Perfect Communication Research Articles

Time-Varying Cypher Assignment Based on Secrecy Capacity

Wireless communication is a convenient but not secure transmission media. For internet application, such as E-commerce, there are a lot of private information existed. To protect the secret information inside and to set up a secure communication becomes an urgent topic. The purpose of a perfect communication system is to ensure the authentic destination could correctly and successfully receive the exact desired information from the transmitter. Also, the system with authorization and authentication could protect the transmitted information away from the eavesdroppers. Generally, the encryption scheme is applied to. Although these methods have been employed in the system for the security, those unexpected and advanced attackers have been continuously developing. Error-free cryptogram based on Shannon’s theorem could provide a solution for the information security. It could be implemented with physical-layer security coding scheme. In this paper, the cypher generator is proposed with physical-layer coding scheme. The cypher format includes two parts. One is the prefixed code and the other is error-control code. The major purpose of prefixed code is the key to find the position indexing of code in the cypher. In this cypher generator, the interleaver plays a role to disturb the original data. It increases the degree of difficulty to break the cypher. With cryptanalysis, the practical example of LDPC is given. With AI technology, the advanced algorithm might be developed for cypher coding and decoding.

Communication Skills of Deaf Children

As social beings humans have a main need, namely communication, basically communication is a process, and the process must have an obstacle. Like the barriers experienced by deaf children, they experience barriers in their hearing as a result of which deaf people have difficulty speaking so that deaf children are not or less able to communicate verbally. Deaf children maximize their sense of sight as a way to complete the lack of hearing. The purpose and benefits of this study are to determine communication skills in deaf children, know how to socialize deaf children, and find out what are the obstacles in communicating deaf children. This study also aims to test whether there is an interaction between two independent variables that affect verbal and nonverbal communication skills in deaf children.deaf people often have communication problems as in students at SLB B-C Wijaya Kusumah, they still have difficulty in communicating even though generally deaf people use sign language alternatives. The results of our research found that the communication skills of deaf children in SLB B-C Wijaya Kusumah are still very low, this was obtained from the results of the researcher's interview with the class teacher concerned. There are only two children out of nine children who have comprehension in communicating using sign language, the rest still need special guidance in order to maximize their sense of sight as a way to perfect communication.

Employment of Synchronized Chaotic SHA256 Random Number Generators along with their Application in the Field of Image Encryption

Background: Current work is associated with the deployment of synchronized chaotic Secure Hash Algorithm (SHA256) random number generators along with their application in image encryption. Methods: This study aimed to design a perfect communication system to encrypt and decrypt the images via image processing. We introduced a new sliding mode scheme for master-slave fourdimensional (4D) Lorenz-Stenflo systems to deal with the synchronization problem. Then, a new synchronized dynamic secure hash algorithm (SHA-256) was implemented to generate the dynamic random numbers. Results: An image encryption and decryption mechanism was implemented by using synchronized chaotic master-slave systems corresponding to the generated hash values. Here, the master systems were used for encryption, and the slave systems were responsible for the decryption mechanism. The complete design of this paper was implemented in a Python environment. Conclusion: The demonstration of simulation results includes the state responses, strange attractors, and synchronization error responses of master-slave chaotic systems with appropriate switching functions and control input. conclusion: An image encryption and decryption mechanism has been implemented by using synchronized chaotic master-slave systems corresponding to the generated hash values other: The complete design of this paper has been implemented on python environment

Multi-source microwave heating temperature uniformity study based on adaptive dynamic programming

Abstract In view of the multi-physical field coupling and time-varying characteristics of the microwave heating medium process, how to dynamically plan the state characteristics of multiple microwave sources and optimize the material temperature uniformity becomes the focus of this article. To this end, first, algebraic graph theory is used to construct the multiple microwave sources as a multi-agent system, and a perfect communication topology is established to ensure the transfer and sharing of information. Second, according to the real-time temperature distribution of the material, an event-triggered adaptive dynamic planning algorithm is used to co-operate with the power input of the multiple microwave sources to ensure that no new hot spots are generated during the optimization of the temperature distribution using the self-organizing properties of the medium. Finally, a numerical calculation model for optimizing a mixture of integer and continuous variables is solved using the finite-element method. The experimental and numerical results show that this article improves the temperature uniformity by 32.4–73.5% and the heating efficiency by 14.3–39.4% compared to the generic heating model, and the feasibility of the method is verified by the different shapes of the heated material.

