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The article discusses promising methods of data transmission using laser radiation. A comparative analysis of optical (non-laser) and laser communication was conducted, and experimental modeling of two channels was performed, including a mock-up. The optical communication channel model is based on an amplitude-modulated infrared (IR) LED and a narrowly focused laser transmitter. The model of the laser communication channel included a semiconductor laser source and a phototransistor receiver. As part of the work, the main characteristics of these communication channels were evaluated, including the maximum data transfer rate, maximum communication range, and quantitative measures of noise immunity for both channels. Significant differences were revealed, in particular, packet errors of 3–5 bits in a row were observed in the IR channel, which is explained by the inertia of the analog circuits of the receiving part. The laser system, on the contrary, demonstrated a uniform distribution of single errors due to the discrete nature of interference from background illumination. The article shows that both methods of organizing communication can be effectively used for information exchange tasks with a short distance between objects, particularly in groups of unmanned aerial vehicles.

Purpose This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation. Design/methodology/approach This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity. Findings This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers. Research limitations/implications The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings. Practical implications This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS. Originality/value This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

The effectiveness of collaboration in distributed networks, such as sensor networks and multi-agent systems, relies on nodes’ ability to exchange information. The availability of various communication protocols with different technical properties opens the possibility to guarantee connectivity during a system’s operation in any condition. A communication network can be represented by a graph on which connectivity can be expressed by a well-known algebraic connectivity value or Fiedler value. It is one of the most important tools used in many applications where connectivity preservation is required. In this paper, a trust-based consensus algorithm for algebraic connectivity estimation has been implemented. To guarantee the accomplishment of the global objective and the system’s performance, our contributions include: (i) a novel decentralized framework for combining multiple communication channels in a resulting channel and (ii) a decentralized algebraic connectivity control law that dynamically changes the number of agents in the system during operation. The proposed algebraic connectivity control strategy has been evaluated in simulations and in a real multi-robot system using two channels with different properties and initial topologies.

Wireless Underground Sensor Networks (WUSNs) have been showing prospective supervising application domains in the underground region of the earth through sensing, computation, and communication. This paper presents a novel Deep Learning (DL)-based Cooperative communication channel model for Wireless Underground Sensor Networks for accurate and reliable monitoring in hostile underground locations. Furthermore, the proposed communication model aims at the effective utilization of cluster-based Cooperative models through the relay nodes. However, by keeping the cost effectiveness, reliability, and user-friendliness of wireless underground sensor networks through inter-cluster Cooperative transmission between two cluster heads, the determination of the overall energy performance is also measured. The energy co-operative channel allocation routing (ECCAR), Energy Hierarchical Optimistic Routing (EHOR), Non-Cooperative, and Dynamic Energy Routing (DER) methods were used to figure out how well the proposed WUSN works. The Quality of Service (QoS) parameters such as transmission time, throughput, packet loss, and efficiency were used in order to evaluate the performance of the proposed WUSNs. From the simulation results, it is apparently seen that the proposed system demonstrates some superiority over other methods in terms of its better energy utilization of 89.71%, Packet Delivery ratio of 78.2%, Average Packet Delay of 82.3%, Average Network overhead of 77.4%, data packet throughput of 83.5% and an average system packet loss of 91%.

PurposeThis study aimed to test the relationship between various communication channels (in person, on screen, on the phone, messaging), the team feeling and perceived support by colleagues under different intensities of telework.Design/methodology/approachEuropean Social Survey (ESS) Round 10 (2020–22) data file edition 3.0 was used for data analysis. The sample of this study consisted of 9,500 workers from ISCO groups 1–4 from 19 European Union countries. Latent profile analysis was used to analyse the data.FindingsFive communication and telework intensity profiles were revealed: solo office workers, connected teleworkers, solo teleworkers, all-mode office communicators and office classics. Demographic and professional characteristics predicted employees’ membership in specific telework and communication channel profiles. The significant between-profile differences regarding one’s team feelings and perceived support from colleagues were observed. The highest levels of team feeling and expectations of getting work-related help from colleagues were observed among office classics, characterised by all types of communication except on-screen communication. On the contrary, solo teleworkers who worked from home and rarely used all multi-mode communication channels to contact their colleagues reported the lowest levels of team feeling and social support.Originality/valueUsing representative data from 19 European countries (N = 9,500), this study provides insight into how combinations of telework intensity and communication forms relate to different levels of team feeling and perceived support among colleagues. It highlights the importance of using diverse communication for maintaining social support and team cohesion.

The 5G deployment brings forth the usage of Unmanned Aerial Vehicles (UAV) to assist wireless networks by providing improved signal coverage, acting as relays or base-stations. Another technology that could help achieve 5G massive machine-type communications (mMtc) goals is the Long Range Wide-Area Network (LoRaWAN) communication protocol. This paper studied these complementary technologies, LoRa and UAV, through measurement campaigns in suburban, densely forested environments. Downlink and uplink communication at different heights and spreading factors (SF) demonstrate distinct behavior through our analysis. Moreover, a neural network was trained to predict the measured signal-to-noise ratio (SNR) behavior and results compared with SNR regression models. For the downlink scenario, the neural network results show a root mean square error (RMSE) variation between 1.2322–1.6623 dB, with an error standard deviation (SD) less than 1.6730 dB. For the uplink, the RMSE variation was between 0.8714–1.3891 dB, with an error SD less than 1.1706 dB.

