Message Transmission Research Articles

The Cross-Communication of Cuproptosis and Regulated Cell Death in Human Pathophysiology.

Copper (Cu) plays a crucial and diverse function in biological systems, acting as a cofactor at numerous sites of enzymatic activity and participating in various physiological processes, including oxidative stress regulation, lipid metabolism, and energy metabolism. Similar to other micronutrients, the body regulates Cu levels to ensure homeostasis; any disruption in Cu homeostasis may result in various illnesses. Cuproptosis causes proteotoxic stress and ultimately results in cell death by the binding of Cu ions to lipid-acylated proteins during the tricarboxylic acid cycle of mitochondrial respiration. Cu is not only involved in regulatory cell death (RCD), but also in exogenous factors that induce cellular responses and toxic outcomes. Cu imbalances also affect the transmission of several RCD messages. Therefore, this article presents a thorough examination of the mechanisms involved in Cu-induced RCD as well as the role of Cu complexes in its pathophysiology.

Enhancing Image Cryptography Performance with Block Left Rotation Operations

In today’s interconnected world, the transmission of both lengthy and concise text messages is ubiquitous across diverse communication platforms. With the proliferation of sensitive and specialized information being exchanged, safeguarding these messages from potential threats such as intruders, abusers, and data hackers becomes imperative. This study introduces an innovative approach aimed at streamlining data protection procedures while concurrently thwarting hacking attempts. At the core of this method lies the utilization of a sophisticated variable content private key designed to facilitate ease of alteration without compromising the integrity of encryption and decryption operations. The pivotal aspect involves leveraging a covert color image to generate this private key, mandating both the sender and receiver to securely retain this image. By employing a selected color image, the private key can seamlessly adapt to match the length of the confidential message. To fortify the level of security, the message is recommended to be segmented into blocks of predetermined sizes, with the sender and receiver jointly establishing these parameters. Subsequently, the bytes within each block are consolidated into a singular vector, which undergoes a left rotation by a predetermined number of bits as specified by the communicating parties. The proposed methodology is empirically validated through the implementation of various color images and text messages. Comparative analyses against existing methods underscore the efficacy and robustness of the proposed approach, substantiating its significant advancements in data protection paradigms.

Research on basketball training health smart monitoring system based on picture sequence analysis

Abstract At present, exercises have become a frequent international competitive exchange activity. To some extent, a country's exercise level also measures the country's comprehensive economic strength. The holding of various international and domestic exercise events directly leads to the explosive increase of exercise videos digital. Therefore, efficient exercise video analysis is necessary. With the expansion of multimedia techniques and the emergence of message highways, the storage and transmission of digital video is no longer a difficult thing. The holding of different exercise events directly leads to the explosive increase of exercise videos. Therefore, efficient exercise video analysis is very necessary. Computer techniques have injected new vitality into most industries, but their expansion in the exercise industry is relatively slow. The means used in this paper is picture sequence analysis. The basic operation of sequence picture analysis is to detect motion messages or aims from picture sequences. It is a very active branch of picture courseing and computer sight. Because it has been widely used in many aspects of national eco and military, its research has attracted the general concentration of scientists all over the world.

An Improved Spray and Wait Routing Algorithm Based on Stable Transmission Capacity Evaluation of Nodes in Opportunistic Network

In opportunistic network, the regular connectivity of nodes and their individual conditions significantly influence message transmission. To address this, we propose an improved spray and wait routing algorithm based on stable transmission capacity evaluation of nodes (referred to as STCESW), which is derived from traditional Prophet and spray and wait algorithms but surpasses them. STCESW incorporates network models that consider node connection stability and transmission capacity, aiming to enhance the update and punishment formulas for node delivery probability. Furthermore, it combines the residual message buffer size of nodes with the angle between motion directions of nodes to determine more efficient and extensive message spraying in the network. The simulation results clearly indicate that STCESW significantly outperforms the other three enhanced algorithms in both SPMBM and RWP. It demonstrates its robust performance in terms of delivery probability, showing an increase ranging from 2% to 87% across diverse node buffer sizes or simulation time intervals. Additionally, it compromises slightly on delivery latency while maintaining relatively stable message latency and buffer time.

