Power Communication Research Articles

Harmony amidst dissonance: unveiling the power of open communication in resolving demarketing dilemmas

Harmony amidst dissonance: unveiling the power of open communication in resolving demarketing dilemmas

Research on Node Fault Diagnosis in Wireless Sensor Networks Based on a Constrained Data Maximum Entropy BN Parameter Learning Algorithm

Currently, power communication wireless sensor networks (WSNs) exhibit the characteristics of uncertainty and complexity. Furthermore, the application environment is more complex, resulting in nodes damaging easily, power communication breakdown, and economic losses. Dynamic monitoring of power communication WSN nodes is necessary. To this end, a constraint data maximum entropy Bayesian network (BN) parameter learning algorithm is used to solve the problem of small data sample size in monitoring and improve the quality of power communication WSN node fault diagnosis. After the latest verification, it is found that the correct rate of WSN node fault diagnosis under small data set is as follows: in normal conditions, the fault rate is 96%, the sensor fault is 94%, the power supply fault is 100%, the wireless communication fault is 90%, and the processor fault is 91%. It can be seen that even under small sample data sets, better diagnostic accuracy can be brought.

Talking Fingers: A Multilingual Speech-to-Sign Language Converter

Communication is a basic human need, but thousands of people with hearing and speech impairments face limitations in everyday communication "Talking Fingers" is a modern assistive technology tool that transfers spoken or written language to Indian Sign Language (ISL). With multilingual capabilities, the tool provides technologies such as Google ML Kit for language recognition, MyMemory API for translation, ISL grammar services for more than one language and several languages accessible at a time Translated ISL will, a it provides a simple and powerful communication channel. The system outlines the ability to blend artificial intelligence (AI) and language generation to promote inclusion and empower individuals with disabilities

The Role of Reflection for Continuing Professional Development of In-Service Health Care Professionals: A Narrative Inquiry in Four Health Professions.

Health care providers (HCPs) use reflection to intervene in complex, ambiguous clinical situations. Yet, there is scant evidence about the circumstances when HCPs use reflection and how they perceive reflection within their continuing professional development. We selected a narrative inquiry approach to study how HCPs perceive reflection's role in learning in four health professions. We invited 26 health professionals to a narrative interview conducted by a student in one of the four selected professions: medicine, nursing, occupational therapy, and speech-language pathology. The narrative events that make up the stories were analyzed and interpreted using structural analysis based on the narratives' historic-empirical and psycho-semantic dimensions. Physicians told us that reflection bolsters their clinical performance and confidence. Nurses told us that reflection allowed them to develop resilience as they sought to integrate their work setting and gain autonomy. Occupational therapists spoke of how reflection spurred them to innovate and extend the scope of their practice to advocate for their patients' health better. Speech-language pathologists described how they reflect on "educating" other HCPs about their profession and enhancing their communication skills with patients. The communicative power of storytelling allowed us to fathom what is hard to describe in words: how reflection builds clinical and psychosocial skills and introspective capacity. Hence, findings provide empirical evidence of reflection's perceived role in maintaining professional skills that make HCPs effective in complex, ambiguous situations.

A fault localization method for power communication fiber optic cable lines based on brillouin frequency shift features

A fault localization method for power communication fiber optic cable lines based on brillouin frequency shift features

하브루타 독서토론 수업의 교육적 의미 탐색 - G대학 교양 강좌 <독서와 토론> 교과 수업 사례를 중심으로

This study has the following two purposes. First, this study examines the educational implications of Havruta reading discussion classes in this era where high-tech and high-touch is emphasized. Second, the purpose is to check the effectiveness of the Havruta reading discussion class in terms of performance. In light of the results of running and reflecting on team-based havruta-style reading and discussion classes, it is thought that teaching and learning method of refining and expanding thoughts through havruta reading discussions instead of the instructor's one-sided teaching has the value of being used as a response strategy to the liberal arts education methodology in the era of great digital transformation. The concept of high touch, which is emphasized along with the active use of edutech due to the development of digital technology, is further highlighting the effectiveness and importance of learner-centered participatory education methods. It is concluded that reading and discussion, which ‘ask your own questions’ through reading, ‘expand limited thoughts and perspectives’ through discussion, and develop the power of thinking and communication, can be a human-tailored teaching and learning method in the era of digital transformation.