For nonlinear multilateral teleoperation systems, unreliable communication channels and actuator constraints are the main challenging issues to achieve the stability condition and satisfy the required performance. In this paper, a novel fault-tolerant control algorithm is proposed for a class of multi-degree-of-freedom nonlinear multilateral teleoperation systems with the aforementioned problems and unknown environmental forces. The time-varying delays and packet dropouts are incorporated in the unreliable communication channels, and the considered systems are modeled as a kind of T-S fuzzy systems with multiple time-varying delays. For actuator constraints, both the actuator failures and the unknown control directions are investigated in such research, by designing a novel fault-tolerant control scheme, the failures and control directions can be estimated simultaneously. Next, the radial basis function neural network (RBFNN) is introduced to estimate the unknown environmental force, and the estimated results are incorporated in the controller design and the mean-square stability of the closed-loop system with disturbance attenuation level is guaranteed. Finally, a numerical simulation example is given to show the effectiveness of the proposed method.

•An interaction-centric approach was developed to quantify human reciprocal interaction.•Brain response to reciprocal interaction was distinguished from non-reciprocal responses.•The interaction is quantified by an interaction matrix based on reciprocal brain responses.•The interaction induced brain states are characterized by the communication channels from interaction matrix decomposition, as well as the mutual information in all channels.•The interaction-centric approach is applied to study parent-child eye contact. This study presents an interaction-centric framework for analytically investigating brain-to-brain dynamics during eye contact, advancing beyond the traditional spectator model. The foundation of the interactor approach is to delineate the interaction. To achieve this, simultaneous brain activity engaged in eye contact was captured using hyperscanning fMRI. The BOLD responses were first divided into eye-to-eye reciprocal interaction and eye-to-face non-reciprocal communication based on the experimental design; then the reciprocal interaction response was further differentiated into sensory-based (exogenous) and mind-based (endogenous) components to characterize agentic interaction. The proposed interactor approach not only determines interaction from dyadic brain states but also computes emergent interactive brain states arising from the interaction. To achieve these, reciprocal interactive fMRI responses were quantified into an interaction matrix, from which interaction-induced communication channels were identified using Correspondence Analysis, and information flow within those channels was measured with Mutual Information. The advantage of the interactor approach is its ability to reveal emergent dyadic brain states that a spectator approach cannot fully unravel. When applied to parent-child eye contact, this method confirmed existing developmental findings, clarified previous inconsistencies, and uncovered new insights into how reciprocal social engagement shapes brain function.

Visible Light Communication (VLC) has the potential to advance Intelligent Transportation Systems (ITS). This study explores the current advancements of VLC in ITS applications that may enhance traffic flow, road safety, and vehicular communication performance. The potential, benefits, and current research trends of VLC in ITS applications are discussed first. Then, the state-of-the-art VLC technologies including overall concept, IEEE communication protocols, hybrid VLC systems, and software-defined adaptive MIMO VLC systems, are discussed. We investigated different potential applications of VLC in ITS, such as signalized intersection and ramp metering control, collision warning and avoidance, vehicle localization and detection, and vehicle platooning using vehicle–vehicle (V2V), infrastructure–vehicle (I2V), and vehicle–everything (V2X) communications. Besides, VLC faces several challenges in ITS applications, and these concerns, e.g., environmental issues, communication range issues, standards and infrastructure integration issues, light conditions and integration issues are discussed. Finally, this paper discusses various advanced techniques to enhance VLC performance in ITS applications, such as machine learning-based channel estimation, adaptive beamforming, robust modulation schemes, and hybrid VLC integration. With this review, the authors aim to inform academics, engineers, and policymakers about the status and challenges of VLC in ITS. It is expected that, by applying VLC in ITS, mobility will be safer, more efficient, and sustainable.

Industry 4.0 describes a phenomenon which augments business models and also communication channels in commercial enterprises. This paper analyses scientific publications related to the business model changes driven by Industry 4.0, and also digital internal communication channels used to reduce risks in the process. The paper is based upon a systematic review of scientific publications and evaluation by experts. The research revealed a gap between internal communication through digital channels and the change process in Industry 4.0-driven business models. Each channel has its mission and contributes to reducing risk during the change process. Since there is no universal digital channel for internal communication, different digital communication channels are efficient at different stages of change. The paper makes recommendations for enterprises, related to the effectiveness of digital communication channels during the business model transformation. It further contributes to existing knowledge by expanding the change process model and aligning the change process with features of digital communication channels. The research focused on the manufacturing sector, exploring digital communication channels used to reduce risk during the change process, which is a limitation of this study, along with assumption of a basic level of digital competences in the enterprise.