Power Communication Research Articles

A Graph Reinforcement Learning-Based Handover Strategy for Low Earth Orbit Satellites under Power Grid Scenarios

Amidst the escalating need for stable power supplies and high-quality communication services in remote regions globally, due to challenges associated with deploying a conventional power communication infrastructure and its susceptibility to natural disasters, LEO satellite networks present a promising solution for broad geographical coverage and the provision of stable and high-speed communication services in remote regions. Given the necessity for frequent handovers to maintain service continuity, due to the high mobility of LEO satellites, a primary technical challenge confronting LEO satellite networks lies in efficiently managing the handover process between satellites, to guarantee the continuity and quality of communication services, particularly for power services. Thus, there is a critical need to explore satellite handover optimization algorithms. This paper presents a handover optimization scheme that integrates deep reinforcement learning (DRL) and graph neural networks (GNN) to dynamically optimize the satellite handover process and adapt to the time-varying satellite network environment. DRL models can effectively detect changes in the topology of satellite handover graphs across different time periods by leveraging the powerful representational capabilities of GNNs to make optimal handover decisions. Simulation experiments confirm that the handover strategy based on the fusion of message-passing neural network and deep Q-network algorithm (MPNN-DQN) outperforms traditional handover mechanisms and DRL-based strategies in reducing handover frequency, lowering communication latency, and achieving network load balancing. Integrating DRL and GNN into the satellite handover mechanism enhances the communication continuity and reliability of power systems in remote areas, while also offering a new direction for the design and optimization of future power system communication networks. This research contributes to the advancement of sophisticated satellite communication architectures that facilitate high-speed and reliable internet access in remote regions worldwide.

Relatively important node identification for cyber–physical power systems based on relatively weighted entropy

In recent years, a large number of scholars have paid attention to the identification of vital nodes of cyber–physical power systems. However, in addition to these vital nodes, other relatively important nodes in the system have important research significance. For example, when a vital node in the system has been damaged, avoiding further damage is particularly important. We can obtain useful information from these vital nodes and find out which nodes are relatively important for these nodes to protect, which can prevent further cascading of failures to some extent. In this paper, we aim to identify the relatively important nodes and define the connection tightness index of any two nodes. By combining these indexes with relative entropy, we can correctly measure the degree of difference between any two nodes and sort them to determine the relative importance of nodes. The results show that the proposed strategy can evaluate relatively important nodes without distinguishing between power network and communication network. It is also possible to identify nodes that are relatively important to the network on one side of the cyber–physical power system by the importance of the network nodes on the other side, and this is superior to other strategies.

Generation Z's Trust in Mainstream Media and Social Media in Indonesia and Lebanon

This study investigates Generation Z's trust in mainstream and social media in Indonesia and Lebanon. Using a descriptive research design and survey method, data were collected from 114 respondents through Google Forms in April 2022, including students from Universitas Islam Negeri Sunan Ampel (UINSA) Surabaya and participants from @iCademy in Lebanon. The research explores the critical role of mainstream media in modern information dissemination and social media as a powerful communication tool. The results indicate that while social media is widely used, mainstream media maintains credibility due to its verified information. The findings emphasize the importance of reliable information sources for Generation Z, especially in predominantly Muslim contexts where ethical standards and factual accuracy are crucial. These findings suggest that media organizations must uphold high journalistic standards to retain the trust of young audiences.

"The Power of Clear Communication: Health Literacy and Randomized Controlled Trials of Infection Control Measures in Italy Linked to the Recent Surge of Pertussis and Measles Cases"

"The Power of Clear Communication: Health Literacy and Randomized Controlled Trials of Infection Control Measures in Italy Linked to the Recent Surge of Pertussis and Measles Cases"

Uncovering Employee Engagement in the Power of Leadership, Communication, and Teamwork Study

This study investigates the impact of servant leadership, communication, and teamwork on employee engagement at PT Irawan Djaja Agung, aiming to address a gap in research regarding their combined influence in Indonesian organizations. Through a quantitative survey of 70 employees and analysis using Smart-PLS Version 3.0, the research finds significant positive relationships between servant leadership, communication, teamwork, and employee engagement. The results highlight the importance of nurturing supportive leadership, enhancing communication channels, and fostering teamwork to bolster employee engagement. Organizational leaders are urged to consider implementing recognition and reward systems, while employees are encouraged to strengthen interpersonal relationships for improved collaboration. Further research could delve into additional factors affecting employee engagement in similar contexts. Highlight: Synergy of Leadership, Communication, Teamwork. Quantitative Analysis with Smart-PLS. Actionable Insights for Organizational Improvement. Keyword: Servant leadership, Communication, Teamwork, Employee engagement, Organizational development

