Ideal Communication Research Articles

Input predictors for networked iterative learning control systems with data dropouts and time delays

Hold-up compensation decelerates the convergence of iterative learning control (ILC) systems with data dropouts and time delays. Only depending on the prior knowledge of both ILC controllers and transmission channels, this paper develops a predictor to calculate the input not received on time due to data dropouts and time delays. First, a controller adopting the proportional learning strategy is considered directly, which is appropriate for objects in ideal communication conditions. After that, two data-receiving equations are given to describe the effect of data dropouts and one-step time delays. Finally, a predictor is designed according to the innovation analysis approach. Since the prediction uses all historical input at the identical time index in previous iterations, the predicted input is more approximate to the one not received on time than the input held up for compensation. Simulation results show the object with prediction compensation tracks the expected trajectory faster than that with input-hold compensation.

Fault-Tolerant cooperative driving at highway on-ramps considering communication failure

Cooperative driving has great potential to improve traffic safety and efficiency and has been widely discussed in recent years. However, most existing researches only focus on the ideal communication environment and ignore the potential vehicle communication failure, which poses serious safety threats to traffic safety. To fill this research gap, we propose three designing principles for a fault-tolerant cooperative driving model considering communication failure. We let vehicles make real-time decision adjustments according to changes in communication conditions. Fault and non-fault vehicles can execute different decision models in a distributed manner. We test with on-ramps scenarios in simulations. Experiment results demonstrate the promising performance of the proposed model in achieving fault tolerance while reducing the impacts on traffic efficiency.

Distributed Discrete-Time Secondary Cooperative Control for AC Microgrids With Communication Delays

This paper presents a droop-based distributed discrete-time secondary cooperative control scheme for AC microgrids with communication delays, which can regulate the voltage and frequency of all distributed generators (DGs) and ensure that each DG obtains active power sharing accurately. Unlike the ideal communication among DGs, the delays caused by low-band-bandwidth communication networks generally lead to potential oscillation and endanger the system stable operation. To this end, the proposed control protocol aims to compensate the general communication delays for cyber-physical microgrids actively by using predictive control theory while realizing voltage and frequency recovery as well as active power sharing precisely. Morever, each DG only needs to share information with its neighbors in the proposed scheme, and sufficient conditions for achieving stability of the closed-loop control systems are derived. The effectiveness of the control strategy is also verified by simulation studies and some experiments on OPAL-RT platform.

Finding Self-Salvation for the Ill-Informed Society: A Summary of Empirical Studies

The internet was once seen as a beacon of hope for democratizing public access to information, but scholars argue that social media has led to frustration, isolation, and pseudo-information. This volume presents empirical studies exploring paths to potentially rebuild ideal communication situations, if ever, in the digital age and cope with digital information failure. Can we salvage an ill-informed society? These studies offer insights into addressing these issues.

Wireless Federated Langevin Monte Carlo: Repurposing Channel Noise for Bayesian Sampling and Privacy

Most works on federated learning (FL) focus on the most common frequentist formulation of learning whereby the goal is minimizing the global empirical loss. Frequentist learning, however, is known to be problematic in the regime of limited data as it fails to quantify epistemic uncertainty in prediction. Bayesian learning provides a principled solution to this problem by shifting the optimization domain to the space of distribution in the model parameters. {\color{black}This paper proposes a novel mechanism for the efficient implementation of Bayesian learning in wireless systems. Specifically, we focus on a standard gradient-based Markov Chain Monte Carlo (MCMC) method, namely Langevin Monte Carlo (LMC), and we introduce a novel protocol, termed Wireless Federated LMC (WFLMC), that is able to repurpose channel noise for the double role of seed randomness for MCMC sampling and of privacy preservation.} To this end, based on the analysis of the Wasserstein distance between sample distribution and global posterior distribution under privacy and power constraints, we introduce a power allocation strategy as the solution of a convex program. The analysis identifies distinct operating regimes in which the performance of the system is power-limited, privacy-limited, or limited by the requirement of MCMC sampling. Both analytical and simulation results demonstrate that, if the channel noise is properly accounted for under suitable conditions, it can be fully repurposed for both MCMC sampling and privacy preservation, obtaining the same performance as in an ideal communication setting that is not subject to privacy constraints.