High-Brightness Color-Tunable AC-Driven Quantum Dot Light-Emitting Diodes for Integrated Passive High-Electric-Field Contactless Detection.

This work explores the carrier recombination dynamics of AC-driven quantum dot (QD) light-emitting diodes (AC-QLEDs) and proposes their application in the field of electric field contactless detection. Different sequences of green QD (GQD)/red QD (RQD) bilayer thin films as the emission layer of AC-QLEDs were fabricated via film transfer printing to ensure the complete morphology of each layer. AC-QLEDs with the emission layer as the sequence of GQD + RQD (GR-QLEDs) show a significantly enhanced carrier recombination efficiency due to its stable energy level structure, achieving the highest peak brightness ever recorded for vertically emitting brightness of 1648.2 cd/m2 depending on the carriers generated inside the device under AC bias. Owing to an imbalance in the carrier concentration generated by two sides of the emission layer, the proportion of emitted green light changes with the electric field strength, resulting in a macroscopic color shift of GR-QLEDs. The results indicate that although no carriers are injected directly from two electrodes, the equilibrium-induced carrier concentration under the AC electric field remains important. We utilized this unique device structure and color shift of GR-QLEDs for on-site inspection of large-scale communications power consumption. The patterned detector displays a significant color change from 9 × 106 to 6 × 107 V/m. True noncontact direct visualization detection was conducted under variable electric fields from 1 × 107 to 2 × 107 V/m in the vicinity of the running cable by emitting bright light. The proposed passive electric field detector is well-suited for investigating air gap discharge and monitoring spatial electric fields, featuring high integration, transparency, lightweight characteristics, high sensitivity, and broad bandwidth.

Building Confidence and Well-being: The Power of Coach Communication and Personal Connections in College Basketball

The relationship between coaches and athletes plays a critical role in shaping athletes' confidence, performance, and overall well-being. Effective communication and strong interpersonal connections between coaches and athletes are often key determinants of success in sports, particularly for student athletes who are balancing academic and athletic responsibilities. This research aims to identify and analyze the influence of coach communication skills and personal closeness on self-confidence and well-being of student basketball athletes at Universitas Negeri Jakarta and Riau Islamic University. The research used mixed methods with purposive sampling techniques to select participants who met the criteria, namely athletes and coaches with relevant experience in basketball teams. Data were collected through quantitative questionnaires to measure coach communication quality, personal closeness, confidence, and athlete well-being; as well as in-depth interviews and observations of interactions in training and matches to obtain more in-depth contextual data. Quantitative analysis was conducted using regression techniques, while qualitative data were thematically analyzed to identify key themes and patterns. The results showed that clear, open, and emotionally supportive coach communication had a significant effect on athletes' confidence and well-being. Athletes who perceived emotional support and effective communication from coaches were more motivated and confident in their abilities, which had a positive impact on their performance on the field. In addition, the personal closeness between coaches and athletes also increased athletes' confidence and emotional satisfaction. The implication of this research is the importance of communication skills and interpersonal relationships in the training process.

Damned If You Do and Damned If You Don’t: A Theoretical Examination and Extension of CEO Activism