Alteration in neural oscillatory activity and phase‐amplitude coupling after sleep deprivation: Evidence for impairment and compensation effects

SummaryInsufficient sleep can significantly affect vigilance and increase slow‐wave electroencephalographic power as homeostatic sleep pressure accumulates. Phase‐amplitude coupling is involved in regulating the spatiotemporal integration of physiological processes. This study aimed to examine the functional associations of resting‐state electroencephalographic power and delta/theta‐gamma phase‐amplitude coupling from the prefrontal cortex (PFC) to posterior regions with vigilance performance after sleep deprivation. Forty‐six healthy adults underwent 24‐hr sleep deprivation with resting‐state electroencephalographic recordings, and vigilant attention was measured using the Psychomotor Vigilance Task. Power spectral and phase‐amplitude coupling analyses were conducted, and correlation analysis was utilized to reveal the relationship between electroencephalographic patterns and changes in vigilance resulting from sleep deprivation. Sleep deprivation significantly declined vigilance performance, accompanied by increased resting‐state electroencephalographic power in all bands and delta/theta‐gamma phase‐amplitude coupling. The increased theta activity in centro‐parieto‐occipital areas significantly correlated with decreased mean and slowest response speed. Conversely, the increased delta‐low gamma and theta‐high gamma phase‐amplitude couplings negatively correlated with the deceleration of the fastest Psychomotor Vigilance Task reaction times. These findings suggest that sleep deprivation affects vigilance by altering electroencephalographic spectral power and information communication across frequency bands in different brain regions. The distinct effects of increased theta power and delta/theta‐gamma phase‐amplitude coupling might reflect the impairment and compensation of sleep deprivation on vigilance performance, respectively.

SP-SAT: DEVELOPMENT OF AN EDUCATIONAL SATELLITE

n Bolivia, as in several other Latin American nations, there is a growing trend of burgeoning space projects and a rising interest among young students in the aerospace domain. Consequently, there arises an imperative to cultivate a new generation of space professionals. However, the exorbitant costs associated with the equipment utilized in these projects render them inaccessible to a vast majority of inter- ested students, including CubeSat kits, educational satellites, satellite kits, among others. Consequently, alternatives like educational sat- ellites have emerged to simulate the satellite design, construction, testing, launch, and operation processes on a scale conducive to student involvement. The primary challenge faced by students lies in integrating the essential subsystems of a satellite, encompassing power supply, sensors, and communication systems, within the confines of limited space. Considering this, the design and construction of an educational satellite with its respective signal reception equipment was developed. The equipment designed and manufactured is a low-cost one so that universities and educational centers could acquire it. This equipment educational kit is called SP-SAT (Space Program — educational satellite kit). This real satellite simulator offers a wide variety of educational activities. The kit’s equipment is distributed in two systems: 1) Space Segment, which consists of an Onboard Computer (OBC), Electrical Power System (EPS), Communications System (COMM), Experiment Plate (PYL), Complete PLA plastic structure (3D printed), rods, bolts, and nuts. 2) Ground segment: This segment includes all the equipment that is part of the ground station, which will receive data from the satellite.

Flexible resource demand response scheduling strategy under 5G-V2X

Electric vehicles (EV) and 5 G base stations, functioning as flexible load resources, contribute significantly to the provision of ample reserve capacity for the power grid. The emergence of 5 G Vehicle-to-Everything (V2X) technology has fostered a coupling between EV and base stations, further enhancing their roles within the power grid. Building upon this foundation, this paper proposes a scheduling strategy for demand response in flexibility resources under the 5 G-V2X framework. Initially, the dispatchable load of EV is examined in conjunction with the traffic network. Subsequently, we consider the communication power consumption resulting from the connected vehicle model, enabling us to devise path planning and charging navigation strategies for EV. Lastly, we establish a scheduling decision model that aims to minimize both the operation costs of base stations and the variance in grid load. The simulation is validated using real-world road conditions in the primary urban area of a city. The findings illustrate that the proposed dispatching strategy not only achieves a mutually beneficial outcome for EV users and aggregators, without disrupting EV charging and discharging processes, but also enhances the capability of demand response, thereby ensuring reliable grid operation.

