Communication Of Uncertainty Research Articles

A practical approach to networked control design for robust H∞ performance in the presence of uncertainties in both communication and system

This work presents results on the development of robust H∞ control strategy for Networked Control Systems (NCSs) by involving uncertainties in both communication and controlled plant subsystems. The network-induced delays in both communication links (to and from the controller) are assumed to behave as Markov chains. An analytical approach is presented to calculate the transition probabilities of the Markovian network-induced delays. By employing the augmentation method, the resultant system is converted into a delay-free uncertain singular Markovian jump system with bounded transition probabilities. New conditions are established to assure that the uncertain NCS satisfies an H∞ performance requirement. Moreover, sufficient conditions for robust H∞ output feedback controller design are expressed in terms of LMIs. Finally, numerical examples are presented to verify the validity of the proposed controller design method.

A Mixed Methods Analysis of Parental Perspectives on Diagnosis and Prognosis of Neonatal Intensive Care Unit Graduates With Cerebral Palsy

This study aimed to evaluate how parents of former neonatal intensive care unit patients with cerebral palsy perceive prognostic discussions following neuroimaging. Parent members of a cerebral palsy support network described memories of prognostic discussions after neuroimaging in the neonatal intensive care unit. We analyzed responses using Linguistic Inquiry and Word Count, manual content analysis, and thematic analysis. In 2015, a total of 463 parents met eligibility criteria and 266 provided free-text responses. Linguistic Inquiry and Word Count analysis showed that responses following neuroimaging contained negative emotion. The most common components identified through the content analysis included outcome, uncertainty, hope/hopelessness, and weakness in communication. Thematic analysis revealed 3 themes: (1) Information, (2) Communication, and (3) Impact. Parents of children with cerebral palsy report weakness in communication relating to prognosis, which persists in parents' memories. Prospective work to develop interventions to improve communication between parents and providers in the neonatal intensive care unit is necessary.

Distributed and Asynchronous Coordination of a Mixed-Integer Linear System via Surrogate Lagrangian Relaxation

With the emergence of the Internet of Things that allows communications and local computations and with the vision of Industry 4.0, a foreseeable transition is from centralized system planning and operation toward decentralization with interacting components and subsystems, e.g., self-optimizing factories. In this article, a new “price-based” decomposition and coordination methodology is developed to efficiently coordinate a system consisting of distributed subsystems such as machines and parts, which are described by mixed-integer linear programming (MILP) formulations, in an asynchronous way. The novel method is a dual approach, whereby the coordination is performed by updating Lagrangian multipliers based on economic principles of “supply and demand.” To ensure low communication requirements within the method, exchanges between the “coordinator” and subsystems are limited to “prices” (Lagrangian multipliers) broadcast by the coordinator and to subsystem solutions sent at the coordinator. Asynchronous coordination, however, may lead to convergence difficulties since the order in which subsystem solutions arrive at the coordinator is not predefined as a result of uncertainties in communication and solving times. Under realistic assumptions of finite communication and solve times, the convergence of our method is proven by innovatively extending the Lyapunov stability theory. Numerical testing of generalized assignment problems through simulation demonstrates that the method converges fast and provides near-optimal results, paving the way for self-optimizing factories in the future. Accompanying CPLEX codes and data are included. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In view of a foreseeable transition toward self-optimizing factories whereby machines and parts have communication and computational capabilities, a novel “price-based” distributed and asynchronous method to coordinate a system consisting of distributed subsystems is developed. Under realistic assumptions of finite communication and solve times, method convergence is proven. Numerical testing of generalized assignment problems through simulation demonstrates that the method converges fast and provides near-optimal results, paving the way for self-optimizing factories in the future. Accompanying CPLEX codes and data are included.

The influences of host and ethnic internet use on sociocultural and psychological adaptation among Chinese college students in the United States: Intercultural communication apprehension and uncertainty reduction as mediators

ABSTRACT This study investigated the influences of internet use on cross-cultural adaptation. One hundred and fifty-two Chinese students (N = 152) in the United States completed a battery of questionnaires. Results indicated that host internet use negatively predicted intercultural communication apprehension (ICA) and uncertainty, which in turn positively influenced sociocultural and psychological adaptation. ICA predicted sociocultural adaptation equally as uncertainty, but was a stronger factor explaining psychological adaptation. Ethnic internet use, however, was not related to cross-cultural adaptation. These findings suggest that the host internet helps newcomers adapt to a new culture by reducing their ICA and uncertainty levels.