Tourism development policy implementation in the natural tourism object of Tesbatan Waterfall, Kupang District

The purpose of this study: 1) Knowing the ideal communication model for disseminating Kupang district government policies 2) Knowing the optimal resources in dealing with Tesbatan waterfall tourism development. 3) 3. Knowing the attitude of the ideal executor in order to be able to make policy implementation go well The research method uses a qualitative approach. The data sources used are primary and secondary data. Data collection techniques in this study were carried out through interviews, observation, and documentation. Data analysis was carried out in a qualitative descriptive method using the Miles & Huberman analysis model. This research seeks to obtain the ideal formulation of tourism policy implementation in the Tesbatan Waterfall tourism object based on four dimensions of public policy which is often called the Edward III model, which consists of communication, resources, implementing attitudes and bureaucratic structure.

Learning for Vehicle-to-Vehicle Cooperative Perception Under Lossy Communication

Deep learning has been widely used in intelligent vehicle driving perception systems, such as 3D object detection. One promising technique is Cooperative Perception, which leverages Vehicle-to-Vehicle (V2V) communication to share deep learning-based features among vehicles. However, most cooperative perception algorithms assume ideal communication and do not consider the impact of Lossy Communication (LC), which is very common in the real world, on feature sharing. In this paper, we explore the effects of LC on Cooperative Perception and propose a novel approach to mitigate these effects. Our approach includes an LC-aware Repair Network (LCRN) and a V2V Attention Module (V2VAM) with intra-vehicle attention and uncertainty-aware inter-vehicle attention. We demonstrate the effectiveness of our approach on the public OPV2V dataset (a digital-twin simulated dataset) using point cloud-based 3D object detection. Our results show that our approach improves detection performance under lossy V2V communication. Specifically, our proposed method achieves a significant improvement in Average Precision compared to the state-of-the-art cooperative perception algorithms, which proves the capability of our approach to effectively mitigate the negative impact of LC and enhance the interaction between the ego vehicle and other vehicles. The code is available at: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/jinlong17/V2VLC</uri>

Leading brand communication during crises: COVID-19 lockdown at Gautrain, South Africa

Learning outcomes The learning outcomes of this study are as follows: 1. comprehending foundational dimensions of brand equity and criteria to compare the use of traditional and new media in leading brand communication appropriateness and performance; 2. understanding and evaluating implications of leading brand communications during times of crises; and 3. creating recommendations for leading brand communication preparedness and response to crises. Case overview/synopsis On 16 August 2020, Dr Barbara Jensen Vorster, Senior Executive Manager, Communications and Marketing of the Gautrain Management Agency (GMA), in Midrand South Africa, considered her dilemma of adapting their communication approach during COVID-19 and beyond the current crisis. The GMA relied on traditional media and the crisis created an opportunity to rethink their entire communications approach. It was important to the GMA communications team to keep the Gautrain commuters connected even though they might not be using the Gautrain during the lockdown of COVID-19. Jensen Vorster believed that a brand should be adaptive and continue even when a service is not running. Jensen Vorster had to lead her communications team when they were all working from home, and they had to keep commuters informed of the requirements during the different levels of lockdown in South Africa. Their various campaigns during this time purposefully communicated with commuters and the various “staying home” initiatives with the intention of lifting spirits. The communication outreach during the COVID-19 pandemic switched over to social media communications out of necessity; however, was that ideal communication during a crisis? While most of the case focuses on this external communication, the case pays attention to some internal communication initiatives by Jensen Vorster with her own team and for the Gautrain’s staff. The question is whether brands should shift from traditional media to new media campaigns during the 21st-century crises? Students will get the opportunity to compare the use of traditional and new media during crisis times. How might they approach their brand communications during COVID-19 and in preparation for future crises? Complexity academic level Marketing and Business Communications and Leadership courses for MBA or executive education programs. Study level/applicability Masters level MBA. Research method The team of authors conducted face-to-face interviews prior to and during the lockdown in South Africa; the interviews were conducted online through Zoom. Interviews included Dr Barbara Jensen Vorster, Senior Executive Manager, Communications and Marketing of the Gautrain Management Agency and Kesagee Nayager, the Marketing and Communications Executive Manager at Bombela Concession Company. Viwe Mgedzi, Executive Manager for Knowledge Management, provided documents supporting the case. The researchers also conducted desktop research of secondary data, including media and press articles on the companies. The @Gautrain Twitter feed was very important for the researchers to investigate as part of the secondary data research, to triangulate the interview data. For example, see one of the Twitter feeds on 17 March 2020, 5:37 pm. The following Twitter feed on the Gautrain’s status confirmed the interview data: https://twitter.com/TheGautrain/status/1239938937885466633 The main resources of this case study were the interviews and the media articles to offer objective references. The authors used the following two newspaper articles to triangulate the information they gained from the interviews: BusinessTech, March 18, 2020, accessed March 8, 2021 at https://businesstech.co.za/news/lifestyle/382707/south-african-coronavirus-cases-jumps-to-116-as-a-gautrain-exec-tests-positive/ Timeslive, www.timeslive.co.za/news/south-africa/2020-03-17-staff-in-self-isolation-after-executive-tests-positive-two-gautrain-stations-chemically-decontaminated/ Supplementary materials Teaching notes are available for educators only. Subject code CSS 7: Management science; CSS 8: Marketing.

