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This research paper aims to optimize the calibration process for an ABB IRB 120 robot, specifically for robotic orbital milling applications, by introducing and validating the use of the observability index and telescopic ballbar for accuracy enhancement.

The study uses the telescopic ballbar and an observability index for the calibration of an ABB IRB 120 robot, focusing on robotic orbital milling. Comparative simulation analysis selects the O₃ index. Experimental tests, both static and dynamic, evaluate the proposed calibration approach within the robot’s workspace.

The proposed calibration approach significantly reduces circularity errors, particularly in robotic orbital milling, showcasing effectiveness in both static and dynamic modes at various tool center point speeds.

The study focuses on a specific robot model and application (robotic orbital milling), limiting generalizability. Further research could explore diverse robot models and applications.

The findings offer practical benefits by enhancing the accuracy of robotic systems, particularly in precision tasks like orbital milling, providing a valuable calibration method.

While primarily technological, improved robotic precision can have social implications, potentially influencing fields where robotic applications are crucial, such as manufacturing and automation.

This study’s distinctiveness lies in advancing the accuracy and precision of industrial robots during circular motions, specifically tailored for orbital milling applications. The innovative approach synergistically uses the observability index and telescopic ballbar to achieve these objectives.

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 examine the extent to which user liaison behavior and outcome control influence the process performance of information technology (IT) projects and how the IT experience, behavior observability, and outcome measurability of user liaisons affect behavior and outcome control.

A research model that integrates the IT experience, behavior observability, outcome measurability, behavior and outcome control, and performance from the perspective of user liaisons is developed. Quantitative data are obtained from 63 completed IT projects. Partial least squares technique is used to evaluate the measurement model. Hypotheses are tested through hierarchical regression analysis.

User liaisons with high IT experience exhibit decreased behavior control but increased outcome control. The outcome control of user liaisons is effective in the process performance of IT projects, whereas their behavior control insignificantly affects performance. However, the behavior observability and outcome measurability of user liaisons strengthen the effectiveness of behavior and outcome control. The behavior and outcome control of user liaisons also vary across different industries and project types.

The results of this study highlight the joint effects of the IT experience, abilities, and control decisions of user liaisons. Although the outcome control of user liaisons is an appropriate control mechanism in IT projects in consideration of the strengths of these liaisons in business knowledge and their control expenditures, the behavior control of user liaisons may also be effective in process performance if these liaisons possess high levels of behavior observability and outcome measurability.

To operate with high efficiency and minimise the risks of power failures, power systems require careful monitoring. The availability of real-time data is crucial for assessing the performance of the grid and assisting operators in gauging the present security of the grid. Traditional supervisory control and data acquisition (SCADA)-based systems actually employed provides steady-state measurement values which are the calculation premise of State Estimation. More often, however, the power grid operates under dynamic state and SCADA measurements can lead to erroneous and inaccurate calculation results. The introduction of the phasor measurement unit (PMU) which provides real-time synchronised voltage and current phasors with very high accuracy is universally recognised as an important aspect of delivering a secure and sustainable power system. PMUs are a relatively new technology and because of their high procurement and installation costs, it is imperative to develop appropriate methodologies to determine the minimum number of PMUs as well as their strategic placements to guarantee full observability of a power system. Thus, the problem of the optimal PMU placement (OPP) is formulated as an optimisation problem subject to various constraints to minimise the number of PMUs while ensuring complete observability of the grid. In this chapter, integer linear programming (ILP), genetic algorithm (GA) and non-linear programming (NLP) constrained models of the OPP problem are presented. A new methodology is proposed to incorporate several constraints using the NLP. The optimisation methods have been written in Matlab software and verified on the standard Institute of Electrical and Electronics Engineers (IEEE) 14-bus test system to authenticate their effectiveness. This chapter targets United Nations Sustainable Development Goal 7.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

By integrating the diffusion of innovation (DOI) theory, technology acceptance model (TAM), and social capital theory, the purpose of this paper is to: develop a model of consumer behavior and trial willingness toward nano-foods from product, consumer, and social perspectives; examine the effects of innovative features, consumer characteristics, and trust in authority on subjective perceptions (perceived trustworthiness and perceived benefit) as well as the social influence on attitudes toward nano-foods and trial willingness; examine the moderating role of product uncertainty on the relationship between these characteristics and subjective perceptions; and examine the effect of perceived benefit on perceived trustworthiness.

The results of the structural equation model (SEM), with nano-food knowledge data collected from 431 respondents, supported the research model and revealed the main effects hypothesized in this study and the moderating effect of product uncertainty. Simple slope analysis was further adopted to test the significant moderating effects.