Estimating tolerable communication delays for distributed optimization problems in control of heterogeneous multi‐agent systems

AbstractThis study addresses the problem of distributed optimization in control of heterogeneous linear multi‐agent systems. Instead of assuming a perfect communication medium as in many existing approaches, two important issues arising from communication networks are considered. First, the existence of communication delays is assumed when each agent receives information from its neighbors. Second, since communication networks are generally unreliable, it is assumed that each agent interacts with other agents through random digraphs. Finally, delay‐dependent sufficient conditions are derived in the form of linear matrix inequalities (LMIs) to prove convergence to optimal solutions. Numerical simulation results are analyzed to demonstrate the effectiveness of the proposed approach.

Signal-Vehicle Coordination Control Modeling and Roadside Unit Deployment Evaluation under V2I Communication Environment

Signal-vehicle coordinated control holds substantial promise for enhancing urban transportation efficiency. However, its development faces notable challenges: (1) most existing studies have been conducted based on the assumption of perfect communication conditions. This assumption overlooks the significant impact of vehicle-to-infrastructure (V2I) communication quality on control performance, which leads to poor applicability in practice. (2) The evaluation of roadside unit (RSU) deployment for optimizing signal-vehicle control has not been well studied. Hence, the modeling of signal-vehicle coordination control and RSU deployment evaluation under V2I environment are studied in this paper. First, we introduce a communication model that characterizes the imperfections in communication between RSUs and connected vehicles (CVs). Second, we propose a model for signal-vehicle coordination control within this connected environment. This model integrates strategies from both signal control optimization and the speed optimization of CV platoons. Finally, to assess the impact of the RSU deployment parameters on the performance of signal-vehicle coordination control, we introduce a systematic evaluation method. The reduction in vehicle delays is introduced as the evaluation indicator for control performance. Six other indicators—the number of vehicles in the RSU communication domain, connectivity probability between the CV and RSU, number of vehicles whose speeds are successfully optimized, number of speed adjustments, green extension time, and overlap rate of the communication domains of multiple RSUs—are introduced as the observation indicators. The simulation experiments verify the effectiveness of the proposed model in implementing signal-vehicle coordination control under imperfect communication and environments in low-traffic, medium-traffic, and high-traffic scenarios. Furthermore, these experiments show the quantitative impact of RSU deployment parameters (communication distance, command transmission cycle, installation position, and number of RSUs) on control performance.

Quantum teleportation of W-type states in the presence of a controller

In this paper, we discuss a proposal for the transfer of states belonging to the W-type states by executing a controlled teleportation protocol. A 7-qubit quantum entangled resource shared between the sender, receiver and controller is utilized in this protocol. The scheme proposed here is a perfect communication scheme where the task of quantum state transfer is performed with certainty. Further, a protocol for the generation of the quantum resource used here is designed and run on IBM platform. Additionally, we consider the effect of four types of noises, namely, amplitude-damping noise, bit-flip noise, phase-flip noise and phase-damping noise on our protocol. The efficiency of the protocol is compared with other similar protocols which shows that the present one is better performing.

Analisis Tindak Tutur Pada Roman Panggil Aku Sakai Karya Ediruslan Pe Amanriza

Currently, language has become a benchmark for conducting effective and perfect communication activities. This is due to the ease of using language to communicate and interact with others. In our daily lives, we also require various forms of language, such as spoken language, written language, and speech acts. However, language, especially in the form of speech acts, does not only occur in everyday life but can also be found in various written works, including literary works such as short stories, novels, and romances. It cannot be denied that inspiration from literary works, particularly romances, reflects aspects of everyday life and naturally employs language and speech acts within them. One of these romances is "Panggil Aku Sakai" by Ediruslan Pe Amanriza. This romance serves as the subject of the author's research, which employs a qualitative approach and a descriptive method. The research also emphasizes the study of speech acts, where several types of speech acts, such as representative, directive, expressive, and commissive, can be identified.

Decentralized online convex optimization with compressed communications

Due to the iterative information exchange between agents, decentralized multi-agent optimization algorithms often incur large communication overhead, which is not affordable in many practical systems with scarce resources. To address this communication bottleneck, we compress the exchanged information between neighboring agents to solve decentralized online convex optimization problem, where each agent has a time-varying local loss function and the goal is to minimize the accumulated global loss by choosing actions sequentially. We develop a decentralized online gradient descent algorithm based on compressed communications, where the compression operators can reduce the amount of data to be sent significantly. Error-compensation technique is utilized to mitigate the error accumulation caused by the communication compression. We further analyze the performance of the proposed algorithm. It is shown that the regret is bounded from above by O(T) (T is the time horizon), which is the same as (in order sense) the regret bound for vanilla decentralized online gradient descent with perfect communication. Thus, the proposed algorithm is capable of reducing the communication overhead remarkably without much degradation of the optimization performance. This is further corroborated by numerical experiments, where compressed communication reduces the number of transmitted bits by an order of magnitude without compromising the optimization performance.