Development and Evaluation of a Cellular Vehicle-to-Everything Enabled Energy-Efficient Dynamic Routing Application.

Cellular vehicle-to-everything (C-V2X) is a communication technology that supports various safety, mobility, and environmental applications, given its higher reliability properties compared to other communication technologies. The performance of these C-V2X-enabled intelligent transportation system (ITS) applications is affected by the performance of the C-V2X communication technology (mainly packet loss). Similarly, the performance of the C-V2X communication is dependent on the vehicular traffic density which is affected by the traffic mobility patterns and vehicle routing strategies. Consequently, it is critical to develop a tool that can simulate, analyze, and evaluate the mutual interactions of the transportation and communication systems at the application level to quantify the benefits of C-V2X-enabled ITS applications realistically. In this paper, we demonstrate the benefits gained when using C-V2X Vehicle-to-Infrastructure (V2I) communication technology in an energy-efficient dynamic routing application. Specifically, we develop a Connected Energy-Efficient Dynamic Routing (C-EEDR) application using C-V2X as a communication medium in an integrated vehicular traffic and communication simulator (INTEGRATION). The results demonstrate that the C-EEDR application achieves fuel savings of up to 16.6% and 14.7% in the IDEAL and C-V2X communication cases, respectively, for a peak hour demand on the downtown Los Angeles network considering a 50% level of market penetration of connected vehicles. The results demonstrate that the fuel savings increase with increasing levels of market penetration at lower traffic demand levels (25% and 50% the peak demand). At higher traffic demand levels (75% and 100%), the fuel savings increase with increasing levels of market penetration with maximum benefits at a 50% market penetration rate. Although the communication system is affected by the high density of vehicles at the high traffic demand levels (75% and 100% the peak demand), the C-EEDR application manages to perform reliably, producing system-wide fuel consumption savings.The C-EEDR application achieves fuel savings of 15.2% and 11.7% for the IDEAL communication and 14% and 9% for the C-V2X communication at the 75% and 100% market penetration rates, respectively. Finally, the paper demonstrates that the C-V2X communication constraints only affect the performance of the C-EEDR application at the full demand level when the market penetration of the connected vehicles exceeds 25%. This degradation, however, is minimal (less than a 2.5% reduction in fuel savings).

