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A series of “learning lab” projects on disaster risk management for sustainable development (DRM-SD) have been accomplished from 2014 to 2016 in Malaysia, Vietnam, Lao PDR and Cambodia by the Centre for Global Sustainability Studies. The project is designed for professionals from the disaster risk management field to encourage integration of sustainable development (SD) concerns into the larger planning framework for DRM. As a case study for capacity building (CB) evaluation, the central purpose of this study is to explore the approaches, feedbacks and implications of the DRM-SD CB project that have been developed and carried out.

Three methods have been used which are participation observations, surveys and document analysis. The results show that the project had successfully applied seven different tools to enhance analytical skills and professional knowledge of development practitioners in specific areas of DRM-SD.

Based on the survey, the project received positive response and valuable information from participants for future project development. Regarding the perspective of outcomes, the result indicates that south–south, ASEAN regional and triangular cooperation and role of higher education in DRM-SD are significant impacts from this project which can bring several benefits and should be promoted as an approach for the DRM-CB project as a whole.

It is hoped that this study will serve as a transfer learning initiative to provide approach guidelines and innovative mechanisms for DRM practitioners who will have the know-how and potential for leadership in DRM-SD.

The aim of this study is to assess healthcare workers' behavior on the congenital hypothyroidism screening program implementation based on a framework protocol and its associated factors.

A cross-sectional study was conducted using the multistage random sampling method in recruiting health clinic workers and purposive sampling techniques for hospital workers. The demographics, providers' characteristic, occupational profile, attitude, perceived behavior control (PBC), knowledge, behavioral intention and adherence to protocol were gathered using validated and reliable self-administered questionnaires.

Partial intention to adhere to protocol was 25.7%. Weak attitude (adjusted odds ratio [AOR]: 5.48, 95% confidence interval [CI]: 3.32–9.06), low PBC score (AOR: 0.91, 95% CI: 0.86–0.95) and low knowledge score (AOR: 0.85, 95% CI: 0.75–0.96) were associated with partial intention to adhere to protocol. In the self-rated adherence assessment, 92.6% of participants from health clinics, 79.1% from pediatric and 61.1% from pathology were found not adhering to protocol. There was a significant association between intention and adherence to protocol.

Documentations and observations in assessing program implementation were limited to perform in the present study. Using self-rated instruments and focusing on healthcare workers alone did not provide a comprehensive assessment.

Availability of a training module at site and regular refreshing course training should be made available to harness knowledge, attitude and behavioral perception in implementing the program activities.

Integrating the Logical Framework Approach in assessing program implementation and application of the Theory of Planned Behavior and Attitude, Subjective Norms, Self-Efficacy Model in this study were beneficial.

The purpose of this paper is to define the integration capability dimensions and create a model for self-assessing the integration capability in inter-organizational projects.

A theoretical construct of, referred in this study as integration capability framework is elaborated following a systematic literature review. Thereafter, an integration capability self-assessment model, based on maturity thinking, is derived from the theoretical framework. The self-assessment model is further developed and tested for validity within five inter-organizational project networks in cooperation with industry practitioners, representing construction, industrial engineering, and mining sectors.

The results show that inter-organizational projects can use the developed model in self-assessing the maturity levels of various integration mechanisms, thus the state of integration capability at any point in time during inter-organizational projects.

This study is an attempt to identify how the integration capability dimensions can be self-assessed in inter-organizational projects, through the maturity levels of various integration mechanisms. The results offer insights for both academics and project management practitioners.

Studies on academic entrepreneurship (AE) agree on the significant impact that Universities can have on entrepreneurial development. AE deploys through fundamental activities, like the start-up of new companies and the connection of the University with Enterprises. The purpose of this paper is to analyse the role of digital learning platforms (DLP) to connect Universities and Enterprises effectively. Although the literature has extensively investigated DLP, there is a lack of understanding of the role of DLP in supporting digital AE. This paper focuses, in particular, on the functional requirements that have to distinguish the development of DLPs supporting education-based activities of knowledge transfer between academia and enterprise.

The research is carried out, adopting a case study methodology. A single and holistic case regarding a DLP developed for the strategic and exclusive deployment of AE activities is proposed to describe and discuss the functional requirements of such Platform.

The DLP is a virtual learning space in which Enterprises and Universities can interact. The definition of design requirements is crucial for the efficacy of DLPs and needs to be carefully supported. Various criteria are proposed, respect to the various stakeholders engaged in DAE learning platform (Universities, Enterprises, students, employees), and according to the short- and long-term objectives of Universities and Entrepreneurship connection.

The paper explores an original case of DLP established in AE, to connect Universities and Enterprises. The research also sheds light on the under focussed typology of AE activities regarding education-based knowledge exchange. They are currently unaddressed by the literature on AE.

This paper proposes a holistic, proactive and adaptive approach to cybersecurity from a service lens, given the continuously evolving cyber-attack techniques, threat and vulnerability landscape that often overshadow existing cybersecurity approaches.

Through an extensive literature review of relevant concepts and analysis of existing cybersecurity frameworks, standards and best practices, a logical argument is made to produce a dynamic end-to-end cybersecurity service system model.

Cyberspace has provided great value for businesses and individuals. The COVID-19 pandemic has significantly motivated the move to cyberspace by organizations. However, the extension to cyberspace comes with additional risks as traditional protection techniques are insufficient and isolated, generally focused on an organization's perimeter with little attention to what is out there. More so, cyberattacks continue to grow in complexity creating overwhelming consequences. Existing cybersecurity approaches and best practices are limited in scope, and implementation strategies, differing in strength and focus, at different levels of granularity. Nevertheless, the need for a proactive, adaptive and responsive cybersecurity solution is recognized.

This paper presents a model that promises proactive, adaptive and responsive end-to-end cybersecurity. The proposed cybersecurity continuity and management model premised on a service system, leveraging on lessons learned from existing solutions, takes a holistic analytical view of service activities from source (service provider) to destination (Customer) to ensure end-to-end security, whether internally (within an organization) or externally.

The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios.

A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications.

First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects.

The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.

As main mode of modern service industry and future economy society, the research on crowd network can greatly facilitate governances of economy society and make it more efficient, humane, sustainable and at the same time avoid disorders. However, because most results cannot be observed in real world, the research of crowd network cannot follow a traditional way. Simulation is the main means to put forward related research studies. Compared with other large-scale interactive simulations, simulation for crowd network has challenges of dynamic, diversification and massive participants. Fortunately, known as the most famous and widely accepted standard, high level architecture (HLA) has been widely used in large-scale simulations. But when it comes to crowd network, HLA has shortcomings like fixed federation, limited scale and agreement outside the software system.

This paper proposes a novel reflective memory-based framework for crowd network simulations. The proposed framework adopts a two-level federation-based architecture, which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem.

With reference to HLA, this paper proposes a novel reflective memory-based framework toward crowd network simulations. The proposed framework adopts a two-level federation-based architecture, system-level simulation (system federation) and application-level simulation (application federations), which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem.

Simulation syntax and semantic are all settled under this framework by templates, especially interface templates, as simulations are separated by two-level federations, physical and logical simulation environment are considered separately; the definition of simulation execution is flexible. When developing new simulations, recompile is not necessary, which can acquire much more reusability, because reflective memory is adopted as share memory within given simulation execution in this framework; population can be perceived by all federates, which greatly enhances the scalability of this kind of simulations; communication efficiency and capability has greatly improved by this share memory-based framework.