Assessing a Connected Environment’s Safety Impact During Mandatory Lane-Changing: A Block Maxima Approach

Previous studies have mostly hypothesised or provided preliminary evidence that crash risk during mandatory lane-changing manoeuvres in a connected environment would be reduced. However, the unavailability of crash data for a connected environment makes it challenging to confirm such a hypothesis. To this end, this study has adopted an Extreme Value Theory approach to estimate and compare crash risk using traffic conflicts during mandatory lane-changing manoeuvres in the traditional and connected environments. Using the CARRS-Q advanced driving simulator, seventy-eight participants performed mandatory lane-changing manoeuvres in three randomised driving conditions: baseline (without driving aids), connected environment with perfect communication (PC), and connected environment with communication delay (CD). Driving-related factors obtained from the driving simulator data such as speeds, spacings, lag gaps, and remaining distances were used as input to a block maximum (or generalised extreme value, GEV) model. The characteristics of the estimated GEV distributions and relative crash risk were employed as an indicator of safety. Results reveal that in the connected environment driving conditions, the mandatory lane-changing crash risk is significantly reduced compared to the baseline, with the highest reduction observed in the PC condition. The crash risk is found to be higher in the CD condition compared with the PC condition. Findings of this study confirm (i) that the connected environment has the potential to reduce the crash risk substantially by assisting drivers during mandatory lane-changing manoeuvres, and (ii) the efficacy of GEV models to quantify crash risk by using conflict data when crash records are unavailable.

Can Connected Autonomous Vehicles Improve Mixed Traffic Safety Without Compromising Efficiency in Realistic Scenarios?

CAVs have the potential to improve traffic safety and efficiency in a fully connected environment, but they face additional challenges when they interact with human-driven vehicles in mixed-traffic scenarios due to the uncertainty in humans’ driving behaviour. Another challenge is the unreliability of communication networks. Delays and packet losses in communication links due to dense traffic, communication interference, channel fading, etc. may jeopardize CAVs driving behaviour and negatively affect traffic safety and efficiency. While the impact of CAVs on traffic safety and efficiency at different market penetration rates (MPRs) has been studied extensively, CAVs have been assumed to operate in either realistic traffic scenarios with perfect communication or with only a very small number of vehicles with imperfect communication. In contrast, this paper investigates the impact of CAVs on both traffic safety and efficiency in realistic scenarios in terms of imperfect communication, large-reaction time, vehicle modelling, and traffic scenario, with a focus on quantifying the detrimental effects of unreliable V2V communication and large-reaction time. Results show that CAVs can significantly improve mixed traffic safety in the presence of unreliable V2V communication and large-reaction times by adopting a very cautious car-following strategy (i.e., larger time headways), but this is at the expense of a slight reduction in traffic efficiency. Specifically, safety conflicts can be reduced by up to 66.67% at 70% penetration rate in the presence of packet drop of 70% and reaction time of 0.5s, but only at the cost of a travel time increase of 2.6%.

Attack-Resilient Distributed Convex Optimization of Cyber–Physical Systems Against Malicious Cyber-Attacks Over Random Digraphs

This article addresses a resilient exponential distributed convex optimization problem for a heterogeneous linear multiagent system under Denial-of-Service (DoS) attacks over random digraphs. The random digraphs are caused by unreliable networks and the DoS attacks, allowed to occur aperiodically, refer to an interruption of the communication channels carried out by the intelligent adversaries. In contrast to many existing distributed convex optimization works over a perfect communication network, the global optimal solution might not be sought under the adverse influences that result in performance degradations or even failures of optimization algorithms. The aforementioned setting poses certain technical challenges to optimization algorithm design and exponential convergence analysis. In this work, several resilient algorithms are presented such that a team of agents minimizes a sum of local nonquadratic cost functions in a safe and reliable manner with the global exponential convergence. Numerical simulation results are further presented to validate the effectiveness of the proposed distributed approaches.