A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges

Long-range (LoRa) technology is most widely used for enabling low-power wide area networks (WANs) on unlicensed frequency bands. Despite its modest data rates, it provides extensive coverage for low-power devices, making it an ideal communication system for many internet of things (IoT) applications. In general, LoRa is considered as the physical layer, whereas LoRaWAN is the medium access control (MAC) layer of the LoRa stack that adopts a star topology to enable communication between multiple end devices (EDs) and the network gateway. The chirp spread spectrum modulation deals with LoRa signal interference and ensures long-range communication. At the same time, the adaptive data rate mechanism allows EDs to dynamically alter some LoRa features, such as the spreading factor (SF), code rate, and carrier frequency to address the time variance of communication conditions in dense networks. Despite the high LoRa connectivity demand, LoRa signals interference and concurrent transmission collisions are major limitations. Therefore, to enhance LoRaWAN capacity, the LoRa Alliance released many LoRaWAN versions, and the research community has provided numerous solutions to develop scalable LoRaWAN technology. Hence, we thoroughly examine LoRaWAN scalability challenges and state-of-the-art solutions in both the physical and MAC layers. These solutions primarily rely on SF, logical, and frequency channel assignment, whereas others propose new network topologies or implement signal processing schemes to cancel the interference and allow LoRaWAN to connect more EDs efficiently. A summary of the existing solutions in the literature is provided at the end of the paper, describing the advantages and disadvantages of each solution and suggesting possible enhancements as future research directions.

Compressed Differentially Private Distributed Optimization with Linear Convergence

This paper addresses the problem of differentially private distributed optimization under limited communication, where each agent aims to keep their cost function private while minimizing the sum of all agents’ cost functions. In response, we propose a novel Compressed differentially Private distributed Gradient Tracking algorithm (CPGT). We demonstrate that CPGT achieves linear convergence for smooth and strongly convex cost functions, even with a class of biased but contractive compressors, and achieves the same accuracy as the idealized communication algorithm. Additionally, we rigorously prove that CPGT ensures differential privacy. Simulations are provided to validate the effectiveness of the proposed algorithm.

Intelligent Reflecting Surface-Assisted Physical Layer Key Generation with Deep Learning in MIMO Systems

Physical layer secret key generation (PLKG) is a promising technology for establishing effective secret keys. Current works for PLKG mostly study key generation schemes in ideal communication environments with little or even no signal interference. In terms of this issue, exploiting the reconfigurable intelligent reflecting surface (IRS) to assist PLKG has caused an increasing interest. Most IRS-assisted PLKG schemes focus on the single-input-single-output (SISO), which is limited in future communications with multi-input-multi-output (MIMO). However, MIMO could bring a serious overhead of channel reciprocity extraction. To fill the gap, this paper proposes a novel low-overhead IRS-assisted PLKG scheme with deep learning in the MIMO communications environments. We first combine the direct channel and the reflecting channel established by the IRS to construct the channel response function, and we propose a theoretically optimal interaction matrix to approach the optimal achievable rate. Then we design a channel reciprocity-learning neural network with an IRS introduced (IRS-CRNet), which is exploited to extract the channel reciprocity in time division duplexing (TDD) systems. Moreover, a PLKG scheme based on the IRS-CRNet is proposed. Final simulation results verify the performance of the PLKG scheme based on the IRS-CRNet in terms of key generation rate, key error rate and randomness.

Nonviolent resistance as a strategy of agitation - impeding or promoting unity through communication in South Africa?

This article focuses on the idea of nonviolent resistance as a strategy of agitation and whether it can help to promote unity through communication in South Africa. By means of critical-analytical argumentation key aspects of nonviolent resistance are posited, placed in historical context, and applied to socio-political reality In South Africa. It is concluded that nonviolent resistance efforts create a greater awareness of stumbling blocks that impede the promotion of Ideal communication (as mutual understanding) among all the social groups in South Africa. However, the dilemma of organising nonviolent actions responsibly, that is in such a way that they do not violate the human rights of others, remains.

Status update control based on reinforcement learning in energy harvesting sensor networks

With the development of the Internet of Things, more and more sensors are deployed to monitor the environmental status. To reduce deployment costs, a large number of sensors need to be deployed without a stable grid power supply. Therefore, on the one hand, the wireless sensors need to save as much energy as possible to extend their lifetime. On the other hand, they need to sense and transmit timely and accurate information for real-time monitoring. In this study, based on the spatiotemporal correlation of the environmental status monitored by the sensors, status information estimation is considered to effectively reduce the information collection frequency of the sensors, thereby reducing the energy cost. Under an ideal communication model with unlimited and perfect channels, a status update scheduling mechanism based on a Q-learning algorithm is proposed. With a nonideal channel model, a status update scheduling mechanism based on deep reinforcement learning is proposed. In this scenario, all sensors share a limited number of channels, and channel fading is considered. A finite state Markov chain is adopted to model the channel state transition process. The simulation results based on a real dataset show that compared with several baseline methods, the proposed mechanisms can well balance the energy cost and information errors and significantly reduce the update frequency while ensuring information accuracy.