Hybrid Robust Sequential Fusion Estimation for WSN-Assisted Moving-Target Localization With Sensor-Node-Position Uncertainty

This article presents a hybrid robust sequential fusion estimation (HRSFE) method for moving-target localization in mobile asynchronous wireless sensor networks (WSNs). The estimation error or inconsistency, caused by the uncertainties of sampling, communication, and sensor-node position, is considered fully and compensated by incorporating the sensor-node position with uncertainty into the state vector as well as introducing an adaptive fading factor into the cubature Kalman filter (CKF) to maintain the estimation consistency. In addition, a QR-decomposition-based square-root form of the cubature strong localization filter (SR-CSLF) is proposed to improve the accuracy and stability of the CSLF. Moreover, an HRSFE method is designed to estimate the augment state of the WSN-assisted moving-target-localization system, and the proposed estimation method combines the merits of both the SR-CSLF and SR-CKF effectively and is able to deal with the uncertainties of sampling, communication, and sensor-node position in a unified framework. Simulations and experiments of a WSN-assisted moving-target-localization system under various uncertainty settings are employed to demonstrate the effectiveness and superiorities of the proposed method.

RBF-Neural-Network-Based Adaptive Robust Control for Nonlinear Bilateral Teleoperation Manipulators With Uncertainty and Time Delay

The bilateral teleoperation system has raised expansive concern as its excellent behaviors in executing the tasks in the remote, unstructured, and dangerous areas via the cooperative operation systems. In this article, an radial basis function (RBF) neural network based adaptive robust control design is proposed for nonlinear bilateral teleoperation manipulators to cope with the main issues including the communication time delay, various nonlinearities, and uncertainties. Specifically, the slave environmental dynamics is modeled by a general RBF neural network, and its parameters are estimated and then transmitted for the environmental torque reconstruction in the master side. Since the parameters of the neural network (which are nonpower signals) are transmitted instead of the traditional environmental torque in the communication channel, the previous existing passivity problem under time delay is avoided. In both of master and slave sides, the trajectory creators are applied to generate the desired trajectories, and the RBF-neural-network-based adaptive robust controllers are designed subsequently to handle the nonlinearities and uncertainties. Theoretically, the proposed control algorithm can guarantee the global stability of bilateral teleoperation manipulators under time delay, and the good transparency performance with both position tracking and force feedback is also achieved simultaneously. The real platform comparative experiments are carried out, and the results show the good position tracking to execute precise operation and the good force feedback to detect the sudden disturbance in the environment dynamics.

Overcoming Channel Uncertainties in Touchable Molecular Communication for Direct-Drug-Targeting-Assisted Immuno-Chemotherapy.

The performance of targeted immuno-chemotherapy of tumor is highly exposed to drug absorption in systemic circulation, which reduces its efficiency and increases side-effects. Direct drug targeting (DDT) combined with immuno-chemotherapy has the potential to mitigate the undesired systemic exposure, by using drug-loaded nanorobots to target cancer cells with the shortest possible physiological routes. This process can be modeled by the "touchable" (i.e., externally controllable and trackable) molecular communication system. However, such a complex process still suffers from various pharmacokinetic uncertainties caused by diffusion, degeneration, and branching of nanorobots (DDT pharmacokinetic uncertainties), as well as tumor/immune system modeling errors. The current work aims at identifying optimal drug administration plans by overcoming such challenges. A revisited tumor-immune interaction model is proposed to incorporate randomness of the drug concentration in the tumor site. Then, a robust multiple model predictive control (MMPC) scheme for the proposed tumor-immune interaction model is designed that uses multiple system models and an adaptive switch to identify the optimal plans for mixed drug administration via drug-loaded nanorobots. Furthermore, a wide range of prediction horizons under different loss scenarios of drug-loaded nanorobots and system model mismatches have been investigated in order to identify safe operating regions. From the molecular communications paradigm, this can be considered as a more robust information transmission system with feedback of channel state information to the transmitter implemented in the control unit. The efficacy of the proposed MMPC is illustrated through identification of globally optimized drug administration schedules subject to various controller operation imperfections, which lead to successful cancer treatment as demonstrated through computational experiments. By combining DDT with conventional mixed immunotherapy and chemotherapy, the proposed robust MMPC offers promising performance in controlling tumor growth while keeping the immune cell density higher than a specific level in the presence of both DDT pharmacokinetic uncertainties and system model mismatches. We believe that the proposed design framework represents an important first step towards clinically relevant DDT in the combined immunotherapy and chemotherapy of tumor given its robust performance.