Infiltrating Functional English for Technical Students with the Concomitant of Project Transcripts: A Paradigm in Education

A powerful communication strategy plays a key role in professional settings, all the while demonstrating its ability to garner admiration and respect. Over time, Language is an ever-evolving system from a usage standpoint. Despite several existing methods, the quality of knowledge of technical communication remains a persistent challenge for non-native speakers at the instructional level. This paper explores how engineering students can acquire an understanding of and practice functional technical English by preparing micro and macro projects. This study examined 200 student projects, each comprising 20 pages and approximately 300 lines. These projects serve for statistical analysis and are evaluated based on specific five test areas, such as usage of tense, change of voice, concord, vocabulary, and connectors. The two groups (EG & CG) were offered pretest and post-test. The result of the analysis is interpreted with the help of line graphs that assess the comparability of the two groups. Remedial measures with sequence flow charts were suggested to the participants that served the purpose of mending their deficient areas, which, if believed, would enhance their career progression. This method would assist tertiary-level students in breaking language barriers, enabling them to express their ideas in writing and speaking more effectively using technical language, especially in the ordinary usage of technical means to explain complex technical principles. A language is language, when reflected in the correct sense with the ability to use it functionally rather than learning it for years.

Application of Internet of Things and embedded technology in electronic communication

In order to explore the energy-saving control method of electronic communication, the author proposes the application of Internet of Things and embedded technology in electronic communication. The application makes full use of the “Internet of Things” and embedded technology to create an energy-saving system, send data to the energy-saving system to control the power supply, and control operation of electrical appliances to achieve energy saving results. According to the test resultsThe energy consumption of the system designed by the author after energy saving is 4.8335kWh, which is lower than that of the device before energy saving, which is 5.8424kWh and saves electricity. At different load current, the system output voltage is controlled at 220 V and the performance of the system is stable. ConclusionThe system designed according to the model proposed by the author has a good performance in terms of energy consumption and has a connection with Internet technology and embedded technology in fire communication power.

Patent Trend Analysis of Unmanned Ground Vehicles(UGV) using Topic Modeling

This study provides a thorough examination of Unmanned Ground Vehicles(UGVs), focusing on crucial technologies and trends across major global markets. It includes an in-depth patent analysis revealing the dominant positions of the United States and the European Union in this field. Additionally, it underscores substantial advancements made by China, Japan, and Korea since 2010. Using Latent Dirichlet Allocation(LDA)-based patent text mining, the study identified key technology areas in UGV development, such as advanced control systems, navigation technologies, power supply mechanisms, and sensing and communication tools. Through linear regression analysis, the study predicted the future paths of these technology areas, offering important insights into the evolving world of UGV technology. The findings can provide strategic guidance for stakeholders in the defense, commercial, and academic sectors, pointing out the future directions in UGV advancements.

An Online Home Energy Management System using Q-Learning and Deep Q-Learning

The users of home energy management systems schedule their real-time energy consumption thanks to advancements in communication technology and smart metering infrastructures. In this paper, a data-driven strategy is proposed, which is an Online Home Energy Management System (ON-HEM) that uses reinforcement learning algorithms (Q-Learning and Deep Q-Learning) to control the optimal energy consumption of a smart home system. The proposed system comprises power resources (grid, photovoltaic), communication networks, and appliances with their agents classified into four groups: deferrable, non-deferrable, power level controllable, and electric vehicle. The system reduces electricity costs and high peak demands while considering the cost of user dissatisfaction with real-life data. Simulations are performed on the proposed ON-HEM considering different pricing approaches (Real Time Pricing and Time of Use Pricing) with Q-Learning and Deep Q-Learning (DQL) algorithms using PyCharm Professional Edition software. The findings demonstrate both the superiority of DQL over Q-Learning and the efficiency of the proposed ON-HEM in decreasing high peak demand, electricity costs, and customer dissatisfaction costs. The efficiency and dependability of the proposed system were verified by utilizing simulation-based findings with real-life data using IBM SPSS Statistics software.

