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The aim of this paper is to demonstrate the application and usefulness of quality function deployment (QFD) in large‐scale system redesign, such as the system of social services serving a large urban municipality. Over the past ten years, the author has experimented in applying QFD to the problem of large‐scale social system redesign. With each application, lessons have been learned that have increased the usefulness of the technique. The paper concludes with a case study detailing the most recent application of QFD in the redesign of services to the deaf and hard of hearing to highlight the how the technique is currently being applied. Traditional tools and approaches used to support large‐scale system redesign, such as program evaluation, become stretched beyond their capacity when applied to complex systems. QFD has proved itself capable of handling this complexity, effectively supporting the redesign of these complex systems. It has further demonstrated its usefulness as a framework within which traditional tools may regain their relevance. Governments, social agencies, not for profit agencies, like other organizations, are all seeking to do more with less. Recently, these efforts have emphasized taking a systemic approach – moving away from the evaluation of a single agency or program to evaluating how the combination of agencies and programs (the system) work together to achieve social outcomes. The ability of QFD to handle the complexity of such a task makes it the ideal approach to addressing these types of problems. The application of QFD to the redesign of complex social systems indicates it may prove equally useful to applications in related fields including organizational design and community planning.

The purpose of this paper is to propose a decentralized observer for large‐scale singular systems.

In this paper, the authors investigate the problem of observers' design for large‐scale singular systems. The proposed decentralized observer is based on a new parameterization of the generalized Sylvester equation solution. The considered system is partitioned into small‐sizes interconnected subsystems with unknown interconnections.

A decentralized observer based on new parameterization of generalized Sylvester equation. The performance of the proposed approach is illustrated by a numerical example.

The proposed approach unites the full‐order, the reduced‐order and the minimal order observer design for large‐scale system. The conditions of the existence of this observer are given in the linear matrix inequalities (LMI) form.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

Economic load dispatch (ELD) is one of the crucial optimization problems in power system planning and operation. The ELD problem with valve point loading (VPL) and multi-fuel options (MFO) is defined as a non-smooth and non-convex optimization problem with equality and inequality constraints, which obliges an efficient heuristic strategy to be addressed. The purpose of this study is to present a new and powerful heuristic optimization technique (HOT) named as squirrel search algorithm (SSA) to solve non-convex ELD problems of large-scale power plants.

The suggested SSA approach is aimed to minimize the total fuel cost consumption of power plant considering their generation values as decision variables while satisfying the problem constraints. It confers a solution to the ELD issue by anchoring with foraging behavior of squirrels based on the dynamic jumping and gliding strategies. Furthermore, a heuristic approach and selection rules are used in SSA to handle the constraints appropriately.

Empirical results authenticate the superior performance of SSA technique by validating on four different large-scale systems. Comparing SSA with other HOTs, numerical results depict its proficiencies with high-qualitative solution and by its excellent computational efficiency to solve the ELD problems with non-smooth fuel cost function addressing the VPL and MFO. Moreover, the non-parametric tests prove the robustness and efficacy of the suggested SSA and demonstrate that it can be used as a competent optimizer for solving the real-world large-scale non-convex ELD problems.

This study has compared various HOTs to determine optimal generation scheduling for large-scale ELD problems. Consequently, its comparative analysis will be beneficial to power engineers for accurate generation planning.

To the best of the authors’ knowledge, this manuscript is the first research work of using SSA approach for solving ELD problems. Consequently, the solution to this problem configures the key contribution of this paper.

In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems.

A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed.

Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions.

The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.

Contemporary coliving is a rapidly developing housing typology, characterised by high-density private living spaces integrated with various shared, mixed-use amenities. The purpose of this research is to quantitatively examine the spatial configurations of coliving building systems, and the integration of programmatic space labels, to provide insights for architects and researchers into the homogeneity and genotypical patterns embedded within these contexts.

Coliving buildings of various scales from the United Kingdom and the USA were examined using small graph matching and inequality genotypes. The former was adopted to identify a genotype signature and assess homogeneity levels, whilst the latter provided a comparative analysis of the ranked integration values for space labels within these building systems.

Although local samples exhibited superior levels of homogeneity compared to the sample population (n = 18), the latter still evinced a marked homogeneity and no statistical difference in building system integration (mean real relative asymmetry (RRA)). Local large-scale samples showed the greatest homogeneity and building system integration of all sample groups, whilst a statistically significant distinction in building system integration was evident between large- and small-scale samples. However, a comparison of space label integration (RRA) across different building scales demonstrated that a potential genotypical pattern exists between small- and large-scale samples.

Through the identification of homogeneity and integration values related to scale and location, this research establishes an empirical, methodological framework for the generalisable spatial analysis of contemporary coliving buildings. Furthermore, genotypical patterns provide insights into space labels that are most likely to encourage copresence and social encounters between residents.

This study aims to focus on asset management of large‐scale information systems supporting infrastructures and especially seeks to address a methodology of their statistical deterioration prediction based on their historical inspection data. Information systems are composed of many devices. Deterioration process i.e. wear‐out failure generation process of those devices is formulated by a Weibull hazard model. Furthermore, in order to consider the heterogeneity of the hazard rate of each device, the random proportional Weibull hazard model, which expresses the heterogeneity of the hazard rate as random variables, is to be proposed.