Optimizing Message Response Time in IoT Security Using DenseNet and Fusion Techniques for Enhanced Real-Time Threat Detection

As IoT devices increase, accuracy and data security become increasingly crucial. This research recommends a powerful threat detection system that accelerates message responses to improve IoT security. The recommended strategy finds dangers in using many data sources. Our deep learning system is DenseNet. It groups photographs nicely. We show how the approach works using real-world experiments. It has few false positives and negatives and is effective at recognizing items. Through ablation research, we examine how design and component selections impact technique performance. This clarifies the method's fundamentals. The research reveals that feature selection, fusion, and DenseNet design improve the technique. We discuss the need for fine-tuning hyperparameters to improve approaches and monitor more individuals. The strategy makes IoT communities safer and more robust by laying the groundwork for threat detection and response. This approach solves message transmission delay concerns, making the IoT safer. These discoveries may benefit hacking specialists. They improve and speed up IoT security.

Applications and Challenges of Fieldbus Technology in Intelligent Manufacturing Systems

Abstract This study advances the field of intelligent manufacturing by integrating automation, information technology, and digitalization into a novel “five horizontal and three vertical” system architecture. We introduce an enhanced model-free adaptive control (MFAC) algorithm that utilizes a dynamic linearization method alongside pseudo-partial derivatives (PPD) for optimizing data transfer within intelligent manufacturing systems. Using CANoe software for simulation, our research demonstrates the improved MFAC algorithm’s superior bus message transmission efficiency by 0.0224 to 0.026 and a significant reduction in the network load factor by 0.2068. These advancements highlight the efficacy of fieldbus technology in reducing network congestion and enhancing real-time performance in intelligent manufacturing environments.

An Optimization Framework for Active Physical-Layer Authentication

This paper concerns the problem of the parameter optimization of an active Physical-Layer Authentication (PLA) scheme, which is crucial for minimizing the distortion on the base signal carrying the original message caused by embedding a tag. An inappropriate parameter may significantly lower the efficiency of the entire period of message transmission. In this paper, we propose an optimization framework for an active PLA scheme and further propose a new systematic metric, defined as Secure Authentication Efficiency (SAE). In the proposed framework, we minimize the aforementioned distortion by tuning three parameters, i.e., the Probability of Message Transmission (PMT), the Probability of Message Outage (PMO), and the Probability of Secure Authentication (PSA). The proposed optimization framework deepens the understanding of the correlation between the parameters of an active PLA scheme and the conditions of a wireless channel, and allows us to systematically optimize the parameters of the active PLA scheme. Then, we establish an objective function by maximizing the SAE with both PMT and PMO constraints. We implement our approach and conduct extensive performance comparisons. Our experimental results show that when the SNR at the receiver is more than 15 dB, our approach achieves an average SAE of greater than 80%, whereas the prior scheme without parameter optimization degenerates to zero SAE under some conditions, e.g., high SNR at adversary or high communication rate.

Secure Message Transmission: Integrating AES Encryption and LSB Substitution Steganography in a Django-based System

Abstract: This study introduces an innovative strategy for ensuring secure message transmission by merging AES encryption with steganography. The proposed technique entails the development of a user-friendly website using Django, facilitating the secure input of messages. The input text is then subjected to encryption using the well-established AES algorithm, recognized for its robust cryptographic capabilities. Subsequently, the encrypted message becomes concealed within an image through the utilization of LSB substitution, a prevalent steganographic method. The paper thoroughly explores the methodology, experimental configuration, and outcomes, effectively showcasing the efficacy of this amalgamated approach. Ultimately, this solution offers a pragmatic remedy for accomplishing covert and secure communication across diverse applications.

Machine Learning-Based Risk-Aware Congestion Control Scheme for Minimization of Information Loss in Dense VANET Environment

Vehicular Ad-Hoc Network is one of the most growing research fields and has become a promising topic for researchers. Day by day, vehicle density increases, causing very serious issues like road accidents and traffic jams. These issues can be minimized by a periodic exchange of awareness messages among the vehicles. Traffic density increases transmission of awareness messages, which causes channel congestion and degrades safety services, so congestion control schemes must ensure that the channel load should be below a particular threshold, boost the quality of services and minimize information loss and delay in the network. This paper proposes a machine learning-based risk-aware congestion control (MLB-RACC) scheme which is an efficient congestion control scheme based on the modified [Formula: see text] -means machine learning algorithms. MLB-RACC technique processes the input data and helps to improve the quality of services in the automotive industry. It works in three phases: detecting congestion, clustering of vehicles and controlling the broadcasting of awareness messages for decreasing the channel load. MLB-RACC scheme works by grouping the nearest vehicles and the number of groups or clusters is decided on the basis of transmission range/transmission power. The group member selects adaptive transmission rate by looking at the channel busy ratio (CBR). In this technique, message generation rate is controlled at two levels: first is at the clustering level and second is during the checking of CBR. The scheme is implemented through MATLAB, NS2 and the SUMO platform and provides evidence for the minimization of information loss by analyzing the throughput, packet loss and end-to-end delay in comparison to ordinary decentralized congestion control (DCC) technique.