The traditional responsibility of a CEO—prioritizing firm performance and shareholder returns—has become increasingly intertwined with expectations to actively engage with sociopolitical issues. These competing expectations have created a scenario where engaging, not engaging, or incorrectly engaging in CEO activism all carry the risk of alienating at least some stakeholders and undermining CEO and firm reputation and performance. Further, extant research has primarily focused on whether CEOs engage in activism rather than disentangling the heterogeneous ways by which they do so. We address these shortcomings and augment existing theory by comprehensively considering distinct CEO activism engagement strategies, their outcomes, and the moderators influencing relations between the two. Moreover, we illuminate the highly heterogeneous nature of CEO activism to better capture the phenomenon’s complexity. We first introduce the CEO Activism Decision Matrix—a typology of four unique activism engagement strategies based on the behavioral dimensions of CEO Talk (leveraging communicative power) and CEO Action (leveraging economic power), successfully addressing the heterogeneity in activism behaviors that existing theory has overlooked. We then present an integrative conceptual model that outlines the short- and long-term consequences and relevant moderators of CEO activism engagement and offer detailed recommendations for future research, including methodological guidance on operationalizing variables and designing research that can infer causality. Altogether, we demonstrate that although CEOs may find themselves “damned if you do, and damned if you don’t” engage in activism, they also have the potential to drive meaningful career, firm, and societal change based on how they choose to engage.

High‑Temperature Image Pre‐Processing Based on ε‐Ga2O3 Photo‐Synapses

AbstractThe era of big data has brought about substantial challenges in terms of power consumption and communication bandwidth. Edge‐based neuromorphic computing with data pre‐processing can help alleviate these burdens and enhance overall system efficiency. However, existing neuromorphic devices are typically limited to operation at room temperature, restricting their applications in extreme environments. Here, the use of wide‐bandgap ε‐Ga2O3 photo‐synapses as image pre‐processors is demonstrated, even at temperatures as high as 650 K. This is possible because of the high‐quality ε‐Ga2O3 epitaxial films, which exhibit angstrom‐level surface roughness, as evidenced by the highly uniform 152 photodetector devices. These devices show enhanced photo‐synaptic behavior at elevated temperatures, enabling high‐temperature image compression capability. The 4 × 4‐pixel images are compresed into 4 × 1 vectors, achieving an image recognition accuracy of 100% at 650 K. This work demonstrates the potential of ε‐Ga2O3 artificial synapses for extremely high‐temperature computing.

Youth Leaders' Emotional Intelligence Story Book Two: When will I be good enough for my parents?

This story explores the emotional journey of Abby, a young girl seeking balance between her mother’s high expectations and her own independence. Frustrated by constant criticism yet yearning for her mom's approval, Abby reflects on their relationship and discovers the power of open communication.

Artificial Intelligence (AI) and Health Communication Policy in Nigeria: Challenges and Prospects

Advances in Artificial Intelligence (AI) are reshaping health communication worldwide, a key aspect of enhancing public health. This study analyzed current health communication policies to pinpoint areas where AI-driven approaches are yet to be addressed. In Nigeria, integrating AI into health communication policies presents both opportunities and hurdles. The study examined how AI can boost health communication initiatives in Nigeria, particularly through AI-powered tools that enhance the spread of health messages, patient education, and public awareness campaigns. Additionally, the study highlighted challenges in implementing AI technologies, including limited infrastructure, inadequate data management, and a shortage of skilled professionals. The paper also presented the potential of Artificial Intelligence (AI) to transform health communication. It suggested policy guidelines to support its integration while reducing risks. Additionally, it recommended policy changes, training, and cooperation among stakeholders to leverage AI's power in health communication. In Nigeria, the outlook for AI in health communication is optimistic, assuming focused investments in technology, training, and regulatory reforms.

The value of coordination for restoring power and wireless communication networks

The value of coordination for restoring power and wireless communication networks

A Miniature Batteryless Bioelectronic Implant Using One Magnetoelectric Transducer for Wireless Powering and PWM Backscatter Communication.