Large‐scale information systems comprise many components, and different types of components might have different hazard rates. Therefore, when analyzing faults of information systems that comprise various types of devices and components, it is important to consider the heterogeneity of the hazard rates that exist between the different types of components. In this study, with this in consideration, the random proportional Weibull hazard model, whose heterogeneity of hazard rates is subject to a gamma distribution, is formulated and a methodology is proposed which estimates the failure rate of various components comprising an information system.

Through a case study using a traffic control system for expressways, the validity of the proposed model is empirically verified. Concretely, as for HDD, the service life at which the survival probability is 50 percent is estimated as 158 months. However, even for the same HDD, use environment differs according to usage. Actually, among the three different usages (PC, server, others), failures happen earliest in the case of PCs, which have the highest heterogeneity parameter and a survival probability of 50 percent after 135 months of usage. On the other hand, as for others, its survival probability is 50 percent at 303 months.

To operationally express the heterogeneity of failure rates, the Weibull hazard model is employed as a base, and a random proportional Weibull hazard model expressing the proportional heterogeneity of hazard rates with a standard gamma distribution is formulated. By estimating the parameter of the standard proportional Weibull hazard function and the parameter of the probability distribution that expresses the heterogeneity of the proportionality constant between the types, the random proportional Weibull hazard model can easily express the heterogeneity of the hazard rates between types and components.

Enterprise resource planning (ERP) offers a streamlined system architecture to feed businesses with beneficial information in the current intense global competition. The primary concern of ERP is how to integrate different functional units to facilitate a unified flow of information. This paper aims at providing a non-trivial practice of integrating the quality control (QC) system into the core ERP processes of a real large-scaled case study.

To satisfy the purpose of the current study, a large-scale steel making holding, inclusive of 27 business units being dispersed over a wide area, has been targeted. In our research methodology, a sample of four business units is selected as the pilot cases to be investigated at first. The output results of such investigations are further extended to the other units. In light of the investigation, the existing QC working conditions of the pilot cases are assessed through the As-Is model. The To-Be models are derived based on the best practices and the integration scope is then bordered.

The findings show that the integrated QC solution has enabled the following features: the smooth interconnection between QC and other functional units like purchase and manufacturing, the ease of generating real-time performance report of QC unit, the sack of tracing the quality of any available item in the system and the root-cause of defects, and the straightforwardness of the qualitative assessment of the suppliers.

There is almost no similar practice for designing a large-sized integrated system from scratch in the target region associated with our case study while the off-the-shelf products are prohibitively expensive.

This paper includes implications for providing a standard practice on integrating a substantial module of ERP down to the smallest detail.

The value of the current paper is associated with fulfilling a critical research gap in the context of studying the QC integration into an enterprise solution. In fact, despite the importance of the QC module and its plethora of interconnection with other functional units, the literature review shows a centric lack of considering such integration in a real case study, particularly the large-scale one. Further, this paper works as a valuable study in the literature owing to not only focusing on the design and development of an integrated QC solution but also considering the deployment facet of such a practice.

One of the fundamental problems in control systems engineering is the problem of sensors and actuators placement. Decisions in this context play a key role in the success of control process. The methods developed for optimal placement of the sensors and actuators are known to be computationally expensive. The computational burden is significant, in particular, for large-scale systems. The purpose of this paper is to improve and extend the state-of-the-art methods within this field.

In this paper, a new technique is developed for placing sensor and actuator in large-scale systems by using restricted genetic algorithm (RGA). RGA is a kind of genetic algorithm which is developed specifically for sensors and actuator placement.

Unlike its other counterparts, the proposed method not only supports unstable systems but also requires significantly lower computations. The numerical investigations have confirmed the advantages of the proposed methods which are clearly significant, in particular, in dealing with large-scale unstable systems.

The proposed method is novel, and compared to the methods which have already been presented in literature is more general and numerically more efficient.

Government imperatives that drive integrated care are challenging corporate executive leadership. Conspicuous by its absence in both government's imperatives and the literature, is any reference to corporate executive leadership in transitioning a hierarchically oriented health system to a laterally integrated health system referred to, in this paper, as an integrated health system. This lack of reference to executive leadership involvement conveys either significant consequences or opportunities for corporate healthcare executives. The purpose of this qualitative, multi-case study is to explore corporate executive leadership in transitioning a hierarchically oriented health system to an integrated health system.

Between December 2017 and February 2018, a qualitative methodology and multi-case study design facilitated one hour telephone interviews with 11 presidents and four senior vice presidents. Critical case sampling was used to select the study sample from a target population of 246 corporate healthcare executives representing Ontario's major acute healthcare organizations/systems.

Corporate healthcare executives possess the requisite skills and knowledge to transition a hierarchically oriented to a laterally integrated the health system but are constrained by an undefined partnership role with government and fear of government changes.

This paper provides corporate executive leaders with a systematic leadership approach to organizational readiness, in transitioning to an integrated health system. Features and outcomes of the approach are illustrated.