HABERMAS MODEL AND AESTHETIC PREFERENCE EVALUATION OF HOUSE FACADES: INSIGHTS FROM ERBIL CITY

Introduction: Architecture is a discipline distinguished through diversity, message transmission, and communication. Purpose of the study: A notable phenomenon has been noticed in Erbil: most of the units in the typical housing complexes started to redesign or change the facade characteristics. These changes were the result of the psychological trait of aesthetic preference. This study aims to analyze aesthetic preference parameters to identify communicative action using the Habermas model of communicative action. The analysis of the effective factors contributed to the understanding of these changes. Methods: The methodology of this study combines case study formal analysis and a proper questionnaire survey. A statistical analysis of the obtained results was used to formulate research objectives. Results: Five parameters derived from the theoretical framework (unity, scale, color, proportion, and balance) serve as elements and principles of design that affect the aesthetics. As a result, the study concludes that unity, proportion, and balance are the main factors to create a pleasing aesthetic appearance on the house facades.

Improving electrotactile communication with a multi-pad electrode under cognitive load.

Electrotactile systems are compact interfaces that can be used to convey information through the skin by producing a range of haptic sensations. In many applications, however, the user needs to perceive and interpret haptic stimulation while being engaged in parallel activities. Developing methods that ensure reliable recognition of electrotactile messages despite additional cognitive load is, therefore, an important step for the practical application of electrotactile displays. This study investigated if a simple strategy of repeating electrotactile messages can improve message identification during multitasking. Ten participants identified 36 spatiotemporal electrotactile messages delivered through a 3 × 2 pad-matrix electrode placed on the torso while performing a concomitant cognitive task in three conditions: the messages were presented once (No-REP), and each message was repeated three (REP3) and five (REP5) times. The main outcome measure was the success rate (SR) of message identification. During multitasking, in the No-REP condition, the SR (median (IQR)) dropped to 56.25% (22.62%), demonstrating that the cognitive task decreased performance. However, the SR significantly improved with message repetitions, reaching 72.92% (21.87%) and 81.25% (18.66%) in REP3 and REP5 conditions respectively, without a statistically significant difference between REP3 and REP5. Multitasking affected the efficacy of haptic communication, but message repetition was shown to be an effective strategy for improving performance. Additionally, only three repetitions were enough, as an additional increase in the duration of message transmission (5 repetitions) did not lead to further improvement. This study is an important step toward delivering electrotactile communication that can cope with the demands of real-world applications.

Mathematical formula detection in document images: A new dataset and a new approach

Most of existing mathematical formula detectors focus on detecting formula entities through object detection or instance segmentation techniques. However, these methods often fail to convey complete messages due to the absence of the contextual and layout information of mathematical formulas. For a more comprehensive understanding of mathematical formulas in document images, it is preferable to detect logical formula blocks that include one or multiple formula entities arranged in their natural reading order. These logical formula blocks enable the transmission of complete contextual messages of mathematical formulas and aid in the reconstruction of layout information of the document images, resulting in a more accurate mathematical formula detection. In this paper, we present a novel perspective on mathematical formula detection by framing it as a joint task of formula entity detection and formula relation extraction for identifying logical formula blocks. To this end, we introduce a new, large-scale dataset, called ArxivFormula, that includes well-annotated formula entity bounding boxes and formula relationships. We also propose a new approach, called FormulaDet, to address these two sub-tasks simultaneously. FormulaDet first employs a dynamic convolution-based formula entity detector, named DynFormula, to detect formula entities. It then uses a multi-modal transformer-based relation extraction method, named RelFormer, to group these detected formula entities into logical formula blocks. Extensive experiments on standard benchmarks in this field and the proposed dataset demonstrate that our FormulaDet can achieve significantly improved performance on formula entity detection and formula relation extraction compared to previous state-of-the-art methods. The joint detection and relation extraction approach provides a more thorough understanding of mathematical formulas in document images and effectively supports downstream tasks such as document layout analysis and scientific document digitization. The ArxivFormula dataset is publicly available at https://github.com/microsoft/ArxivFormula.