A distributed secondary voltage and frequency controller considering packet dropouts and communication delay

In this paper, the consensus problem is developed for AC Microgrids (MGs) considering communication delay and packet dropouts. The existing control schemes commonly design the secondary control layer assuming ideal communication channels between distributed generation (DG) units. However, in practical situations, the communication links are exposed to packet dropout and delays which can drastically decrease the quality and stability of DGs controllers. Most of the existing literature studies the impact of delay or packet dropout, and the simultaneous effects of both delay and packet dropout in the communication links considering the rigorous stability analysis and statistical properties are proposed in this paper. Therefore, we propose a new distributed control approach to restore the voltage and frequency to the reference values using the collected sample-based technique of each DG unit. In addition, sufficient consensusability conditions are found when the communication network topology, the DG dynamics, the packet dropout rates, and the communication delay are taken into account. The consensus error of the proposed control strategy is determined, and its convergence is shown. Finally, the proposed method is simulated for different scenarios in MATLAB/SimPowerSystems environment to prove the effectiveness of the proposed secondary control scheme.

Communication process in order to maintain mental health during the COVID-19 pandemic among indonesian students

This research conducted to analyze in depth about the communication process that started from the psychological (mental) symptoms that arise during the pandemic, communication partners, ideal communication approaches, and messages that conveyed in order to maintain mental health of students in Indonesia during the Covid-19. Through qualitative approach with case study method, this research is expected to provide a deeper understanding of the researched problem. Researchers paid attention and examined an issue of interest, and used a single case as an instrument to describe it in detail. Result of this research showed that students are very at risk for mental health disorders during the pandemic. Symptoms that they experienced are anxiety disorders, stress, burnout, depression, loneliness and relationship problems. Family and friends are the most appropriate communication partners during the pandemic. The pandemic creates a revolution momentum to restore the role of the family for children. Interpersonal communication is still considered as the most ideal approach. The majority communication messages are emotional, spiritual and motivational messages. As a result of this research, it is hoped that the government and universities will increase the awareness of students' mental health because of the lack of counseling related to mental health for students.

FACTORS AFFECTING COMMUNICATION BETWEEN TEACHER AND SCHOOL ADMINISTRATOR

The aim of this research is to examine the effects of the communication skills of primary and secondary school principals, the communication established between administrators and teachers, on educational activities, school organization and school climate. A total of 12 primary and secondary school principals working in primary and secondary schools participated in this study, which was carried out in a qualitative research method and case study pattern. Easily accessible sampling, one of the purposive sampling methods, was used to determine the participants of the study. In the collection of research data, a semi-structured interview form prepared by the researcher in accordance with the relevant literature and the aims of the research was used. Descriptive analysis was used in the analysis of the data. At the end of the research, the following conclusions were reached: In the communication of the administrators and teachers working in primary and secondary schools, there is a communication disorder caused by not trying to understand each other between the parties, there is no respect and understanding towards each other in the communication between the administrators and the teachers, and education, seminar and group activities are needed to ensure a healthier communication of the participants. It has been determined that administrators and teachers believe that their communication can be increased by organizing meetings. It has been suggested that the ideal communication between administrators and teachers should be in mutual respect, trust and sincerity.