Robust Multitask Formation Control via Parametric Lyapunov-Like Barrier Functions

An essential problem in the coordination of multiple agents is formation control. Significant challenges to the theoretical design may arise when the multiagent system is subject to uncertainty. This paper considers the robust multitask formation control problem for multiple agents, whose communication and measurements are disturbed by uncertain parameters. The control objectives include achieving the desired configuration, avoiding collisions, and preserving the connectivity of the uncertain topology. To achieve these objectives, we first provide conditions in terms of linear matrix inequalities for checking the connectivity of uncertain topologies. Then, we propose a new type of Lyapunov-like barrier function, called parametric Lyapunov-like barrier function, that is applicable to multiagent systems with uncertainties in communication and measurements. It is shown that this new type of Lyapunov-like barrier function guarantees the robust multitask formation and displays advantages over parameter-independent Lyapunov-like barrier functions. The efficacy of the proposed method is demonstrated via simulation results.

Novel Control Approaches for Demand Response With Real-Time Pricing Using Parallel and Distributed Consensus-Based ADMM

This paper studies the automated demand response (DR) problem in smart grids equipped with information and communication technology networks, where power generating and consuming units can exchange information as a multiagent system (MAS), and a real-time pricing (RTP) scheme is proposed. When the communication graph among agents is connected, a novel parallel and distributed consensus-based algorithm is proposed to derive an RTP scheme to facilitate DR, and when communication uncertainties exist, a robust consensus algorithm is proposed to cease the effect of uncertainties. Next, this paper proposes a novel control mechanism to tackle the problem of disconnected communication among agents, e.g., under cyber-attacks, by employing the so-called mixed communication-broadcast control architecture where the underlying ideas are twofold. First, each area in the grid associated with a connected subgraph is controlled by a MAS to guarantee the power balance and to reach consensus on the local electric price for that area. Second, a supervisory unit observes those local electric prices to calculate the global electric price for the whole grid and then broadcasts to all units so that they can properly adjust their output powers. Simulations are carried out on the IEEE 39-bus system to validate the proposed control mechanisms.

Stochastic Semistability for Nonlinear Dynamical Systems With Application to Consensus on Networks With Communication Uncertainty

This article focuses on semistability and finite time semistability analysis and synthesis of stochastic dynamical systems having a continuum of equilibria. Stochastic semistability is the property whereby the solutions of a stochastic dynamical system almost surely converge to Lyapunov stable in probability equilibrium points determined by the system initial conditions. In this article, we extend the theories of semistability and finite-time semistability for deterministic dynamical systems to develop a rigorous framework for stochastic semistability and stochastic finite-time semistability. Specifically, Lyapunov and converse Lyapunov theorems for stochastic semistability are developed for dynamical systems driven by Markov diffusion processes. These results are then used to develop a general framework for designing semistable consensus protocols for dynamical networks in the face of stochastic communication uncertainty for achieving multiagent coordination tasks in finite time. The proposed controller architectures involve the exchange of generalized charge or energy state information between agents guaranteeing that the closed-loop dynamical network is stochastically semistable to an equipartitioned equilibrium representing a state of almost sure consensus consistent with basic thermodynamic principles.

Contemporary Human Resource Management Practices in Russia: Flexibility under Uncertainty

This article develops the concept of flexibility in Human Resource Management (HRM) practices which can increase a company’s potential to respond to substantial variation in the business environment. It reveals the characteristics of flexible HRM practices in Russian companies in an uncertain external and internal environment. Cranet survey data gathered from October 2014 until March 2015 is used for measuring the environmental uncertainty and flexibility of staffing, training, and development, pay, employee relations, and communication. A comparison of the flexibility indices for the four HRM practices shows a higher level of flexibility in training and development practices. The research results confirm a direct positive relationship between the complexity of the environment and the flexibility of HRM practices.

Uncertainty and health literacy in dementia care.