Kształtowanie kompetencji komunikacyjnych w aspekcie psychologicznym w zarządzaniu bezpieczeństwem państwa


 State security management, like any organisation, requires not only the provision of appropriate forces and resources but also the proper transmission of information and messages. Only the ability to send and receive messages correctly ensures efficient implementation of assigned tasks, their understanding, and execution. For the process of managing them to proceed properly, it is essential to follow the rules of interpersonal communication. In this context, it is necessary to further define the elements of communication competence. They can be divided into five psychological and linguistic components. They are also determinants of proper communication (i.e. correct, appropriate, and at the same time effective). These include having a high level of communication awareness, presenting a high communication culture, active listening, using appropriate feedback,, and avoiding communication barriers. The results of research on the communication competences of the surveyed students allow us to draw the conclusion that their level of communication awareness is too low, which is a quite a disturbing phenomenon, because it is the awareness of mistakes made or deficiencies and ignorance in the discussed area that is an essential element of improving communication competence. The multitude of aspects for which communication competences are of great importance is almost unlimited, and therefore emphasing the need for their guided development and improvement is a priority.

Research on Teaching Resource Management in Colleges and Universities Based on Multiple Data Chain Networks

Abstract In this paper, we first take the datalink network as the entry point and construct a university teaching resource management model based on a multivariate datalink network. A Link-22 data chain time synchronization algorithm with KF-RTPT is proposed to address the actual existence and unavoidable time deviation based on accuracy and timestamp acquisition errors. Meanwhile, a time slot allocation and optimization algorithm designed to maximize message transmission benefits is being developed to optimize the allocation of node time slot requirements. Finally, the constructed teaching resource management model is empirically analyzed from three perspectives: error optimization, dynamic time slot allocation, and model application effect. According to the findings, the KF-RTPT algorithm increases motion error efficiency by 3.83 in low-speed motion states and 8.16 in high-speed motion states when compared to the conventional RTT method. This effectively eliminates motion error and boosts the effectiveness of teaching and managing resources in colleges and universities.

Application of Fast Fourier Transform to the Speech Signals Scrambling

The article is devoted to the closure of speech signals by implementing a fast Fourier transform in a bandpass scrambler. The most radical measure to prevent the interception of speech signals is the use of cryptographic security methods. The first technical security systems began to be developed immediately after the invention of the telephone. The main goal when developing speech transmission systems is to preserve those characteristics that are most important for the listener to perceive. Communication security in the transmission of voice messages is based on the use of a large number of different methods of blocking signals that change the characteristics of speech in such a way that it becomes illegible and unrecognizable to attackers who listen to or intercept the closed voice message. The choice of closure methods depends on the specific application and the technical characteristics of the transmission channel. That is, technical channels of information leakage are a source of information for technical intelligence, which extracts information using technical means. Therefore, the problem of protecting information from technical intelligence is of particular relevance. The object of the study is the transmission of voice messages. The subject of the research is real-time speech closing systems. The purpose of the paper is to use fast Fourier transform to close speech signals in a bandpass scrambler. To do this, it is necessary to assess the capabilities of technical intelligence to intercept information of limited distribution; analyze types of speech signal closing systems.
 The paper presents a block diagram of a combined scrambler, an algorithm for rearranging input signal values using the fast Fourier transform, and hashing functions that are used to obtain a speech signal from a combined scrambler. It has been determined that "through-window" scramblers are the most reliable, and for greater levels of closure, combination scramblers should be used. The task set for further development of the topic is the development of a software application for the operation of streaming data encryption methods in real time.

Neonatal adiposity is associated with microRNAs in adipocyte-derived extracellular vesicles in maternal and cord blood, a discovery analysis.

Maternal body size, nutrition, and hyperglycemia contribute to neonatal body size and composition. There is little information on maternal-fetal transmission of messages which influence fetal growth. We analyzed adipocyte-derived small extracellular vesicular (ADsEV) microRNAs in maternal and cord blood to explore their adipogenic potential. There were 279 mother-neonate pairs with all phenotypic data (normal glucose tolerant NGT = 148, gestational diabetes mellitus GDM = 131). Neonates with adiposity were those in the highest tertile (T3) of sex-specific sum of skinfolds and those without adiposity (lean) in the lowest tertile T1 of NGT pregnancies. We studied ADsEV miRNAs in 76 and 51 neonates with and without adiposity respectively and their mothers based on power calculations (68 NGT and 59 GDM pregnancies). ADsEV miRNAs from maternal and cord blood plasma samples were profiled on Agilent 8*60 K microarray. Differential expression (DE) of ADsEV miRNAs in adipose vs. lean groups was studied before and after adjustment for maternal GDM, adiposity, and vitamin B12-folate status. Multiple miRNAs were common in maternal and cord blood and positively correlated. We identified 24 maternal and 5 cord blood miRNAs differentially expressed (discovery p ≤ 0.1) in the adipose group in unadjusted, and 19 and 26, respectively, in the adjusted analyses. Even though DE miRNAs were different in maternal and cord blood, they targeted similar adipogenic pathways (e.g., the forkhead box O (FOXO) family of transcription factors, mitogen‑activated protein kinase (MAPK) pathway, transforming growth factor beta (TGF-β) pathway). Maternal GDM and adiposity were associated with many DE ADsEV miRNAs. Our results suggest that the ADsEV miRNAs in mothers are potential regulators of fetal adiposity. The expression and functionality of miRNAs appear to be influenced by maternal adiposity, hyperglycemia, and micronutrient status during pregnancy.