Wirelessly Powered and Bi-Directional Data Communication System With Adaptive Conversion Chain for Multisite Biomedical Implants Over Single Inductive Link.

A wirelessly powered and data communication system is presented which is implemented as a full system, designed for multisite implanted biomedical applications. The system is capable of receiving wireless power and data communication for each implant separately, using inductive links with different resonance frequencies. To achieve this, dual-band coils are presented in the system. In addition, the system supports bi-directional half-duplex data communication, utilizing amplitude and load shift keying (ASK and LSK) modulation schemes over a single inductive link. The system employs a digitally assisted active rectifier and an automatic resonance tuning system, to improve the power transfer efficiency (PTE) through various coupling coefficients, while minimizing the reverse current and power dissipation. The power control unit enables closed-loop monitoring to prevent high or low power delivery, and it can detect inefficient or excessive wireless power transmission or prevent temperature elevation by limiting the voltage to a safe level. A new structure of self-sampling separated- Vb ASK demodulator is proposed in the paper which is utilized within the data conversion chain, serving both the external and implanted units. The whole system is fabricated using a standard 180-nm 1.8/3.3 V CMOS process with a core area of 0.82 mm[Formula: see text]. The system is tested with coupled multisite inductive links and offers the maximum overall PTE of 31.2%, from the Tx coil to the implant load.

Long-Term Throughput Maximization in Wireless Powered Communication Networks: A Multitask DRL Approach

Long-Term Throughput Maximization in Wireless Powered Communication Networks: A Multitask DRL Approach

A joint extraction method for fault text entity relationships in smart grid considering nested entities and complex semantics

Entity relationship extraction is the core task of text mining and intelligent retrieval, which can automatically extract the semantic relationships between entities. For a problem of low accuracy of information extraction due to semantic complexity and nested entities in the text in the field of electric power communication network, this paper proposes an Orth-Biaff-CasRel method for joint extraction of entity relationships in faulty text. The method incorporates the RoFormer of rotational position as a coding layer in the encoding process, capturing the relative positional relationships between entities in the text; In addition, considers the entity content information and entity boundary information, designs the head entity extraction method with Orthogonalized Biaffine attention mechanism. Finally, combining stacked pointers and adding hidden layers in the joint extraction of tail entities and relationships to achieve accurate extraction of information from complex semantic fault texts. The proposed method is experimentally verified in real fault texts of power communication networks and achieves good results, significantly outperforming the existing methods in terms of accuracy, recall and Fl value, with an improvement of 4.41 %,1.43 % and 2.92 %, respectively.

Research on a Fully Digital Simulation Training System for Power Communication EPON Equipment

Research on a Fully Digital Simulation Training System for Power Communication EPON Equipment

Cultural Research on Drug Users in Indonesia

This study aims to examine the construction of rehabilitation for drug users in Indonesia from various aspects using a literature review approach. The aspects discussed include rehabilitation policies, the role of family and community, societal stigma, as well as cultural perspectives such as identity, consumer culture, and regulatory frameworks. Additionally, this research employs Jurgen Habermas's theory of Communicative Power as its theoretical foundation. The method used is a literature review by examining various previous studies relevant to the topic of drug user rehabilitation. The results indicate that rehabilitation is constructed from policy aspects that still need improvement, the importance of family support, the need to eliminate societal stigma, the diverse identities of drug users, consumer culture related to residence and occupation, and regulatory frameworks encompassing societal regulations and values. The theory of Communicative Power highlights the importance of public space as a deliberative arena in the rehabilitation process involving drug users, families, communities, and other stakeholders. This research provides a comprehensive overview of the construction of drug user rehabilitation in Indonesia from various perspectives and aspects that need attention to enhance the effectiveness of rehabilitation programs.

