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InfoMall is a program led by the Northeast Parallel Architectures Center featuring a partnership of approximately twenty‐four organizations with a plan for accelerating development of the High‐Performance Computing and Communications (HPCC) software and systems industry. HPCC is a critical technology where the United States has clear international leadership and which will have unprecedented impact on industry, education, society, and defense. The communications component of HPCC is critical to developing HPCC products. Acceptance of HPCC by these real‐world sectors has been delayed by the extremely hard problem of HPCC software development. InfoMall employs a novel technology development strategy involving closely linked programs in technology extraction and certification, software development, marketing, education, and training, economic development, and small business support. The process is constructured and explained by analogy to a full‐service set of stores in a shopping mall.

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

The World Library Summit on Global Knowledge Renaissance was a conference organised by the National Library Board of Singapore in April 2002. An overview of the papers presented which covered the broad themes of knowledge augmentation, cultural entrepreneurship and knowledge governance is given. In addition descriptions of visits made to libraries in Singapore following the conference are provided.

Women cross-border traders face impediments in their entrepreneurial work from time-to-time. To overcome these impediments, females need to take on self-concept (self-esteem, self-confidence, social roles) mediated by self-organization (adaptability, interaction, team working) in order to thrive in cross-border trading (CBT), using evidence from Uganda. So, in this paper the authors explain the behavior of a female who succeeds in CBT with interest of scaling it up to empower more female entrepreneurs.

This study is a correlational and cross-sectional type. A questionnaire survey of 288 females was used. The data collected were analyzed through SPSS.

The results reveal that self-concept, mediated by self-organization, controlled by tenure in business and the age of a female in CBT significantly influences CBT behavior among females in Uganda.

This study focused on females who are involved in CBT in Uganda. Therefore, it is likely that the results may not be generalized to other settings. The results show that for females to succeed in CBT, self-concept and self-organization affect CBT behavior once they are controlled by tenure in business and the age of a female in CBT at more than 30 years of age and longer than 5 years.

This study provides initial evidence that self-concept, mediated by self-organization, controlled by tenure in business and age of a CBT directly affects CBT behavior, using evidence from an African developing country – Uganda.

Based on resource dependence theory and transaction cost economics this study explores how green customer integration (GCI) affects financial performance via information sharing and opportunistic behavior, and the moderating effects of dependence and trust.

This study develops a theoretical model and tests it using data from two-waved survey data of 206 Chinese manufacturers. The hypotheses were tested using hierarchical linear regression analysis.

The results show that GCI has a significant and positive impact on information sharing, but its impact on opportunistic behavior is insignificant. Notably, information sharing has a significant and positive impact on financial performance, while opportunistic behavior has an insignificant impact on financial performance. In addition, dependence negatively moderates the impact of GCI on information sharing and positively moderates the impact of GCI on opportunistic behavior. Trust negatively moderates the impact of GCI on opportunistic behavior.

Although GCI has received widespread attention, how it affects a firm's performance remains unclear. Most previous studies have focused only on its bright side and ignored its dark side. This study highlights how GCI affects financial performance through information sharing and opportunistic behavior, and the moderating effects of dependence and trust. This enriches the understanding of how and under what conditions GCI affects a firm's performance.

Shared decision making (SDM) prioritises joint deliberation between practitioner and service user, and a respect for service-users’ experiential knowledge, values and preferences. The purpose of this paper is to review the existing literature pertaining to key stakeholders’ attitudes towards SDM in mental health. It examines whether perceived barriers and facilitators differ by group (e.g. service user, psychiatrist, nurse and social worker) and includes views of what facilitates and hinders the process for service users and practitioners.

This review adopts the principles of a qualitative research synthesis. A key word search of research published between 1990 and 2016 was undertaken. Qualitative, quantitative and mixed methods studies were included.

In total, 43 papers were included and several themes identified for service user and practitioner perspectives. Both practitioners and service users see SDM as an ethical imperative, and both groups highlight the need to be flexible in implementing SDM, suggesting it is context dependent. A range of challenges and barriers are presented by both practitioners and service users reflecting complex contextual and cultural features within which interactions in mental health take place. There were qualitative differences in what service users and practitioners describe as preventing or enabling SDM. The differences highlighted point towards different challenges and priorities in SDM for service users and practitioners.

The presentation of nuanced views and attitudes that practitioners and service users hold represent an important and under reported area and offer insight into the reasons for the gap between idealised policy and actual practice of SDM in mental health settings.