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The authors aim to investigate the observability properties of the process of simultaneous localization and mapping of an autonomous underwater vehicle (AUV), a challenging and important problem in marine robotics, and illustrate the derived results through computer simulations and experimental results with a real AUV.

The authors address the single/multiple beacon observability analysis of the process of simultaneous localization and mapping of an AUV by deriving the nonlinear mathematical model that describes the process; then applying a suitable coordinate transformation, and subsequently a time-scaling transformation to obtain a linear time varying (LTV) system. The AUV considered is equipped with a set of inertial sensors, a depth sensor, and an acoustic ranging device that provides relative range measurements to a set of stationary beacons. The location of the beacons does not need to be necessarily known and in that case, the authors are also interested to localize them. Numerical tests and experimental results illustrate the derived theoretical results.

The authors show that if either the position of one of the beacons or the initial position of the AUV is known, then the system is at least locally weakly observable, in the sense that the set of indistinguishable states from a given initial configuration contains a finite set of isolated points. The simulations and experiments results illustrate the findings.

In the single and multiple beacon case and for manoeuvres with constant linear and angular velocities both expressed in the body-frame, known as trimming or steady-state trajectories, the authors derive conditions under which it is possible to infer the state of the resulting system (and in particular the position of the AUV). The authors also describe the implementation of an advanced continuous time constrained minimum energy observer combined with multiple model techniques. Numerical tests and experimental results illustrate the derived theoretical results.

The purpose of this paper is to describe a calibration method developed to improve the accuracy of a six degrees-of-freedom medical robot. The proposed calibration approach aims to enhance the robot’s accuracy in a specific target workspace. A comparison of five observability indices is also done to choose the most appropriate calibration robot configurations.

The calibration method is based on the forward kinematic approach, which uses a nonlinear optimization model. The used experimental data are 84 end-effector positions, which are measured using a laser tracker. The calibration configurations are chosen through an observability analysis, while the validation after calibration is carried out in 336 positions within the target workspace.

Simulations allowed finding the most appropriate observability index for choosing the optimal calibration configurations. They also showed the ability of our calibration model to identify most of the considered robot’s parameters, despite measurement errors. Experimental tests confirmed the simulation findings and showed that the robot’s mean position error is reduced from 3.992 mm before calibration to 0.387 mm after, and the maximum error is reduced from 5.957 to 0.851 mm.

This paper presents a calibration method which makes it possible to accurately identify the kinematic errors for a novel medical robot. In addition, this paper presents a comparison between the five observability indices proposed in the literature. The proposed method might be applied to any industrial or medical robot similar to the robot studied in this paper.

Penetrator plays an important role in the exploration of Moon and Mars. The navigation method is a key technology during the development of penetrator. To meet the high accuracy requirements of Moon penetrator, this paper aims to propose two kinds of navigation systems.

The line of sight of vision sensor between the penetrator and Moon orbiter could be utilized as the measurement during the navigation system design. However, the analysis of observability shows that the navigation system cannot estimate the position and velocity of penetrator, when the line of sight measurement is the only resource of information. Therefore, the Doppler measurement due to the relative motion between penetrator and the orbiter is used as the supplement. The other option is the relative range measurement between penetrator and the orbiter. The sigma-point Kalman Filtering is implemented to fuse the information from the vision sensor and Doppler or rangefinder. The observability of two navigation system is analyzed.

The sigma-point Kalman filtering could be used based on vision sensor and Doppler radar or laser rangefinder to give an accurate estimation of Moon penetrator position and velocity without increasing the payload of Moon penetrator or decreasing the estimation accuracy. However, the simulation result shows that the last method is better. The observability analysis also proves this conclusion.

Two navigation systems are proposed, and the simulations show that both systems can provide accurate estimation of states of penetrator.

Two navigation methods are proposed, and the observability of these navigation systems is analyzed. The sigma-point Kalman filtering is first introduced to the vision-based navigation system for Moon penetrator to provide precision navigation during the descent phase of Moon penetrator.

Motivated by the problems that the positioning error of strap-down inertial navigation system (SINS) accumulates over time and few sensors are available for midwater navigation, this paper aims to propose a self-aided SINS scheme for the spiral-diving human-occupied vehicle (HOV) based on the characteristics of maneuvering pattern and SINS error propagation.

First, the navigation equations of SINS are simultaneously executed twice with the same inertial measurement unit (IMU) data as input to obtain two sets of SINS. Then, to deal with the horizontal velocity provided by one SINS, a delay-correction high-pass filter without phase shift and amplitude attenuation is designed. Finally, the horizontal velocity after processing is used to integrate with other SINS.

Simulation results indicate that the horizontal positioning error of the proposed scheme is less than 0.1 m when an HOV executes spiral diving to 7,000 meters under the sea and it is inherently able to estimate significant sensors biases.

The proposed scheme can provide a precise navigation solution without error growth for spiral-diving HOV on the condition that only IMU is required as a navigation sensor.

The purpose of this paper is to provide a retrospective analysis of computer simulation’s role in accelerating individual innovation adoption decisions. The process innovation examined is Lean Systems Thinking, and the organizational context is the imaging department of an Australian public hospital.

Intrinsic case study methods including observation, interviews with radiology and emergency personnel about scheduling procedures, mapping patient appointment processes and document analysis were used over three years and then complemented with retrospective interviews with key hospital staff. The multiple data sources and methods were combined in a pragmatic and reflexive manner to explore an extreme case that provides potential to act as an instructive template for effective change.

Computer simulation of process change ideas offered by staff to improve patient-flow accelerated the adoption of the process changes, largely because animated computer simulation permitted experimentation (trialability), provided observable predictions of change results (observability) and minimized perceived risk.