The SEM results indicated that innovative characteristics (relative advantage, lack of observability, and novelty), consumer characteristics (perceived technology application), and social characteristics (trust in authority) affect perceived trustworthiness or perceived benefit. Social influence also has a direct effect on attitude toward nano-foods and trial willingness. Product uncertainty significantly moderates the relationship between characteristics (relative advantage and perceived technology application) and subjective perceptions (perceived trustworthiness and perceived benefit).

With increasing numbers and kinds of nanotechnology products now being developed and sold, it is important to go further to determine consumer perceptions and attitudes toward these. This study, thus, applied the DOI, TAM, and social capital theory to examine this issue. However, other theories might also be used to carry out research from other perspectives. This study should, thus, be seen as preliminary, and it is hoped that more works will discuss consumer attitudes toward nanotechnology products in the future.

When a new nano-food is introduced, the current study suggests that food manufacturers use the description on the package as a communicative tool. Detailing the advantages of nano-foods on food packages might be a useful way to enhance trial willingness and to reduce the fears and insecurities related to the use of nano-related products. In addition, if food manufacturers could cooperate with organizations or individuals seen as having some authority in this area (e.g. nanotechnology researchers) in order to disseminate accurate information about nanotechnology and related food products, this might be an effective way to increase sales and profits.

This is the first paper integrating the DOI, the social capital theory and the TAM to empirically investigate consumer willingness to try nano-food products.

The purpose of this paper is to plan the penetration trajectory for unmanned aerial vehicle (UAV) in the presence of radar‐guided surface to air missiles (SAMs).

The penetration trajectory planning problem is modelled based on four aspects of radar tracking features. As penetration just utilizes the low observability of radar cross section (RCS) to satisfy temporal constraints of tracking, the problem is formulated as multi‐phase trajectory planning with detected probability (MTP‐DP). While utilizing both the low observability of RCS and the radial velocity blind area of radar, the problem is formulated as multi‐phase trajectory planning with detected probability and radial velocity (MTP‐DP&RV). The pseudospectral multi‐phase optimal control based trajectory planning algorithm is proposed.

The results of the examples illustrate that the multi‐phase trajectory planning method can finely utilize the radar tracking features to optimize the comprehensive efficiency of penetration. The pseudospectral multi‐phase optimal control based trajectory planning algorithm could effectively solve the trajectory planning problem.

This paper provides new structured method to plan UAV penetration trajectory for military application and academic study.

This paper aims to find the minimum possible number of phasor measurement units (PMUs) to achieve maximum and complete observability of the power system and improve the redundancy of measurements, in normal cases (with and without zero injection bus [ZIB]), and then in conditions of a single PMU failure and outage of a single line.

An efficient approach operates adequately and provides the optimal solutions for the PMUs placement problem. The finest function of optimal PMUs placement (OPP) should be mathematically devised as a problem, and via that, the aim of the OPP problem is to identify the buses of the power system to place the PMU devices to ensure full observability of the system. In this paper, the grey wolf optimizer (GWO) is used for training multi-layer perceptrons (MLPs), which is known as Grey Wolf Optimizer (GWO) based Neural Network (“GW-NN”) to place the PMUs in power grids optimally.

Following extensive simulation tests with MATLAB/Simulink, the results obtained for the placement of PMUs provide system measurements with less or at most the same number of PMUs, but with a greater degree of observability than other approaches.

The efficiency of the suggested method is tested on the IEEE 14-bus, 24-bus, New England 39-bus and Algerian 114-bus systems.

This paper proposes a new method for placing PMUs in the power grids as a multi-objective to reduce the cost and improve the observability of these grids in normal and faulty cases.

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.

Purpose – The aim of this chapter is to analyze the measurement error due to partial observability of circumstances, given the current methodologies used to capture the inequality of opportunity.

Methodology – We limit our analysis to the case in which IOp is measured by using an inequality index and evaluated according to the ex ante and the ex post approaches proposed by Checchi and Peragine (2010). Both approaches rely on the use of two hypothetical distributions obtained by standardizing and smoothing processes so that in one of them all inequalities are due to effort and in the other they are all caused by individuals circumstances. The impact of a change in the observability of circumstances has been analyzed directly in the first case (ex ante approach) and indirectly in the second (ex post approach). Hence, in the latter results are obtained by using a decomposable inequality index, while in the first case the result holds for any Lorenz consistent inequality index.

Findings – We have shown that, in both cases, we can only identify a lower bound of opportunity inequality, and the results obtained when measuring IOp with the two approaches are biased in the same direction.

Originality – The idea that inequality of opportunity, as it is generally measured, is only a lower bound of the real inequality of opportunity has already been hinted in Peragine (2004a), Fleurbaey (2008, Chap. 9), and Ferreira and Gignoux (2011). We attempt to bring this intuition to complete fruition in this chapter by providing clear and distinct demonstrations of this result for both the ex ante and the ex post approach for measuring IOp.