Wireless minimally invasive bioelectronic implants enable a wide range of applications in healthcare, medicine, and scientific research. Magnetoelectric (ME) wireless power transfer (WPT) has emerged as a promising approach for powering miniature bio-implants because of its remarkable efficiency, safety limit, and misalignment tolerance. However, achieving low-power and high-quality uplink communication using ME remains a challenge. This paper presents a pulse-width modulated (PWM) ME backscatter uplink communication enabled by a switched-capacitor energy extraction (SCEE) technique. The SCEE rapidly extracts and dissipates the kinetic energy within the ME transducer during its ringdown period, enabling time-domain PWM in ME backscatter. Various circuit techniques are presented to realize SCEE with low power consumption. This paper also describes the high-order modeling of ME transducers to facilitate the design and analysis, which shows good matching with measurement. Our prototyping system includes a millimeter-scale ME implant with a fully integrated system-on-chip (SoC) and a portable transceiver for power transfer and bidirectional communication. SCEE is proven to induce >50% amplitude reduction within 2 ME cycles, leading to a PWM ME backscatter uplink with 17.73 kbps data rate and 0.9 pJ/bit efficiency. It also achieves 8.5 × 10-5 bit-error-rate (BER) at a 5 cm distance, using a lightweight multi-layer-perception (MLP) decoding algorithm. Finally, the system demonstrates continuous wireless neural local-field potential (LFP) recording in an in vitro setup.

TOPSIS approach based adaptability analysis for power substation area communication schemes

Abstract With the development of new power systems, various new services emerge in substation areas, increasing the number of end devices as well as the frequency of data collection. As a result, end terminal communication in substation areas faces significant challenges such as capacity, coverage, reliability and so on. A unified analytical model is required to evaluate various networking schemes. Therefore, in this paper we propose a technique for order preference by similarity to an ideal solution (TOPSIS) based compatibility analysis model for power communication demand indicators, which provides a theoretical evaluation criteria for substation area communication networks. Based on the model, we also introduce multiple networking schemes for comparison. The comparative results show that for three typical services, emergency response, electric frequency regulation, and peak shaving, there are three distinct networking schemes with the highest compatibility, respectively. Wherein joint HPLC, HRF, and LTE networking provide well-suited performance for substation area communication.

A Niche Quantum Ant Colony Multifaceted Routing Algorithm for WSN-based IoT Networks in the Emerging Quantum Industry

Quantum computing (QC) is an important area of technological study. The ever-growing network size and complexity in quantum computation research are the cause of evolutionary dynamics in QC. The Internet of Things (IoT) is a paradigm shift in thinking; it advances many forms of communication that rely on WSNs to gather data, and it has the potential to be even more effective with the help of quantum computing. Network congestion results in lost packets, delayed transmissions, and wasted effort during recovery. In an attempt to improve the efficiency and velocity of the route, the proposed method considers a number of objectives. Since quantum computers leverage the characteristics of quantum states to do certain computations at orders of magnitude quicker than classical computers, this is an exciting new direction to investigate. This study introduced the Niche Quantum Ant Colony Multifaceted Routing Algorithm (NQAC-MRA), a method for optimizing wireless distributed networks in IoT routes that combines quantum computation, an optimization function for several objectives, and monitoring. Producing cost-effective routing that is congestion-aware for alarm message transmission over WSN-IoT and for alert message transmission utilizing IoT devices to their respective destinations with the lowest latency is the primary goal of this study. To be more specific, the quantum bits stand in for the node pheromone, and turning quantum gates modifies the search path's pheromone. Nodes' power consumption, communication delay, and degree of network load-balancing serve as fitness metrics to find the best communication path. According to the results of the performance analysis, the suggested scheme is both lightweight and more effective than the alternatives. The performance research showed that the proposed approach outperformed the alternatives while being significantly lighter. The suggested NQAC-MRA beat its competitors in terms of total simulation results thanks to its reduced energy usage and enhanced performance.

Nonlinear Analysis and Solution for an Overhead Line Magnetic Energy Harvester with an Active Rectifier

