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The adverse interactions between disruptions can increase the supply chain's vulnerability. Accordingly, establishing supply chain resilience to deal with disruptions and employing business continuity planning to preserve risk management achievements is of considerable importance. The aforementioned idea is discussed in this study.

This study proposes a multi-objective optimization model for employing business continuity management and organizational resilience in a supply chain for responding to multiple interrelated disruptions. The improved augmented e-constraint and the scenario-based robust optimization methods are adopted for multi-objective programming and dealing with uncertainty, respectively. A case study of the automotive battery manufacturing industry is also considered to ensure real-world conformity of the model.

The results indicate that interactions between disruptions remarkably increase the supply chain's vulnerability. Choosing a higher fortification level for the supply chain and foreign suppliers reduces disruption impacts on resources and improves the supply chain's resilience and business continuity. Facilities dispersion, fortification of facilities, lateral transshipment, order deferral policy, dynamic capacity planning and direct transportation of products to markets are the most efficient resilience strategies in the under-study industry.

Applying resource allocation planning and portfolio selection to adopt preventive and reactive resilience strategies simultaneously to manage multiple interrelated disruptions in a real-world automotive battery manufacturing industry, maintaining the long-term achievements of supply chain resilience using business continuity management and dynamic capacity planning are the main contributions of the presented paper.

Stochastic uncertainties in material parameters have a significant impact on the analysis of real-world electromagnetic compatibility (EMC) problems. Conventional approaches via the Monte-Carlo scheme attempt to provide viable solutions, yet at the expense of prohibitively elongated simulations and system overhead, due to the large amount of statistical implementations. The purpose of this paper is to introduce a 3-D stochastic finite-difference time-domain (S-FDTD) technique for the accurate modelling of generalised EMC applications with highly random media properties, while concurrently offering fast and economical single-run realisations.

The proposed method establishes the concept of covariant/contravariant metrics for robust tessellations of arbitrarily curved structures and derives the mean value and standard deviation of the generated fields in a single-run. Also, the critical case of geometrical and physical uncertainties is handled via an optimal parameterisation, which locally reforms the curvilinear grid. In order to pursue extra speed efficiency, code implementation is conducted through contemporary graphics processor units and parallel programming.

The curvilinear S-FDTD algorithm is proven very precise and stable, compared to existing multiple-realisation approaches, in the analysis of statistically-varying problems. Moreover, its generalised formulation allows the effective treatment of realistic structures with arbitrarily curved geometries, unlike staircase schemes. Finally, the GPU-based enhancements accomplish notably accelerated simulations that may exceed the level of 120 times. Conclusively, the featured technique can successfully attain highly accurate results with very limited system requirements.

Development of a generalised curvilinear S-FDTD methodology, based on a covariant/contravariant algorithm. Incorporation of the important geometric/physical uncertainties through a locally adaptive curved mesh. Speed advancement via modern GPU and CUDA programming which leads to reliable estimations, even for abrupt statistical media parameter fluctuations.

This paper proposes a dexel‐based virtual prototyping system, which builds a virtual prototype with dexels or rectangular strips of solid. The approach resembles the physical fabrication process of most powder‐based rapid prototyping (RP) systems. It simulates an RP process to create a virtual prototype. Colour virtual prototypes may also be fabricated relatively easily. Thus, the designer can perform design validation and accuracy analysis easily in a virtual environment as if using a physical prototype. In addition to numeric quantification of the RP process, the system provides vivid visualisations of the prototype for studying its characteristics. Furthermore, the prototype may be superimposed on the product model, and the areas with dimensional errors beyond design limits may be clearly highlighted for subsequent improvement. The designer may thus analyse and compare the surface texture point‐by‐point of the prototype with the product design.

An arterial blood gas (ABG) interpretation remains indispensable tool to assess and monitor critically ill patients in the intensive care unit or other critical care settings. This paper proposes a mobile‐based interpreter for ABG tests with the aim of providing accurate diagnosis in face of multiple acid‐base and oxygenation disorders. The paper aims to discuss these issues.

A rule‐based expert system is designed and implemented using interpretation knowledge gathered from specialist physicians and peer‐reviewed medical literature. The gathered knowledge of ABG tests are organized into premise‐explanation pairs to deliver reliable evaluation with the appropriate differential in a timely manner.

Performance of the developed interpreter prototype was assessed using a dataset of 74 ABG tests gathered from medical literature and clinical practice. The obtained results demonstrated that the identified acid‐base and oxygenation disorders and their differential diagnoses are accurately correlated with those assessed manually by consultant specialist physicians.

This application is foreseen to be an everyday tool for clinicians at various levels; however, further studies are needed to evaluate its eventual impact on patients’ outcomes.

The contribution of this paper is the development of a new ABG interpreter which combines both the acid‐base and oxygenation disorders in a single application. Unlike existing ABG interpreters, it is comprehensive and capable of accurately identifying all kinds of acid‐base disorders and their combinations. In addition, it utilizes urine electrolytes which are useful tools in the differential diagnosis of normal anion gap metabolic acidosis and metabolic alkalosis. The interpretation algorithm is also designed to be flexible for some clinical settings which lack some input test data.

In spite of the popularity of learning analytics (LA) in higher education institutions (HEIs), the success rate and value gained through LA projects is still little and unclear. The existing research on LA focusses more on tactical capabilities rather than its effect on organizational value. The key questions are what are the expected benefits for the institution? And how the investment in LA can bring tangible value? In this research, the authors proposed a value realization framework from LA extending the existing framework of information technology value.

