Imprecise Communication Research Articles

Transforming Conflict into Collaboration: A Systematic Approach to Conflict Resolution at Antara East Java Indonesia News Agency

Conflict is an unavoidable part of organizational dynamics, necessitating systematic techniques for effective resolution. This study investigates the use of the Problem Solving and Decision Making (PSDM) paradigm to resolve conflicts at Antara East Java News Agency. During the first half of 2024, data were gathered using a qualitative case study approach, including in-depth interviews, participatory observations, and document analysis. The findings show that the PSDM model efficiently resolves organizational conflicts by rigorously diagnosing fundamental causes, encouraging inclusive decision-making, and implementing tailored remedies. Misaligned work allocations, imprecise communication routes, and conflicts between regional autonomy and centralized directives were among the most significant obstacles. Practical measures, such as the use of digital task management systems and collaborative decision forums, resulted in considerable improvements in operational efficiency and teamwork. This study advances conflict resolution theory by proving the PSDM model's flexibility in media enterprises and integration with digital transformation challenges. It also offers tangible ideas for organizations dealing with comparable difficulties, highlighting the value of participatory and context-sensitive approaches. Future study should look at the model's applicability in a variety of industries, cross-cultural contexts, and digital-first environments to increase its relevance and influence.

Artificial Empathy and Imprecise Communication in a Multi-Agent System

This paper introduces a novel artificial intelligence model that integrates artificial empathy into the decision-making processes of collaborative agent systems. The existing models of collaborative behaviors, especially in swarm applications, lack the aspect of empathy, known to improve cooperation in human teams. Emphasizing both cognitive and emotional aspects of empathy, the introduced model navigates communication uncertainties and ambiguities, transforming these challenges into opportunities for learning and adaptation in dynamic environments. A significant feature of this model is its handling of imprecision through fuzzy logic, using fuzzy similarity measures in the decision process. The main objective of the presented research is to introduce a new model for improving cooperativeness in multi-agent systems with the use of cognitive empathy. Future research focus on implementing the model on physical platform and optimize the artificial empathy algorithms in the decision-making module.

Substantial differences in perception of disease severity between post COVID-19 patients, internists, and psychiatrists or psychologists: the Health Perception Gap and its clinical implications

Patient-reported outcome measures (PROMs) such as the Numeric Pain Rating Scale (NPRS) or Likert scales addressing various domains of health are important tools to assess disease severity in Post COVID-19 (PC) patients. By design, they are subjective in nature and prone to bias. Our findings reveal substantial differences in the perception of disease severity between patients (PAT), their attending internists (INT) and psychiatrists/psychologists (PSY). Patients rated almost all aspects of their health worse than INT or PSY. Most of the differences were statistically highly significant. The presence of fatigue and mood disorders correlated negatively with health perception. The physical health section of the WHO Quality of Life Assessment (WHOQoL-BREF) and Karnofsky index correlated positively with overall and mental health ratings by PAT and INT. Health ratings by neither PAT, PSY nor INT were associated with the number of abnormal findings in diagnostic procedures. This study highlights how strongly perceptions of disease severity diverge between PC patients and attending medical staff. Imprecise communication, different experiences regarding health and disease, and confounding psychological factors may explain these observations. Discrepancies in disease perception threaten patient-physician relationships and pose strong confounders in clinical studies. Established scores (e.g., WHOQoL-BREF, Karnofsky index) may represent an approach to overcome these discrepancies. Physicians and psychologists noting harsh differences between a patient’s and their own perception of the patient’s health should apply screening tools for mood disorders (i.e., PHQ-9, WHOQoL-BREF), psychosomatic symptom burden (SSD-12, FCV-19) and consider further psychological evaluation. An interdisciplinary approach to PC patients remains imperative. Trial Registration Number & Date of Registration: DRKS00030974, 22 Dec 2022, retrospectively registered.