Parent-Child Sexual Communication Frequency and Adolescent Disclosure to Mothers About Sexuality: The Moderating Role of Open Communication in a Common Fate Structural Equation Model

ABSTRACT Although frequent and open parent–child sexual communication (PCSC) has been shown to yield positive effects on adolescent sexual health outcomes, most PCSC is one-sided and parent dominated rather than ideal communication characterized by openness. Adolescent children’s disclosure of sexual feelings and behaviors to parents can prompt parent–child sexual communication (PCSC) and help parents tailor PCSC to children’s needs, increasing the effectiveness of PCSC in promoting positive sexual outcomes. However, very little work has been done exploring correlates of adolescent disclosure about sexuality. Thus, the current study explored the associations between frequent PCSC and child disclosure and secret keeping, and whether open PCSC moderated the relationships. The sample included 603 mother–child dyads from the United States. Adolescent children were 12–17 years old (M = 14.55, SD = 1.68), White (55.6%) and cisgender female (49.8%). A common-fate SEM model revealed that PCSC frequency was positively associated with adolescent disclosure and adolescent secret keeping. However, when PCSC was open, PCSC frequency was associated with a decrease in adolescent secret keeping and an increase in adolescent disclosure. We discuss the importance of encouraging both open and frequent PCSC, as their interaction is related to increased adolescent disclosure and less adolescent secret keeping.

Entanglement teleportation in anisotropic Heisenberg XY spin model with Herring–Flicker coupling

In this paper, the features of quantum teleportation of a maximally entangled input thermal state using a system, consisting of two qubits (spin-1/2) anisotropic XY Heisenberg model with Herring–Flicker coupling in the presence of a magnetic field, are discussed. So, we study the influence on the thermal entanglement of different physical parameters such as temperature [Formula: see text], magnetic field [Formula: see text], degree of anisotropy [Formula: see text] and distance [Formula: see text] between the two spins. The goal is to determine the conditions of use of the system as a good channel to promote quantum teleportation. The amount of output entanglement is quantified by the concurrence [Formula: see text], and the quality of teleportation is analyzed using the concept of fidelity [Formula: see text]. It is shown that [Formula: see text] presents a maximum at extremely low temperature for a large range of the parameter [Formula: see text]. Also, when we increase the temperature, we observe a dissipation of the appropriate range of [Formula: see text] and the decrease of the amplitude of [Formula: see text]. Besides, under an external magnetic field [Formula: see text], we show the appearance of quantum phase transitions with the entanglement vanishing when the condition [Formula: see text] is fulfilled, then the system can ensure the ideal communication transmission. Concerning the Ising model [Formula: see text] in the ground state, the output entanglement is nonzero only in the presence of the magnetic field [Formula: see text], and this model is useful for ensuring a distorted transmission. At finite temperature, the fidelity [Formula: see text] is less than the value 2/3, so that the system is useless as a quantum channel for providing quantum teleportation.

Communication During Interhospital Transfers of Emergency General Surgery Patients: A Qualitative Study of Challenges and Opportunities.

Transferred emergency general surgery (EGS) patients experience worse outcomes than directly admitted patients. Improving communication during transfers may improve patient care. We sought to understand the nature of and challenges to communication between referring (RP) and accepting (AP) providers transferring EGS patients from the transfer center nurse's (TCN) perspective. Guided by the Relational Coordination Framework, we interviewed 17 TCNs at an academic medical center regarding (in)efficient and (in)effective communication between RPs and APs. In-person interviews were recorded, transcribed, and managed in NVivo. Four researchers developed a codebook, cocoded transcripts, and met regularly to build consensus and discuss emergent themes. We used data matrices to perform constant comparisons and arrive at higher-level concepts. Challenges to ideal communication centered on the appropriateness and completeness of information, efficiency of the conversation, and degree of consensus. Transfer center nurses described that RPs provided incomplete information because of a lack of necessary infrastructure, personnel, or technical knowledge; competing clinical demands; or a fear of the transfer request being rejected. Inefficient communication resulted from RPs being unfamiliar with the information APs expected and the lack of a structured process to share information. Communication also failed when providers disagreed about the necessity of the transfer. Accepting providers diffused tension and facilitated communication by embracing the role of a "coach," negotiating "wait-and-see" agreements, and providing explanations of why transfers were unnecessary. Transfer center nurses described numerous challenges to provider communication. Opportunities for improvement include sharing appropriate and complete information, ensuring efficient communication, and reaching consensus about the course of action.