The number of dementia cases increases with age, and the prevalence of dementia at the age above 80 is approaching 20% in Taiwan. Dementia is not simply a neurological disorder, but also a long-term care issue in public health and a matter of social adaptation. Scientific discoveries about dementia diagnostics, therapeutics, and preventive strategy have become the focus of media attention, but always updated and overwhelmed, which appears to increase rather than decrease the uncertainty and complexity of health communication in dementia care. Health literacy is essential for patients to understand medical information, utilize medical resources, and make shared decisions; however, the capacity to handle health information is often compromised in older adults with cognitive decline. Both ends of the increased uncertainty in dementia science and the reduced capacity in older adults are major challenges in dementia care. Dementia literacy, defined as knowledge and beliefs regarding dementia that aid recognition, management, or prevention, plays a vital role in effective care risk assessment and communication. However, little is known about the current state of dementia literacy among older adults, people with dementia, and their caregivers, and how well the dementia care practice can be implemented at the individual level is questionable. Empowering caregivers with adequate dementia literacy and developing a risk communication model in practice will translate the power of knowledge to effective care strategies, thus ameliorating the caregiver burden and enhancing the life quality of people with dementia in the long run.

Inpatient Communication Barriers and Drivers When Caring for Limited English Proficiency Children.

Achieving effective communication between medical providers and families with limited English proficiency (LEP) in the hospital is difficult. Our objective was to identify barriers to and drivers of effective interpreter service use when caring for hospitalized LEP children from the perspectives of pediatric medical providers and interpreters. We used Group Level Assessment (GLA), a structured qualitative participatory method that allows participants to directly produce and analyze data in an interactive group session. Participants from a single academic children's hospital generated individual responses to prompts and identified themes and relevant action items. Themes were further consolidated by our research team and verified by stakeholder groups. Four GLA sessions were conducted including 64 participants: hospital medicine physicians and pediatric residents (56%), inpatient nursing staff (16%), and interpreter services staff (28%). Barriers identified included: (1) difficulties accessing interpreter services; (2) uncertainty in communication with LEP families; (3) unclear and inconsistent expectations and roles of team members; and (4) unmet family engagement expectations. Drivers of effective communication were: (1) utilizing a team-based approach between medical providers and interpreters; (2) understanding the role of cultural context in providing culturally effective care; (3) practicing empathy for patients and families; and (4) using effective family-centered communication strategies. Participants identified unique barriers and drivers that impact communication with LEP patients and their families during hospitalization. Future directions include exploring the perspective of LEP families and utilizing team-based and family-centered communication strategies to standardize and improve communication practices.

Management of uncertainty in the diagnosis communication of psychogenic nonepileptic seizures in a South African context

The process of communicating a diagnosis of psychogenic nonepileptic seizures (PNES) is an integral part of the treatment process. Many international studies have therefore focused on the PNES diagnosis communication process, but to date, none with a specific focus on the South African context. This current study considered the factors that influence the patient's experience of uncertainty and the strategies employed to manage that uncertainty within the provider–patient communication. This was considered from the healthcare provider's point of view, within the specific context of diagnosis communication. We conducted 13 semi-structured interviews with providers, eliciting their perceptions related to the communication of a PNES diagnosis to patients. Data were analyzed using thematic analysis, and themes were grouped according to the main tenets of the interpersonal health communication theory of uncertainty management, which included, the experience, appraisal, and management of uncertainty.The results revealed medical, personal, and social forms of uncertainty. The social sources of uncertainty, which include challenges related to the South African healthcare system, cultural, and language variability within the South African context, as well as possible stigmatization, seemed to have the biggest influence not only on the other areas of uncertainty, but was also indicated as a barrier to effective uncertainty management by providers.Providers in this study identified the importance of building the provider–patient relationship and ensuring patient understanding, as the main strategies used to reduce uncertainty. There was some evidence to suggest varied emotional appraisals of uncertainty by patients, but because of the subjective nature of this information, further research would be needed to confirm these findings.These findings suggest that as providers, one cannot apply a one-size-fits-all approach when aiding in uncertainty management. Furthermore, it is pertinent to remain cognizant of the social realities of the South African context and its impact on the patient's uncertainty experience. More research is needed to understand patients' perceptions of uncertainty management within the context of PNES diagnosis communication, and how they align with the perceptions of the providers provided here.

Decentralized price incentive energy interaction management for interconnected microgrids

Interconnection of wide-area microgrids encounters a lot of challenges in energy management. Energy interaction among microgrids requires more extensibility and flexibility in communication and decision-making compared to energy management of a single microgrid. To address the problem, two distributed interaction algorithms for both islanded and grid-connected modes are proposed here, where price signal motivates aggregators to adjust power consumption and generation. Privacy-preserving gossip algorithm is designed to avoid disclosing local privacy in islanded interaction. Demand response (DR), as an important means of interaction, can optimize resource distribution and realize virtuous and stable market operation in grid-connected mode. Perturbation primal-dual sub-gradient method is therefore designed to optimize distributed demand response (DDR) considering global predetermined inequal constraints. Finally, taking an actual multiple-microgrid system as an example, simulation verifies the effectiveness and robustness under communication uncertainties.