A Review of Enterprise Architecture for Strategic Performance Management in the Transportation Sector Digital Transformation

This paper reviews the use of Enterprise Architecture (EA) for strategic performance management in the transport sector's digital transformation, focusing on the Balanced Scorecard (BSC) theory. EA is essential for strategic planning and performance management in the transport industry, which is vital to the economy. The study analyses academic publications, industry reports, and case studies to assess EA's benefits, drawbacks, and novel solutions in transportation. The Balanced Scorecard framework, which measures and manages performance holistically, should be used to align EA projects. EA and the Balanced Scorecard theory may provide a solid foundation for strategic performance management in the transportation sector's digital transition. It aligns goals, objectives, and KPIs with strategic vision and mission. EA also helps identify important capabilities, processes, and IT systems to accomplish desired results. It also improves decision-making by offering an integrated perspective of the organisation's resources, capabilities, and dependencies. In the transportation industry, EA for strategic performance management faces obstacles, including imprecise communication, insufficient governance, and limited planning. Innovative solutions, including improved communication channels, stronger governance systems, and enhanced planning techniques, are recommended to tackle these issues. This review analysis sheds light on the transport sector's digital transition using EA and the Balanced Scorecard theory. It advises researchers, practitioners, and policymakers to use EA to improve performance management and maintain transportation industry growth.

Definition, diagnosis and clinical management of non-obstructive kidney dysplasia: a consensus statement by the ERKNet Working Group on Kidney Malformations.

Kidney dysplasia is one of the most frequent causes of chronic kidney failure in children. While dysplasia is a histological diagnosis, the term 'kidney dysplasia' is frequently used in daily clinical life without histopathological confirmation. Clinical parameters of kidney dysplasia have not been clearly defined, leading to imprecise communication amongst healthcare professionals and patients. This lack of consensus hampers precise disease understanding and the development of specific therapies. Based on a structured literature search, we here suggest a common basis for clinical, imaging, genetic, pathological and basic science aspects of non-obstructive kidney dysplasia associated with functional kidney impairment. We propose to accept hallmark sonographic findings as surrogate parameters defining a clinical diagnosis of dysplastic kidneys. We suggest differentiated clinical follow-up plans for children with kidney dysplasia and summarize established monogenic causes for non-obstructive kidney dysplasia. Finally, we point out and discuss research gaps in the field.

Communication of preclinical emergency teams in critical situations: A nationwide study

The emergency medical service as a high-risk workplace is a danger to patient safety. A main factor for patient safety, but also at the same time a main factor for patient harm, is team communication. Team communication is multidimensional and occurs before, during, and after the patient's treatment. In an online based, anonymous and single-blinded study, medical and non-medical employees in the emergency medical services were asked about team communication, and communication errors. Seven hundred and fourteen medical and non-medical rescue workers from all over Germany took part. Among them, 72.0% had harmed at least one patient during their work. With imprecise communication, 81.7% rarely asked for clarification. Also, 66.3% saw leadership behavior as the cause of poor communication; 46.0% could not talk to their superiors about errors. Of note, 96.3% would like joint training of medical and non-medical employees in communication. Deficits in team communication occur frequently in the rescue service. There is a clear need for uniform training in team and communication skills in all professions.

Distributed fuzzy adaptive consensus for high-order multi-agent systems with an imprecise communication topology structure

In this study, we consider the consensus problem for a high-order multi-agent systems (MASs) with an imprecise communication topology structure described by the Takagi–Sugeno fuzzy model. A distributed adaptive control protocol is proposed for the consensus problem comprising MASs with unknown parameters and input disturbances. The proposed protocol can guarantee that the consensus errors asymptotically approach zero under the conditions that the communication topology is fuzzy union connected and the dynamics of the leader are unknown to any agent among the followers. Furthermore, the proposed algorithm is extended to solve the formation control problem for MASs. Sufficient conditions are provided for the consensus and formation problems for MASs based on Lyapunov stability theory. Finally, three simulation examples are presented to illustrate the effectiveness of the proposed control protocol.

High-Flow Oxygen Therapy Concepts: Time to Standardize Nomenclature and Avoid Confusion.