The difficulty of making accurate comparisons between time periods in a health care setting is acknowledged.

This work has implications for policy, practice and theory, particularly for inducing the rapid diffusion of process innovations to address challenges facing health service organizations and national health systems.

The research demonstrates the value of animated computer simulation in presenting the need for change, identifying options, and predicting change outcomes and is the first work to indicate the importance of trialability, observability and risk reduction in individual adoption decisions in health services.

Heuristic algorithms have been widely used in different types of optimization problems. Their unique features in terms of running time and flexibility have made them superior to deterministic algorithms. To accurately compare different heuristic algorithms in solving optimization problems, the final optimal solution needs to be known. Existing deterministic methods such as Exhaustive Search and Integer Linear Programming can provide the final global optimal solution for small-scale optimization problems. However, as the system grows the number of calculations and required memory size incredibly increases, so applying existing deterministic methods is no longer possible for medium and large-scale systems. The purpose of this paper is to introduce a novel deterministic method with short running time and small memory size requirement for optimal placement of Micro Phasor Measurement Units (µPMUs) in radial electricity distribution systems to make the system completely observable.

First, the principle of the method is explained and the observability of the system is analyzed. Then, the algorithm’s running time and memory usage when applying on some of the modified versions of the Institute of Electrical and Electronics Engineers 123-node test feeder are obtained and compared with those of its deterministic counterparts.

Because of the innovative method of step-by-step placement of µPMUs, a unique method is developed. Simulation results elucidate that the proposed method has unique features of short running time and small memory size requirements.

While the mathematical background of the observability study of electricity distribution systems is very well-presented in the referenced papers, the proposed step-by-step placement method of µPMUs, which shrinks unobservable parts of the system in each step, is not discussed yet. The presented paper is directly applicable to typical problems in the field of power systems.

This paper sets out to examine the factors influencing internet‐based e‐commerce in the electronic manufacturing companies in Malaysia.

The sample data are derived from a questionnaire survey of 194 companies selected from the Federation of Malaysian Manufacturer lists to investigate the study hypotheses. Roger's five innovation diffusion characteristics were considered as factors that affect EC adoption and security/confidentiality was taken as an additional factor for this study.

The multiple regression analysis results indicate that relative advantage, compatibility, complexity, observability and security appear significant. Relative advantage and compatibility have positive and significant influence on EC adoption whereas complexity and security have negative effects. This study also revealed a non‐significant relationship between trialability and e‐commerce adoption.

The results are limited within the sample of electronic manufacturing companies in Malaysia, so the results cannot be generalized.

This study provides a greater understanding of managers' perception of e‐commerce adoption in their manufacturing companies. Those interested in promoting their business online may find these results helpful in guiding their efforts.

This study aims to carry out a critical analysis of the methods used to deal with the regulatory impact assessment while proposing an alternative method to overcome some of the drawbacks of the aforementioned methods.

To achieve the objective of this work, the methods currently used in regulatory impact analysis are presented by highlighting their scope and the problems they may pose during their applications. After that, the adjusted variant of radial measure is suggested as an alternative method to the aforementioned methods while showing its relevance with regard to other methods using pertinent criteria. Finally, for concretization, a case study related to the sanctions against Russia after its invasion of Ukraine is presented.

The findings show that regulations related to the sanctions against Russia are good enough, with a score of 0.846. However, this score is less good in several countries like Germany (0.671), Italy (0.677) and France (0.745) and in the poorest countries.

The originality of this work resides in using a novel method in the regulatory impact analysis field, which is adjusted variant of radial measure. This method increases the effectiveness of the regulatory impact assessment.

Bloggers often create digital content. Diffusion of the creative articles can make many bloggers or readers visit blog platforms. Restated, diffusion of the creative articles can assist blog service providers (BSPs) to retain bloggers and attract new bloggers. Thus, the research is conducted on creative article diffusion on blogs based on innovation diffusion theory and social network theory. The paper aims to discuss this issue.

In this study, an information system was used to collect 250 creative articles and social network data of these creative articles. Validity of the specific study hypotheses is tested by using multi-regression analysis.

Analytical results indicate both observability and network density positively affect creative article diffusion, and ties-strength negatively affects creative article diffusion.

Since the interpersonal interactive mechanism of blogs differs from that of social network websites, bloggers establish different social networks which may influence innovation diffusion. However, different websites may have different interpersonal interactive mechanisms. Therefore, the results of this study should not be over-generalized.

For diffusing information, BSPs may focus on blog articles with trackback rate below 10 percent among the friends-bloggers network and advertise these articles to make their trackback rate increase to 10-20 percent to reach the self-sustaining status. This strategy ensures the largest payoff from creative article diffusion.

This study contributes to the knowledge of social network and innovation diffusion on blog website and develops a model explaining how antecedents influence creative article diffusion.

The purpose of this paper is to achieve accurate integrated navigation results for the unmanned aerial vehicle (UAV) systems even in the presence of possible navigation faults in the subsystems of the federated Kalman filter.

The federated Kalman filter is modified from two aspects to get accurate navigation results under abnormity. First, time-variant vector distribution coefficients trading off the navigation accuracy and the observability degree of each state component are computed to replace the traditional scalar coefficients. Second, a fault-tolerant filter is proposed as the local navigation filter.

Simulations for the navigation of a UAV system show that the proposed method can be applied for accurate navigation purpose even in the presence of subsystem navigation faults.

New fault-tolerant federated Kalman filters for integrated navigation are presented to achieve accurate navigation solutions.