The study includes a detailed literature review focusing on the importance, existing frameworks and LA adoption challenges. Based on the identified research gap, a new framework is designed. The framework depicts the several constructs and their relationships focusing on strategic value realization. Furthermore, this study includes three case studies to validate the framework.

The framework suggests that leveraging LA for strategic value demands adequate investment not only in data infrastructure and analytics but also in staff skill training and development and strategic planning. Universities are required to measure the strategic role of LA and spend wisely in quality data, analytical tools, skilled staff who are aware of the latest technologies and data-driven opportunities for continuous improvement in learning.

The framework permits education leaders to design better strategies for attaining excellence in learning and teaching, and furnish learners with new data to settle on the most ideal decisions about learning. The authors believe that the appropriation of this framework and consistent efficient interest in learning analytics by the higher education area will prompt better results for learners, colleges and more extensive society. The research also proposes two approaches and eleven research agendas for future research based on the framework. The first is based on the constructs and their relationships in LA value creation, whereas the later one focusing on identifying problems associate with it.

The purpose is to realize precise apicoectomy with less surgical risk and improved quality and efficiency.

First, the procedure of precise apicoectomy based on additive manufacturing (AM) and digital design is proposed. With CT images of the patient's oral, a 3D model of alveolar bone and teeth is reconstructed, and based on this model, the infected tissue and enclosed root tip can be determined. Thus, a surgical plan can be created based on clear anatomical relationships and minimal negative constraints, which will then determine the drill position, direction and depth, as well as the resection length of root tip. With this plan, a surgical guide design is performed via a composite model from reversed plaster models and hard tissue models from CT, and accessory tools including drill with stop plane and handle are also selected. With the surgical guide, the virtual plan in the computer can be realized in the clinic.

With this methodology, the dentist can perform root-end resection with greater accuracy, save more than 30 percent of operatory time, and the discomfort to the patient is reduced to a minimum.

The proposed methodology has been used in ten cases for root-end resections. In fact, this method of designing a computer-based treatment plan with a 3D model of a patient and applying it in the clinic through guiding tools can be used in other surgeries, such as orthognathic surgery or osteotomy.

This case report illustrates that with AM and digital design methods, optimal operational plans can be designed and realized for apicoectomy, and the quality and efficiency of clinical surgery are greatly improved compared with conventional methods.

Purpose – This chapter investigates vulnerability to poverty in the Republic of Haiti.

Methodology – We use a hierarchical modeling technique to allow the assessment and decomposition of vulnerability to poverty by exploiting the short-panel structure of nested data in a cross section.

Originality – Specifically, a three-level hierarchical model with a partially Bayesian restricted maximum likelihood is used in the estimation procedure. This is novel in this literature.

Findings – The decomposition method adopted in this chapter reveals that vulnerability in the Republic of Haiti is largely a rural phenomenon and is correlated negatively with schooling. The results also disclose the lack of equality in various aspects of circumstances or opportunities, including education, as the salient factor determining the status and level of vulnerability of households. Most importantly, among the different shocks affecting household's income, it is found that meso-level shocks are in general far more important than covariate shocks. This finding points to some interesting policy implications in terms of decentralizing policies and delegating more powers and providing better means to local governments to enhance household resilience to shocks and to alleviate their vulnerability to poverty.

The purpose of this paper is to explore the role of middle managers in the corporate entrepreneurship process that drives new capability development. Middle managers are highlighted as key entrepreneurial agents because of their special position in an organization.

The paper draws on existing capability development and corporate entrepreneurship literature and develops a conceptual model and research propositions that are illustrated through three examples from a Chinese private firm.

This paper contends the dual role of middle managers, both as change implementers to follow pre-set rules of an existing corporate entrepreneurship system and as change initiators to bring new rules to improve the existing system.

The paper is conceptual in nature, advancing the understanding of middle managers’ role in corporate entrepreneurship. The paper provides directions for future empirical research.

The interactions between middle managers and other organizational agents are discussed in the propositions. This paper suggests the importance of empowering middle managers to facilitate changes in complex internal environments.

The paper provides a unique theoretical contribution by introducing the interface-based, multi-level conceptual model of corporate entrepreneurship toward new capability development.

Six Sigma teams are special types of quality improvement teams which originated in the USA in the 1980s and later became popular in manufacturing enterprises worldwide. One dilemma for this type of teams is that they have to generate innovative solutions to solve urgent problems, while they are strictly bound by the rigorous Six Sigma approach. Another important issue is that Six Sigma is a typical western concept and the philosophy behind it contradicts some of the traditional Chinese values. This study seeks to examine the knowledge flow in Six Sigma teams in order to understand how the teams accommodate these conflicts.

The study applies a case study methodology and uses a combination of storytelling and follow‐up interviews.

The results show that Six Sigma teams go through a cycle from transforming the external input into technical knowledge, practical knowledge and finally critical knowledge to create opportunities for improvement. Another finding is that the teams are influenced by both the western philosophy, for example, favouring analytical data, and Chinese values, for example, relying on input from the senior management and apprenticeship mode of learning.

By incorporating cultural elements into the relevant literature of Six Sigma, this study gives an insight into the influence of the cultural factors from both the west and the east on the knowledge flow of Chinese Six Sigma teams in a manufacturing enterprise.