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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]

Many applications of Wireless Mobile Communication are used in military, defense etc. however this type of network have many constraints mainly including power constrains, less range of communication & insecure transmission channel which makes it more vulnerable to attacks. such as sinkhole and black hole attack which hampers the communication by attacking on data traffic and communication links on which packets are routed. The attack which operates by falsely claiming a fresh route to destination is a kind of denial of service is known as Sink hole attack. On the other hand black hole attack, intentionally dropped the incoming packets through malicious node in between the intermediately nodes. In this research paper we can examine and investigate the impact of sink hole and black hole attack on the performance of MANET network using DSR protocol in terms of throughput, packet delivery ratio over the network. [ABSTRACT FROM AUTHOR]

With the advent of the Internet of Things (IoT), accomplishing specific tasks in an interconnected network consisting of integrated computational devices has become simple. The paper titled I "Improved perturbation technique privacy-preserving rotation-based condensation algorithm for privacy preserving in big data stream using Internet of Things" i is based on a privacy-preserving rotation-based condensation algorithm consisting of geometric transformation. The paper titled I "LAMSTAR: For IoT-based face recognition system to manage the safety factor in smart cities" i develop an effective and artificial intelligence IoT-based facial expression detection system is implemented to predict and match the face from the database. [Extracted from the article]

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]

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]

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]

A memoryless bivariate Gaussian source is transmitted to a pair of receivers over an average-power limited bandwidth-matched Gaussian broadcast channel. Based on their observations, Receiver 1 reconstructs the first source component while Receiver 2 reconstructs the second source component both seeking to minimize the expected squared-error distortions. In addition to the source transmission digital information at a specified rate should be conveyed reliably to Receiver 1–the “stronger” receiver. Given the message rate we characterize the achievable distortions region. Specifically, there is an ${\sf SNR}$ -threshold below which Dirty Paper coding of the digital information against a linear combination of the source components is optimal. The threshold is a function of the digital information rate, the source correlation and the distortion at the “stronger” receiver. Above this threshold a Dirty Paper coding extension of the Tian-Diggavi-Shamai hybrid scheme is shown to be optimal. [ABSTRACT FROM AUTHOR]

In this paper smart shoes for dementia care using embedded boards and Low Power Wide Area technology and their application software are implemented. The communication board composed of Cortex-M3 board and LoRa module is embedded into groove made in outsole of smart shoes. Including the mold, the shoe outsole was manufactured by hand. By using application software and embedded board, caregiver can track the position of dementia patient using GPS and LoRa network. The location tracking and data transmission operations of smart shoes have been successfully verified in the outdoor environment. The smart shoes of this paper are applicable to a safety device to prevent the disappearance of demented patients through results of experiments and if bigdata is collected and analyzed by deep-learning, it may be helpful to analyze the predictive path of dementia patients or the pattern of dementia. [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]

The present research work focuses on overcoming cybersecurity problems in the Smart Grid. Smart Grids must have feasible data capture and communications infrastructure to be able to manage the huge amounts of data coming from sensors. To ensure the proper operation of next-generation electricity grids, the captured data must be reliable and protected against vulnerabilities and possible attacks. The contribution of this paper to the state of the art lies in the identification of cyberattacks that produce anomalous behaviour in network management protocols. A novel neural projectionist technique (Beta Hebbian Learning, BHL) has been employed to get a general visual representation of the traffic of a network, making it possible to identify any abnormal behaviours and patterns, indicative of a cyberattack. This novel approach has been validated on 3 different datasets, demonstrating the ability of BHL to detect different types of attacks, more effectively than other state-of-the-art methods. [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]

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]

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]

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]

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

This paper proposes a digital image compression-encryption scheme based on the theory of compressive sensing and cyclic shift, which use random Gauss matrix and sparse transform to compress the digital image, and then cyclic shift and diffusion operation are developed subsequently to the compressive sensing (CS) phase. The algorithm has three advantages: First, the measurement matrix used in the algorithm is generated by Chebyshev mapping, which increases the key space and reduces the burden of key transmission. Second, The Sigmoid function is used to transform the range of compressed data to 0~255, which are stored as 8-bit binary data, thus further reducing the amount of data transmission and avoiding the expansion of encrypted data. Third, the generation of key stream in encryption phase is related to ciphertext, there are different key streams for different plain images. Thus, our algorithm can resist against the chosen-plaintext and known-plaintext attacks effectively. In addition, the implementation of cyclic shift and diffusion operation further enhances the security of the system. Each pixel of the encrypted image is output in the form of 8-bit integer to facilitate data storage, display and transmission. The experimental results and security analysis show that the algorithm has the advantages of large key space, no obvious statistical characteristics of ciphertext, sensitive to plaintext and key, and able to resist chosen-plaintext attack. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]