Recently, there has been a significant focus on developing various energy harvesting technologies to power remote electronic sensors, data loggers, and communication devices for smart grid systems. Among these technologies, magnetic energy harvesting stands out as one straightforward method to extract substantial power from current-carrying overhead lines. Due to the relatively small size of the harvester, the high currents in the distribution system quickly saturate its magnetic core. Consequently, the magnetic harvester operates in a highly nonlinear manner. The nonlinear nature of the downstream AC to DC converters further complicates the process, making precise analytical modeling a challenging task. In this paper, a clamped type overhead line magnetic energy harvester with a controlled active rectifier generating significant DC output power is investigated. A piecewise nonlinear analytical model of the magnetic harvester is derived and reported. The modeling approach is based on the application of the Froelich equation. The chosen approximation method allowed for a complete piecewise nonlinear analytical treatise of the harvester’s behavior. The main findings of this study include a closed-form solution that accounts for both the core and rectifiers’ nonlinearities and provides an accurate quantitative prediction of the harvester’s key parameters such as the transfer window width, optimal pulse location, average DC output current, and average output power. To facilitate the study, a nonlinear model of the core was developed in simulation software, based on parameters extracted from core experimental data. Furthermore, theoretical predictions were verified through comparison with a computer simulation and experimental results of a laboratory prototype harvester. Good agreement between the theoretical, simulation, and experimental results was found.

Adaptive communication power control for enhancing attack resilience in UAV networks

A swarm of Unmanned Aerial Vehicles (UAVs) comprises multiple UAVs that are capable of completing tasks beyond the capabilities of a single UAV. Due to the unique challenges of UAV missions, these vehicles often operate far from base stations, making network connectivity crucial for the successful completion of UAV swarm missions. However, existing methods do not account for strategies to maintain the overall connectivity of the UAV network when nodes are under attack. To address this issue, we propose a method named Adaptive Communication Power Control (ACPC) that dynamically adjusts UAV communication power to mitigate potential connectivity losses caused by node failures or malicious attacks. This adjustment ensures that the network can maintain information exchange among the remaining UAVs even in the event of disruptions. Additionally, we introduce a novel evaluation method to assess the overall connectivity of the network and validate ACPC through simulations of UAV swarm missions where some UAVs experience failures. Using this evaluation method, we measured the network’s state before and after attacks and recovery and calculated the additional energy consumption required by the UAVs. The results indicate that our method can increase the resilience of the UAV network by up to 5.36 times, while only raising the total communication energy consumption to 1.53 times.

Research on Fast Early Warning of False Data Injection Attack in CPS of Electric Power Communication Network

The power grid is vulnerable to bad data interference and false data attacks, so its security is reduced. This paper focuses on the study of false data injection attacks (FDIAs), analyzes the principle of FDIAs and their impact on power systems, and studies the methods of suppressing and detecting FDIAs based on distributed state estimation and neural networks. In addition, this paper establishes a specific simulation model. Simulation results show that the proposed method can effectively identify FDIAs and correct bad data, thus further reducing the impact of FDIAs on power system state estimation. Therefore, in the follow-up, we can use this method to carry out practical research in the power communication network to further improve the security of the power communication network.

Decision making in ambiguous situations: Determining recipients of cash social assistance in Indonesia

Determining recipients of Direct Cash Assistance from Village Funds in Indonesia is a complex process often marked by various challenges, especially in ambiguous situations. In this situation, leadership communication strategies become very important to ensure that decisions are effective and acceptable to the community. This study aims to analyze leadership communication strategies in decision-making in ambiguous situations to determine recipients of direct cash assistance in Indonesia. This study was conducted in two village areas, namely Karangtengah village in Cilongok District, Banyumas Regency, Central Java, Indonesia as a rural area and Rawapanjang village in Bojonggede District, Bogor Regency, West Java, Indonesia as a semi-rural-area. This study uses a qualitative descriptive research design with a case study approach. Data analysis was conducted inductively with a thematic approach, where relevant parts of the data were given specific labels or codes. These codes are based on themes or categories that emerged from interviews with informants. The coded data is presented narratively and in tabular visualization. The study results show that Karangtengah village and Rawapanjang village, in the implementation of BLT-DD, have the power of sensemaking in the direct involvement of village leaders in the field. They do not only rely on data but also directly verify the conditions of residents so that the decisions taken are more relevant to the situation in the field. Overall, Karangtengah village excels in the power of sensemaking and leadership communication through a collaborative approach involving various stakeholders. Active community involvement in village deliberations creates a decision-making process that is more representative and responsive to the needs of residents.