The four frames of leadership and motivating language theory: Version 2.0

Purpose The purpose of this conceptual paper is to increase the clarity and application of the original model and integration table. Specifically, the intent was to increase clarity by highlighting elements left out of the original article (sentence frames), adding additional information on the medium of leadership practice through the addition of Bolman and Deal's leadership lessons, and improving the flow and structure of leader steps as leaders move across the model in the leader sequence of events. Finally, the model was tweaked to adjust the political frame across both direction-giving and empathetic language based on participant feedback and a literature review. Design/methodology/approach The approach of this conceptual paper is to continue the evolution of the integration of the Four-Frames and Motivating Language Theory (MLT) first presented in DLO in 2019 using updated literature from Bolman and Deal (2019, 2021) and feedback from real-world implementation of the contents from the original article. Findings The findings of this conceptual paper are in two forms. First, the Version 2.0 integration model illustrates greater clarity and an improved sequence for implementation by leaders to address the pressing issues they face. Second, the illustration of the sentence frames and their evolution from the original article (2019) to the current paper highlights the power and integration of the Four-Frames and Motivating Language Theory regarding their versatility and utilization as a critical thinking and teaching tool for leaders and organizations. Practical implications For practitioners, this conceptual paper provides additional information on how to implement the Four-Frames as leaders through the power and influence of leadership communication and action. Originality/value The value of the Version 2.0 integrated model continues to leverage the combination of the Four Frames and Motivating Language Theory, which is still unique in the research. This evolution of the integration creates greater clarity in terms of understanding and utilizing leadership, connecting and sequencing the Four-Frames and MLT together, and applying the Four-Frame(s) accurately. This article continues to extend the field of Motivating Language Theory and addresses a gap in the work of the Four Frames – communication.

Conflict Recovery in Socialist Utopia: A Critical Analysis of Vietnam's Postwar Reconstruction Policies Through a Visual Interpretation of 1976–1986 Propaganda Posters

The Vietnam War left a newly reunified Vietnam with innumerable challenges following the fall of Saigon in April 1975. Through an interpretive analytical approach using propaganda posters as the visual data source, this study examines how the Communist Party of Vietnam and the Vietnamese government disseminated economic, political, diplomatic, military, and social policies to the public in order to rally support for the ambitious goal of rebuilding the country as an industrialized socialist nation. In doing so, this study shows how a national reconstruction discourse could be modalized in textual, visual, and symbolic spaces to maximize its persuasiveness in conflict recovery efforts. Ultimately, this study demonstrates that while recovery is the utmost goal of governments following the end of conflicts, basing it on a specific ideology without careful examination of contextual factors can be deleterious and even calamitous. Propaganda posters can serve as a powerful communication tool for policy makers, but poorly aligned campaigns can be counterproductive.

Hybrid framework of fatigue: connecting motivational control and computational moderators to gamma oscillations.

There is a need to develop a comprehensive account of time-on-task fatigue effects on performance (i.e., the vigilance decrement) to increase predictive accuracy. We address this need by integrating three independent accounts into a novel hybrid framework. This framework unites (1) a motivational system balancing goal and comfort drives as described by an influential cognitive-energetic theory with (2) accumulating microlapses from a recent computational model of fatigue, and (3) frontal gamma oscillations indexing fluctuations in motivational control. Moreover, the hybrid framework formally links brief lapses (occurring over milliseconds) to the dynamics of the motivational system at a temporal scale not otherwise described in the fatigue literature. EEG and behavioral data was collected from a brief vigilance task. High frequency gamma oscillations were assayed, indexing effortful controlled processes with motivation as a latent factor. Binned and single-trial gamma power was evaluated for changes in real- and lagged-time and correlated with behavior. Functional connectivity analyses assessed the directionality of gamma power in frontal-parietal communication across time-on-task. As a high-resolution representation of latent motivation, gamma power was scaled by fatigue moderators in two computational models. Microlapses modulated transitions from an effortful controlled state to a minimal-effort default state. The hybrid models were compared to a computational microlapse-only model for goodness-of-fit with simulated data. Findings suggested real-time high gamma power exhibited properties consistent with effortful motivational control. However, gamma power failed to correlate with increases in response times over time, indicating electrophysiology and behavior relations are insufficient in capturing the full range of fatigue effects. Directional connectivity affirmed the dominance of frontal gamma activity in controlled processes in the frontal-parietal network. Parameterizing high frontal gamma power, as an index of fluctuating relative motivational control, produced results that are as accurate or superior to a previous microlapse-only computational model. The hybrid framework views fatigue as a function of a energetical motivational system, managing the trade-space between controlled processes and competing wellbeing needs. Two gamma computational models provided compelling and parsimonious support for this framework, which can potentially be applied to fatigue intervention technologies and related effectiveness measures.