&lt;italic&gt;RT-ByzCast&lt;/italic&gt;: Byzantine-Resilient Real-Time Reliable Broadcast

Today's cyber-physical systems face various impediments to achieving their intended goals, namely, communication uncertainties and faults, relative to the increased integration of networked and wireless devices, hinder the synchronism needed to meet real-time deadlines. Moreover, being critical, these systems are also exposed to significant security threats. This threat combination increases the risk of physical damage. This paper addresses these problems by studying how to build the first real-time Byzantine reliable broadcast protocol (RTBRB) tolerating network uncertainties, faults, and attacks. Previous literature describes either real-time reliable broadcast protocols, or asynchronous (non real-time) Byzantine ones. We first prove that it is impossible to implement RTBRB using traditional distributed computing paradigms, e.g., where the error/failure detection mechanisms of processes are decoupled from the broadcast algorithm itself, even with the help of the most powerful failure detectors. We circumvent this impossibility by proposing RT-ByzCast , an algorithm based on aggregating digital signatures in a sliding time-window and on empowering processes with self-crashing capabilities to mask and bound losses. We show that RT-ByzCast (i) operates in real-time by proving that messages broadcast by correct processes are delivered within a known bounded delay, and (ii) is reliable by demonstrating that correct processes using our algorithm crash themselves with a negligible probability, even with message loss rates as high as 60 percent.

Adaptive Fuzzy Backstepping Control for Stable Nonlinear Bilateral Teleoperation Manipulators With Enhanced Transparency Performance

Bilateral teleoperation technology has been widely concerned by its unique advantages in human–machine interaction-based cooperative operation systems. Communication delay, various nonlinearities, and uncertainties in teleoperation system are the main challenging issues to achieve system stability and good transparency performance. In this paper, a globally stable adaptive fuzzy backstepping control design is proposed for nonlinear bilateral teleoperation manipulators to handle the aforementioned issues. For the communication channel, instead of direct transmission of environmental torque signals, the fuzzy-based nonpower approximate environmental parameters are transmitted to the master side for environmental torque prediction, which effectively avoids the transmission of power signals in the delayed communication channel and solves the passivity problem in the traditional teleoperation system. A trajectory generator is implemented in the master side and a trajectory smoothing is applied in the slave side. Subsequently, nonlinear adaptive fuzzy backstepping controllers for master and slave are separately designed to handle the nonlinearities and uncertainties. Theoretically, the great transparency performance of both position tracking and force feedback can be achieved, and the global stability is still guaranteed under communication delay. Comparative experiments are conducted on the real platform, which verify the effectiveness and advantages of the proposed control design in some typical working scenarios.

Nonparametric Bounds for the Risk Function.

Nonparametric bounds for the risk difference are straightforward to calculate and make no untestable assumptions about unmeasured confounding or selection bias due to missing data (e.g., dropout). These bounds are often wide and communicate uncertainty due to possible systemic errors. An illustrative example is provided.

Information And Communication Technology, Uncertainty Reduction, And Dual Identification In Chinese Organizations

By employing Chinese sample, this study examined the relationship between organizational members’ use of information and communication technologies (ICT) and their identification with the immediate workgroup and the overall organization. Employees’ uncertainty level was proposed as a mediating factor in these relationships. Participants N=336 completed an online survey. Results indicated that workgroup identification (WID) was positively predicted by members’ use of organizational social media to seek work-related information, and organizational identification (OID) was positively predicted by organizational social media and intranet for the same purpose. These relationships were either partially or fully mediated by employee’s uncertainty level. Results contributed to our understanding of ICT’s role in modern collocated work settings and shed lights on ICT and identification in a non-Euro-American context.

Analysis of Uncertainty and Inconsistancy Factors in Communication between Korean mother-in-law and Vietnamese daughter-in-law-Focusing on the story ‘Two Vietnamese Daughters-in-law of a roof’ of the Documentary program "Multicultural episodes between daughters-in-law and mothers-in-law"-

Analysis of Uncertainty and Inconsistancy Factors in Communication between Korean mother-in-law and Vietnamese daughter-in-law-Focusing on the story ‘Two Vietnamese Daughters-in-law of a roof’ of the Documentary program "Multicultural episodes between daughters-in-law and mothers-in-law"-