paper, two hierarchy architecture, task parallelism and data parallelism, are designed to optimize the FD solver parallelization. Moreover, the GPUDirect technology is employed to enhance efficiency of data transmission and drastically reduce copy overhead. The proposed method in this paper achieves a speedup of 9 × ∼ 33 × , compared to the single GPU on a sample large-scale power system. [ABSTRACT FROM AUTHOR]

In an era characterized by unparalleled levels of data exchange and communication, ensuring the security of network transmissions emerges as a paramount concern. This paper undertakes a comprehensive exploration aimed at bolstering network security through the integration of Chaotic Maps with the robust ChaCha20 encryption algorithm. This pioneering approach seeks to introduce an additional stratum of intricacy and unpredictability to data encryption processes, thereby augmenting the confidentiality and integrity of information in transit. The investigation delves deeply into the theoretical underpinnings, practical implementation intricacies, thorough security analysis, and diverse real-world applications of this enhanced encryption framework. By offering a multifaceted examination, this study provides invaluable insights and guidance not only for network professionals but also for researchers operating within this dynamic field. Through its rigorous examination and innovative proposals, this paper contributes significantly to the ongoing discourse surrounding network security enhancement strategies. [ABSTRACT FROM AUTHOR]

A facile and digital do‐it‐yourself technique is proposed to fabricate inexpensive sensors on flexible substrates (paper, cloth, and plastic film). A set of office‐grade equipment (i.e., laserjet printer, thermal laminator, computer‐aided paper cutter), and commercially available supplies (i.e., baking wax paper, furniture restoration metal‐leaf) are used. Forming electrodes through traditional printing and defining a fluidic confinement region through crafting practice enable fabrication of a wide range of devices without requiring customized specialty instruments, costly infrastructure, and complicated fabrication steps, unlike previously introduced methods. Three different levels of experiments are designed to assess the comprehensiveness and responsiveness of the proposed method to the needs of existing research fields. The performances of the fabricated features at each level are evaluated to cover various application domains in environmental monitoring and biomedical diagnostics utilizing conductometric, colorimetric, biochemical, and chemoresistive detection principles. Devices with varying size of features, from nanometers to centimeters, are fabricated and characterized. This method provides an alternative route to decentralized production of low‐cost flexible sensors and other devices, with a minimal step, time, and facilities. The operation of such devices is simple and can be further empowered by smartphones for data analysis and transmission. [ABSTRACT FROM AUTHOR]

The Sunway TaihuLight is the first supercomputer built entirely with domestic processors in China. On Sunway Taihulight, the local data memory (LDM) of the slave core is limited, so data transmission with the main memory is frequent during calculation, and the memory access efficiency is low. On the other hand, for many scientific computing programs, how to solve the storage problem of irregular access data is the key to program optimization. Software cache (SWC) is one of the effective means to solve these problems. Based on the characteristics of Sunway TaihuLight structure and irregular access, this paper designs and implements a new software cache structure by using part of the space in LDM to simulate the cache function, which uses new cache address mapping and conflicts solution to solve high data access overhead and storage overhead in a traditional cache. At the same time, the SWC uses the register communication between the slave cores to share on the different slave core LDMs, increasing the capacity of the software cache and improving the hit rate. In addition, we adopt a double buffer strategy to access regular data in batches, which hides the communication overhead between the slave core and the main memory. The test results on the Sunway TaihuLight platform show that the software cache structure in this paper can effectively reduce the program running time, improve the software cache hit rate, and achieve a better optimization effect. [ABSTRACT FROM AUTHOR]

In our rapidly digitalizing world, the safeguarding of sensitive information stands as a critical concern for organizations across industries. This paper addresses the evolving complexities in data security by advocating the Advanced Encryption Standard (AES) algorithm as a robust defense against the expanding landscape of cyber threats. As financial, healthcare, and educational data transition to digital formats, vulnerabilities in data transmission become more pronounced. To counter these risks and ensure the integrity, confidentiality, and authenticity of essential data, this paper emphasizes the implementation of AES encryption. Thoroughly scrutinizing the widely acknowledged AES algorithm, we highlight its effectiveness and adaptability in securing data. The paper underscores the indispensability of AES in the modern data security milieu, emphasizing its role not only in securing information during transmission and storage but also in decryption, granting authorized users access to protected data. By embracing AES encryption and decryption, organizations can strengthen their defenses against various data-related threats, maintaining the trust and assurance of stakeholders. This work emphasizes the pressing demand for AES encryption and decryption in an era where data security takes precedence, offering valuable insights into their significance and practical application for the protection of crucial digital assets. [ABSTRACT FROM AUTHOR]

The emergence of Internet of Things (IoT) technology brings tremendous benefits to people's lives and work. However, the integration of IoT devices into diverse systems has underscored the pressing issue of security. Safeguarding data confidentiality in IoT systems necessitates the implementation of strong security measures, including authentication, encryption and access control mechanisms. When effectively employed, these measures pave the way for the development of an efficient and secure IoT system, offering substantial benefits to end-users. This paper introduces a novel authentication and access control solution tailored for IoT edge devices. Our suggested approach is applicable to the edge network comprising numerous nodes, enabling the transmission of extensive data within constrained bandwidth based on lightweight symmetric cryptography since it uses Chacha20 algorithm to establishing session key, and maintaining the protocol of identity management and access control more precisely through HoBAC and blockchain technology. We have successfully analyzed the protocol correctness using the scyther tool. The results demonstrate the superiority of the proposed protocol compared to alternative approaches, particularly in terms of communication and time costs. [ABSTRACT FROM AUTHOR]