Invalidation of tunnelling attacks in ubiquitous IoT & wireless sensor enviroment using ML methods

Wireless sensors are interconnected are is ubiquitous in nature and provides great advantage are normally constituting perfect communication on wireless networks like infrastructure and Ad Hoc. The wireless connected devices environment can also be created using Internet of Things and also it can be adhoc. These wireless sensors are installed in the military campus to collect information movement of people, sound, capturing pictures of their activities. These kinds of sensors can be used in most secured places, where there is a need of remote monitoring of the security. It can be either used in atomic power stations or military camps. Based on the same, Ad Hoc networks attract great attention because data obstruction is made in communication interval. The communication interval helps to improve the mobile node convenience, node mobility, scalability and network cost. Perhaps, due the overload in data packet transmission, the routing makes the packet blockage between the nodes. Mobile nodes are always roaming around the particular region for supervise the external conditions or surroundings characteristics in order to accumulates the selective information about alive nodes and its communication route. On certain occasions these communication routes are vulnerable to various attacks due to functionality and deployment scenario, especially wormhole attack. This is an Ad Hoc assembling of mobile nodes that can randomly alter their route with respect to the constrained resources such as bandwidth, energy, security and resource discovery. Based on the above resources wormhole nodes create the fraudulent route within the network; the fraudulent route can confuse routing mechanisms which creates the tunnel between nodes. In order to invalidate the wormhole attacks in the route within the network, this research article proposed the “Train and Avoiding” process. The train and avoid process is the machine learning algorithm to find the optimal route where there are no attacks in the route. The process trains the routing to perform network traffic analysis. In addition to this, avoiding process helps to restrict the packets modification as well as fake route creation. Proposed Train and Avoiding based route Selection is used to achieve more prominent reliable routing. It improves PDR, average lifetime of network and minimizes communication issues, and average delay.

Communication-Aware Local Search for Distributed Constraint Optimization

Most studies investigating models and algorithms for distributed constraint optimization problems (DCOPs) assume that messages arrive instantaneously and are never lost. Specifically, distributed local search DCOP algorithms, have been designed as synchronous algorithms (i.e., they perform in synchronous iterations in which each agent exchanges messages with all its neighbors), despite running in asynchronous environments. This is true also for an anytime mechanism that reports the best solution explored during the run of synchronous distributed local search algorithms. Thus, when the assumption of perfect communication is relaxed, the properties that were established for the state-of-the-art local search algorithms and the anytime mechanism may not necessarily apply. In this work, we address this limitation by: (1) Proposing a Communication-Aware DCOP model (CA-DCOP) that can represent scenarios with different communication disturbances; (2) Investigating the performance of existing local search DCOP algorithms, specifically Distributed Stochastic Algorithm (DSA) and Maximum Gain Messages (MGM), in the presence of message latency and message loss; (3) Proposing a latency-aware monotonic distributed local search DCOP algorithm; and (4) Proposing an asynchronous anytime framework for reporting the best solution explored by non-monotonic asynchronous local search DCOP algorithms. Our empirical results demonstrate that imperfect communication has a positive effect on distributed local search algorithms due to increased exploration. Furthermore, the asynchronous anytime framework we proposed allows one to benefit from algorithms with inherent explorative heuristics.

To speak is to fight

This article, as part of a larger study on the role of war as the primary and primordial formativemechanism of human thought and communication, investigates the functions of war in thethinking of postmodern philosopher Jean-Francois Lyotard. It is argued that the central ideathat provides the structuring framework for Lyotard’s theory of communication is the concept ofagonistics that is derived from Heraclitus’ assertion that war is the father of all things. Againstthe prevailing hegemony of the pacifist bias in poststructuralist social theories, Lyotard returnslanguage to its pragmatic origin in the war-like agonistic and combative social reality. Lyotard’sinsight that acts of speaking in society resemble fighting facilitates a better understanding of thecontemporary postmodern global world that resembles a return of the neomedieval condition,which was characterised by perfect communication and warfare.

The Effects of Vehicle-to-Infrastructure Communication Reliability on Performance of Signalized Intersection Traffic Control

Vehicle-to-infrastructure communications can inform an intersection controller about the location and speed of connected vehicles. Recently, the design of adaptive intersection control algorithms that utilize this information received substantial research attention. These studies typically assume perfect communications. This study explores the possible effects of a temporal decrease in the reliability of the communication channel, on the intersection throughput. Road traffic and DSRC-VANET communications are modelled by integrating traffic and communication simulation tools (Vissim and OMNeT++, respectively). Simulations of scenarios with challenging, but realistic communication distortions conditions show significantly larger average delays to vehicles compared to scenarios with perfect communication conditions. These additional delays are largely independent of whether all or only some of the intersection approaches are affected by the communication distortions. Furthermore, delays do not increase uniformly on all signal groups. They may even decrease for some, which causes unfair allocation of green times. The control may be corrected for the lost communications using the information received in previous time intervals and simple assumptions about the vehicle movements. This correction decreases delays in all scenarios both for isolated and connected intersections. It performs similarly to the case with perfect communications when the communication distortions are distributed uniformly among all intersection approaches. Overall, the results demonstrate that the impact of the communication distortions should be considered in the design of the adaptive intersection control algorithms.