ROS2 Real-time Performance Optimization and Evaluation

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception, force interaction, spatial obstacle avoidance, and motion planning. To ensure the reliability and determinism of system execution, a flexible real-time control system architecture and interaction algorithm are required. The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure, hardware abstraction, message-passing mechanism, and application prototypes. Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system. However, because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel, the system does not have real-time computing. To achieve a balance between real-time and non-real-time computing, this paper uses the transmission mechanism of ROS2, combines it with the scheduling mechanism of the Linux operating system, and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2. The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives, including throughput, transmission mode, QoS service quality, frequency, number of subscription nodes and EtherCAT master. This paper makes two significant contributions: firstly, it employs Preempt_RT to optimize the native ROS2 system, effectively enhancing the real-time performance of native ROS2 message transmission; secondly, it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems. This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance, with results vividly demonstrated through illustrative figures.

Laplace transform for Mittag-Leffler function in cryptography

The security of information has been a significant part of human civilization since the ancient era. In the information society, the protection of information becomes increasingly crucial for humankind, and new technologies are progressing in an unending stream. Cryptography is one of the greatest methods intended for protecting the transmission of messages and the security of data. For instance, digital commerce, electronic telecommunications such as mobile phone networks, sending personal emails, commercial transactions, paying television, the security of bank cards, cryptocurrency, etc, affect many areas of our everyday lives. Cryptography enables secrecy and protection for secret information by concealing it. It is made through a mathematical method. In this study, we built a new mathematical technique for cryptography in which we applied the Laplace transform (L-Transform) for the Mittag-Leffler function (or E-function) to plain text for encryption and the correspondent inverse L-Transform related to the E-function for decryption. Eventually, we use the Monobit test and correlation test for measuring the security level of encryption and the Python programming language for easily attaining cipher text, the original message, and computations of statistical tests.

Поддержка МИС IPSG.2. Повышение эффективности коммуникаций.

Ensuring high quality of medical care and patient safety is one of the most important tasks of modern medicine. Medical information systems (MIS) can make a significant contribution to achieving this result. MIS are important for the creation of clinical safety system due to their capabilities of access to information, unification of medical technological processes, organization of communication between participants of the therapeutic and diagnostic process, including the transmission of signals and warnings about the occurrence of critical events. When critical events are detected, MIS with different degree of automation is able to send a notification about them to the addressee – the attending physician or other responsible person, which allows to quickly take measures and prevent possible complications, contributing to improving the level of clinical safety and improving the quality of medical care. The article discusses the implementation of one of the ways to improve the efficiency of communications, namely, the transmission of messages when critical results of tests or other critical conditions of the patient are detected using the tools included in the MIS.

A Secure Communication System of Synchronized Chua’s Circuits in LC Parallel Coupling

Synchronization capability of two identical chaotic systems can be used for constructing the secure communication systems where the chaotic signal is used as the information carrier. In this paper, a secure communication system is designed by using the bi-directionally synchronized identical Chua’s circuits in LC parallel coupling. LC parallel circuit is used as the new coupling element instead of using a single resistor or capacitor or inductor as the coupling element. This makes the complete synchronization of Chua’s circuits possible for many different sets of coupling inductance and capacitance values so that the flexibility of constructing the secure communication systems is realized. Both the synchronized Chua’s circuits in LC parallel coupling and the corresponding secure communication system are constructed by using the LTspice software. The simulation results show that the secure communication system proposed in the present paper is very efficient for the message transmission for different pairs of coupling inductance and coupling capacitance values where the complete synchronization of Chua’s circuits is observed occur. The two essential properties of an ideal secure communication system - perfect message masking and recovery are observed when compared to other secure communication systems already proposed and constructed previously. So, the simulation results of the present study can be used for practically constructing the efficient communication systems in future.