High-flow nasal oxygen systems are rapidly being adopted as an initial noninvasive treatment for acute respiratory failure. However, the term "high-flow nasal cannula" is nonspecific and leads to imprecise communication between physicians, respiratory therapists, and nurses with the potential for patient harm. In this viewpoint and a brief review of the technology, we argue for a change in nomenclature in order to reduce the chance for future clinical, administrative, and research misunderstanding surrounding high-flow nasal oxygen systems.

T–S fuzzy model-based adaptive repetitive consensus control for multi-agent systems with imprecise communication topology structure

ABSTRACTThis paper studies the consensus problem of multi-agent systems (MAS) with imprecise communication topology structure (ICTS). T–S fuzzy model is used to express the ICTS. Through repeated learning techniques, this paper designs a distributed learning protocol that enables all agents reach consensus with periodic uncertainty parameters. The periodic uncertainty parameters are compensated based on a repetitive learning design method. With the information of leader agent is known to a small portion of following agents, an auxiliary control term is presented for each follower agent to handle leader's dynamic. Under the condition that the ICTS is fuzzy union connected, the learning control protocol proposed in this paper makes all the agents reach an agreement. In addition, the proposed consensus learning protocol is further promoted to solve the formation control problem. Sufficient conditions are given for the consensus and formation problems of the MAS by constructing a composite energy function, respectively. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed control protocol.

T‐S fuzzy model–based adaptive repetitive learning consensus control of high‐order multiagent systems with imprecise communication topology structure

SummaryThis paper addresses the consensus problem for high‐order nonlinear multiagent systems with imprecise communication topology structure (ICTS) and unknown periodic time‐varying parameters. Takagi‐Sugeno fuzzy models are used to portray the ICTS. By using the reparameterization technique, the repetitive learning control protocol is presented to guarantee that all the followers can track the leader asymptotically under the condition that the ICTS is fuzzy union connected. The information of the leader is known to a small portion of following agents; an auxiliary control term is presented for each follower agent to handle leader's dynamics. The consensus performance is analyzed via Lyapunov stability theory. Furthermore, the proposed protocol is further promoted to solve the formation control problem. Finally, the validity of the proposed methods are verified by two simulation examples.

T–S fuzzy model-based adaptive repetitive consensus control for second-order multi-agent systems with imprecise communication topology structure

This paper investigates the consensus problem of the second-order nonlinear multi-agent systems (MAS) with unknown periodic time-varying parameters (UPTVP) and imprecise communication topology structure (ICTS). T–S fuzzy models is used to express the ICTS, and the concept of fuzzy union connected (FUC) is defined. Under the condition that the ICTS is FUC, an adaptive repetitive learning control protocol is presented such that all the followers can track the leader asymptotically. With the information of leader agent is known to a small portion of following agents, an auxiliary control term was presented for each follower agent to handle leaders dynamics. The distributed MAS consensus is analyzed based on the Lyapunov stability theory. Furthermore, the proposed protocol is further promoted to solve the formation control problem. Finally, simulation results are shown to demonstrate the validity of the proposed design methods in this paper.

Fuzzy adaptive leader‐following consensus of second‐order multiagent systems with imprecise communication topology structure

SummaryThe consensus problem of second‐order nonlinear multiagent systems (MAS) with imprecise communication topology structure is addressed in this paper. Takagi‐Sugeno fuzzy models are presented to describe the leader‐following MAS with imprecise communication topology structure. By designing the distributed adaptive controller, an efficient framework is proposed for the consensus control of the MAS with both uncertain parameters and input disturbances. Under the conditions that the communication topology is fuzzy union connected and the dynamics of the leader agent is unknown to any agent of followers, the proposed protocol can guarantee that the consensus errors asymptotically approach zeros. Furthermore, the proposed algorithm is extended to solve the formation control problem. Sufficient conditions are given for the consensus and formation problems of the MAS based on the Lyapunov stability theory. Finally, a numerical example and multiple pendulum systems are given to illustrate the effectiveness of the proposed control protocols.

Imprecise communication and perceptions of palliative care.

Imprecise communication and perceptions of palliative care.

Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure

ABSTRACTIn this paper, we investigate the perfect consensus problem for second-order linearly parameterised multi-agent systems (MAS) with imprecise communication topology structure. Takagi-Sugeno (T–S) fuzzy models are presented to describe the imprecise communication topology structure of leader-following MAS, and a distributed adaptive iterative learning control protocol is proposed with the dynamic of leader unknown to any of the agent. The proposed protocol guarantees that the follower agents can track the leader perfectly on [0,T] for the consensus problem. Under alignment condition, a sufficient condition of the consensus for closed-loop MAS is given based on Lyapunov stability theory. Finally, a numerical example and a multiple pendulum system are given to illustrate the effectiveness of the proposed algorithm.

Sleep deprivation impairs precision of waggle dance signaling in honey bees

Sleep is essential for basic survival, and insufficient sleep leads to a variety of dysfunctions. In humans, one of the most profound consequences of sleep deprivation is imprecise or irrational communication, demonstrated by degradation in signaling as well as in receiving information. Communication in nonhuman animals may suffer analogous degradation of precision, perhaps with especially damaging consequences for social animals. However, society-specific consequences of sleep loss have rarely been explored, and no function of sleep has been ascribed to a truly social (eusocial) organism in the context of its society. Here we show that sleep-deprived honey bees (Apis mellifera) exhibit reduced precision when signaling direction information to food sources in their waggle dances. The deterioration of the honey bee's ability to communicate is expected to reduce the foraging efficiency of nestmates. This study demonstrates the impact of sleep deprivation on signaling in a eusocial animal. If the deterioration of signals made by sleep-deprived honey bees and humans is generalizable, then imprecise communication may be one detrimental effect of sleep loss shared by social organisms.

Creating a Mentally Healthy Community Through the Use of Behavioral Health Indicators

Recent decades have seen the development of robust systems of community health indicators, but those indicator sets tend to have few indicators related to behavioral health. Gauging community behavioral health can be complex, but given the interconnectedness of health and behavioral health and the high social and financial cost of unaddressed behavioral health needs, it is essential to develop meaningful indicators. A community-based participatory research project in Austin, Texas developed behavioral health indicators based on a review of social indicators movements across the globe, existing sets of proposed key indicators of mental health and mental illness, and ongoing community initiatives in Austin relevant to behavioral health. The community behavioral health indicators have been refined through the challenging process of implementing them in the face of competing efforts and imprecise communication about their use. While indicators should always be adapted to suit local conditions, this indicator set should provide a good starting point for researchers and communities to assess and improve the behavioral health of their community.

Editorial--A plea for scholarly writing

Synopsis Scientific writing is a skill that needs to be developed through concentration and practice. By the final draft of a paper, each sentence should have been crafted to convey information clearly, succinctly, and accurately. The standard of writing in current scientific journals has reached an all-time low, in terms of both poor grammar and imprecise communication. This situation has been fueled on one hand by escalating costs of publication and an attempt to shorten papers and, on the other hand, by inadequate training in the structure of the English language.

Ratings of Orally Presented Verbal Expressions of Probability by a Heterogeneous Sample

Verbal expressions of probability are used in daily conversations, physician‐physician and physician‐patient communications, and questionnaire and interview responses. To assess the degree of agreement among English‐speaking Australian adults in allocating numerical probabilities to these verbal expressions of probability, 966 interviewees provided estimates for 60 isolated expressions of probability and a sequence of seven items placed in a sequence. Means and median scores appeared to be consistent with common sense and with findings from other countries. Mirror‐imaged terms were neither symmetrical nor equidistant, with the means and medians for the positive terms being closer to the mid‐points of the scale than the means and medians of the negative terms. Items in a sequence of probability terms showed greater symmetry and less variability than isolated expressions. For most items, there was an unacceptably high level of within‐subject and between‐subject variability. Although subjects with higher levels of education and/ or mathematics education showed less variability, these factors accounted for very little of the variance. The greater variability in Australian results relative to those reported elsewhere was partly attributed to the use of interviews rather than questionnaires. There were no particular stems that yielded greater consistency. It was concluded that the use of these expressions leads to very imprecise communication.