Multiagent Bayesian Deep Reinforcement Learning for Microgrid Energy Management Under Communication Failures

Microgrids (MGs) are important players for the future transactive energy systems where a number of intelligent Internet of Things (IoT) devices interact for energy management in the smart grid. Although there have been many works on MG energy management, most studies assume a perfect communication environment, where communication failures are not considered. In this article, we consider the MG as a multiagent environment with IoT devices in which AI agents exchange information with their peers for collaboration. However, the collaboration information may be lost due to communication failures or packet loss. Such events may affect the operation of the whole MG. To this end, we propose a multiagent Bayesian deep reinforcement learning (BA-DRL) method for MG energy management under communication failures. We first define a multiagent partially observable Markov decision process (MA-POMDP) to describe agents under communication failures, in which each agent can update its beliefs on the actions of its peers. Then, we apply a double deep <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -learning (DDQN) architecture for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -value estimation in BA-DRL, and propose a belief-based correlated equilibrium for the joint-action selection of multiagent BA-DRL. Finally, the simulation results show that BA-DRL is robust to both power supply uncertainty and communication failure uncertainty. BA-DRL has 4.1% and 10.3% higher reward than Nash deep <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -learning (Nash-DQN) and alternating direction method of multipliers (ADMM), respectively, under 1% communication failure probability.

Strengthening Characteristics of Organizational Structures as An Effort To Improve Madrasah Employee Performance

This paper aims to analyze the characteristics of the organizational structure and the efforts of the head of the madrasa to improve employee performance at the Amanatul Ummah Pacet International Standard Madrasah. This type of research has used descriptive qualitative. For data collection techniques, researchers used observation, interviews, and documentation. The data analysis in this study begins before being in the field, analyzing data in the field, reducing data, presenting data, and drawing conclusions. The results showed that the characteristics of the organizational structure in the Amanatul Ummah Pacet International Standard Madrasah impacted employee performance. Characteristics of the organizational structure here using the line staff organizational structure are different from school institutions. The organizational structure at the Amanatul Ummah Pacet International Standard Madrasah impacts employee performance where the performance has a perfect communication pattern.

A Review on Design Implementation and Verification of AMBA AXI- 4 lite Protocol for SoC Integration

Abstract: The present modern bus protocols used for communication between different functional blocks on a System-on-Chip (Soc) designs face many different challenges among which complexity and communication management are the most important factors. These on-chip communications directly impact performance and functionality, hence depending on the application where the bus protocol is to be used, a perfect communication protocol is chosen. AMBA (Advanced Microcontroller Bus Architecture) provides various types of protocols to be used as IP, of which AXI4 (Advance Extensible Interface), is one of the widely used protocols for SoC designs. Out of its three different interconnect protocols: lite, stream and burst, AXI4-lite has the simplest architecture design that best suits to be used in applications where power, area and performance play a vital role. This paper briefs about using AMBA AXI4-lite bus protocol with more bus efficiency and performance in an SoC design for proper communication between various functional blocks present. The RTL is verified using UVM (Universal Verification Methodology) and various designing process is carried out using cadence tools.

Decentralized Federated Learning With Unreliable Communications

Decentralized federated learning, inherited from decentralized learning, enables the edge devices to collaborate on model training in a peer-to-peer manner without the assistance of a server. However, existing decentralized learning frameworks usually assume perfect communication among devices, where they can reliably exchange messages, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , gradients or parameters. But the real-world communication networks are prone to packet loss and transmission errors. Transmission reliability comes with a price. The commonly-used solution is to adopt a reliable transportation layer protocol, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , transmission control protocol (TCP), which however leads to significant communication overhead and reduces connectivity among devices that can be supported. For a communication network with a lightweight and unreliable communication protocol, user datagram protocol (UDP), we propose a robust decentralized stochastic gradient descent (SGD) approach, called Soft-DSGD, to address the unreliability issue. Soft-DSGD updates the model parameters with partially received messages and optimizes the mixing weights according to the link reliability matrix of communication links. We prove that the proposed decentralized training system, even with unreliable communications, can still achieve the same asymptotic convergence rate as vanilla decentralized SGD with perfect communications. Moreover, numerical results confirm the proposed approach can leverage all available unreliable communication links to speed up convergence.